Method for determining wettability index of rock from T.SUB.2 .NMR measurements

Abstract

A method for rapid wettability evaluation during exploratory drilling of a hydrocarbon. The method include pre-saturation of the sample by a brine, measuring the bulk brine's T.sub.2 NMR relaxation parameter, expelling the brine by oil in the sample, measuring the oil's bulk and pore T.sub.2 NMR relaxation parameter, measuring the brine's non-reducible content and T.sub.2 NMR relaxation parameter of water in the presence of dominant oil content, expelling the oil by the brine and measuring the T.sub.2 NMR relaxation parameter of the irreducible oil content in the dominant brine. The measurements are combined in the index:
I=[(T.sub.2WB−T.sub.2WIOIRR)/T.sub.2WB]−[(T.sub.2OB−T.sub.2OIWIRR)/T.sub.2OB], where WB is water bulk, OB is oil bulk, WIOIRR—injected pore water at the irreducible oil content, OIWIRR—injected pore oil at the irreducible water content.

Claims

1. A method of determining wettability of a porous rock, comprising: a) providing an oil and a water-based brine fluid comprising one or more isotopes selected from the group consisting of .sup.1H, .sup.2H, .sup.13C and .sup.14C; b) saturating the porous rock with the brine by pressurizing the porous rock with the brine at a pressure sufficient to overcome the capillary pressure in the pores of the porous rock and reach full saturation with the brine (S.sub.w=1); c) measuring a T.sub.2, WB signal of the brine fluid by NMR outside the porous rock; d) displacing the brine fluid with an oil by pressurizing the porous rock with the oil at a pressure sufficient to overcome the capillary pressure in the pores of the porous rock and reach a final non-decreasing content of the brine fluid, wherein the irreducible amount corresponds to pore wall-bound water; e) measuring a T.sub.2,sWR signal in the porous rock saturated with the brine fluid; f) measuring a T.sub.2,OB signal in the oil outside the porous rock by .sup.1H or .sup.13C NMR; g) saturating the porous rock with the brine until reaching an irreducible oil content; h) measuring a T.sub.2,SOR signal in the oil saturated porous rock, wherein the T.sub.2, SOR signal corresponds to the brine fluid coexisting with the residual irreducible oil in the porous rock; i) calculating a value ${\mathrm{WI}}_w=\frac{T_{2\mathrm{WB}}-T_{2,\mathrm{Sor}}}{T_{2,\mathrm{WB}}}$  representing the difference between the signal of the brine fluid outside the porous rock and the signal of the brine fluid inside the pores of the porous rock; j) calculating the value ${\mathrm{WI}}_o=\frac{T_{2,\mathrm{OB}}-T_{2,\mathrm{Swr}}}{T_{2,\mathrm{OB}}}$  representing the difference between the signal of the oil outside the pores of the porous rock and the signal of the oil inside the pores of the porous rock; k) calculating the wettability index of the porous rock I.sub.NMR=WI.sub.w−WI.sub.o.

2. The method of claim 1, further comprising, between (d) and (e), exposing the porous rock to a reduced pressure and an elevated temperature until the brine fluid evaporates to the level of <1% of a content in (d) to increase the oil-wettability of the porous rock.

3. The method of claim 1, wherein the NMR measurement includes a T.sub.2 estimated by Carr-Purcell-Meiboom-Gill (CPMG) sequence.

4. The method of claim 1, wherein the NMR is measured on a plurality of porous rock samples obtained at different depths of a geological formation.

5. The method of claim 1, further comprising one or more of: measuring a relative displacement of the oil in the porous rock in response to the increase in saturating brine pressure; measuring a relative change in conductance or resistivity of the oil in the porous rock in response to the increase in saturating brine pressure; measuring a relative redistribution of the oil and the brine fluid in the pores of the porous rock at different diameter categories of the pores.

6. The method of claim 1, further comprising: setting a bench for a wettability-prediction.

7. The method of claim 1, further comprising: comparing at least two geological formations with a down hole NMR loggin tool and/or a downhole resistivity logging tool.

8. The method of claim 1, further comprising: modeling a wettability index W according to the expression:
A.sub.1×[τ.sub.NMR.sup.B1]×[R.sup.B2]×[Φ.sub.NMR.sup.B3]×(τ.sub.NMRZ).sup.B4/(τ.sub.NMRXY).sup.B4×S.sub.w.sup.B5×S.sub.wir.sup.B6×(ΔH/H).sup.B7×[D].sup.B8=W Where: W—is dimensionless wettability index in the range (−1, 1), A.sub.1—is an empirical proportionality factor, [τ.sub.NMR.sup.B1]—is a diffusional tortuosity determined by NMR, [R.sup.B2]—is a relative resistivity at a brine fluid saturation level, [Φ.sub.NMR.sup.B3]—is an overall porosity determined by NMR, [(τ.sub.NMRZ).sup.B4/(τ.sub.NMRXY).sup.B4]—is a ratio of diffusional tortuosity in the direction Z to one measured in the plane XY, S.sub.w.sup.B5—is a water saturation fraction, S.sub.wir.sup.B6—is an irreducible water content, (ΔH/H).sup.B7—is a fraction of the oil expelled from the porous rock at S.sub.w, (D).sup.B8—is a weight-averaged diameter of the pores; wherein the values are represent water flooding conditions in an innermost 5 mm layer of a borehole wall in the geological formation.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) A more complete appreciation of the disclosure and many of the attendant advantages thereof will be readily obtained as the same becomes better understood by reference to the following detailed description when considered in connection with the accompanying drawings, wherein:

(2) FIG. 1: The basic components of the gradient NMR installation.

(3) FIG. 2: The scheme of 90 degree flipping and synchronization for the global magnetization vector.

(4) FIG. 3: The scheme of 180 degree flipping and synchronization for the global magnetization vector.

(5) FIG. 4A. The initial orientation of the magnetization vector up-field.

(6) FIG. 4B. The initial focusing after the completion of 90 degree “flip”.

(7) FIG. 4C. Relaxation of spins post 90-degrees focusing. Faster elements lose coherence first, while the lagging remains focused.

(8) FIG. 4D. After RF irradiation from the opposite direction the former invisible elements (in 4C) become leading, face the detector coil and produce a signal. The former visible elements become lagging and are invisible.

(9) FIG. 4E. From the initial 90 degree “flip” of FIGS. 4B and 4C, the global vector first turns by 90 degrees vs, 4B and 4C (or 180 degrees vs 4A) and next additional 90 degrees, arriving at the arrangement as shown. After disconnection of RF energy, the individual magnetization vector continues synchronizing in the global transverse magnetization field M (as they do in B.sub.0 in 4A), reaching a refocusing point later in time.

(10) FIG. 4F. From the initial 90 degree “flip” of FIGS. 4B and 4C, the global vector first turns by 90 degrees vs, 4B and 4C (or 180 degrees vs 4A) and next additional 90 degrees, arriving at the arrangement as shown. The lagging elements continue to move in the transverse magnetic field M even when the RF energy is shut down, in the same sense as they converge in B.sub.0 field in 4A. The field M acts more on the lagging elements and less on the leading elements, contributing to focusing of the signal in phase, observing “echo”, even when RF is turned off.

(11) FIG. 5. Dependence of relaxation times T1 and T2 on the chemical nature, free vs. bound status and molecular weight of the molecules in the magnetized environment.

(12) FIG. 6A: General scheme of PGSE (pulse field gradient echo) for measuring molecular diffusion.

(13) FIG. 6B: The relation of RF and magnetic gradient pulses in the diffusional measurements.

(14) FIG. 6C: Development of decoherence and the subsequent re-focusing in the nuclei assembly as a function of RF pulses (hollow rectangular vertical bars) and magnetic gradient pulses (blue rectangular horizontal bars).

(15) FIG. 6D: Accumulation of data points in the diffusion measurements by NMR.

(16) FIG. 7: Diffusion ordering spectroscopy NMR (general scheme).

(17) FIG. 8A: Transformation of the fl-G data into DOSY data. The primary data: the axis S corresponds to the chemical shifts, the axis M corresponds to the intensity of magnetic pulse gradient. Different species show different rate of extinction.

(18) FIG. 8B: Transformation of the fl-G data into DOSY data. The data 8A are reorganized. The axis D corresponds to the chemical shifts, the axis fl corresponds to the intensity of magnetic pulse gradient.

(19) FIG. 9: A scheme of stimulated echo sequence (STE) NMR experiment.

(20) FIG. 10: A scheme of longitudinal encode-decode or “longitudinal eddy current delay” echo sequence NMR experiment.

(21) FIG. 11: Bipolar gradient longitudinal encode-decode BPP-LED pulse sequence NMR experiment.

(22) FIG. 12: Alternating Pulsed Field Gradient Stimulated Echo Nuclear Magnetic Resonance (APGSTE) sequence.

(23) FIG. 13: Carr-Purcell-Meiboom-Gill (CPMG) pulse train sequence.

(24) FIG. 14: High-pressure valved NMR sample tubes by Norrel.

(25) FIG. 15A: Mineral composition of Berea rock sample.

(26) FIG. 15B: Mineral composition of Indiana rock sample.

(27) FIG. 16A: Measured density at different temperatures of brine.

(28) FIG. 16B: Measured density at different temperatures of oil.

(29) FIG. 17A: Measured viscosity at different temperatures of brine.

(30) FIG. 17B: Measured viscosity at different temperatures of oil.

(31) FIG. 18: Experimental procedure flowchart followed in this study.

(32) FIG. 19: T.sub.2 distribution of Bulk fluids.

(33) FIG. 20A: T.sub.2 distribution of sample 1H at 100% brine saturated after primary drainage. The black dotted line represents the bulk brine T.sub.2 while the red dotted line is the bulk oil T.sub.2.

(34) FIG. 20B: T.sub.2 distribution of sample 1H at 100% brine saturated after draining. The black dotted line represents the bulk brine T.sub.2 while the red dotted line is the bulk oil T.sub.2.

(35) FIG. 20C: T.sub.2 distribution of sample 1H at 100% brine after aging. The black dotted line represents the bulk brine T.sub.2 while the red dotted line is the bulk oil T.sub.2.

(36) FIG. 20D: T.sub.2 distribution of sample 1H at 100% brine after imbibition. The black dotted line represents the bulk brine T.sub.2 while the red dotted line is the bulk oil T.sub.2.

(37) FIG. 21: T.sub.2 distribution of sample 2H at different saturations. The black dotted line represents the bulk brine T.sub.2 while the red dotted line is the bulk oil predominant T.sub.2.

(38) FIG. 22A: T.sub.2 distribution of sample 1S at 100% brine. The black dotted line represents the bulk brine T.sub.2 while the red dotted line is the bulk oil predominant T.sub.2.

(39) FIG. 22B: T.sub.2 distribution of sample 1S at 100% brine after primary drainage. The black dotted line represents the bulk brine T.sub.2 while the red dotted line is the bulk oil predominant T.sub.2.

(40) FIG. 22C: T.sub.2 distribution of sample 1S at 100% brine saturated after imbibition. The black dotted line represents the bulk brine T.sub.2 while the red dotted line is the bulk oil predominant T.sub.2.

(41) FIG. 23: T.sub.2 distribution of sample 2S at different saturations. The black dotted line represents the bulk brine T.sub.2 while the red dotted line is the bulk oil predominant T.sub.2.

DETAILED DESCRIPTION OF THE EMBODIMENTS

(42) Embodiments of the present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all of the embodiments of the disclosure are shown.

(43) The present disclosure will be better understood with reference to the following definitions.

(44) As used herein, the words “a” and “an” and the like carry the meaning of “one or more”. Additionally, within the description of this disclosure, where a numerical limit or range is stated, the endpoints are included unless stated otherwise. Also, all values and subranges within a numerical limit or range are specifically included as if explicitly written out.

(45) As used herein, the terms “optional” or “optionally” means that the subsequently described event(s) can or cannot occur or the subsequently described component(s) may or may not be present (e.g. 0 wt %).

(46) As used herein, the term “flip” and “flip angle” refers to the change in the orientation of the nuclear magnetic momenta in the primary magnetic field due to the absorption of radiofrequency pulse. The resulting macroscopic magnetic momentum gyrates with the resonant Larmor precession rate producing the signal detectable by a separate or the same radiofrequency coil (that produced the said pulse).

(47) As used herein, the terms “collective”, “global’ and “macroscopic” are equivalent when referred to a transverse magnetization vector M, also mentioned as “net magnetization”.

(48) As used herein, the term T1 relaxation refers to re-orientation of the nuclear spins in the direction of the primary magnetic field along the axis Z form the transverse orientation in the plane X0Y perpendicular to the axis Z. As a result, the global magnetization vector turns by 90 degrees and aligns with Z.

(49) As used herein, the term T2 relaxation refers to de-cohering of the spins in the transverse orientation to the primary magnetic field, after absorbing the energy of the RF pulse. The resonance nature of the energy transition leads to the same phase of precession for all spins and therefore the maximal possible transverse magnetization M value. Because of passing energy to the environment and field inhomogeneities, the individual magnetic momenta begin precession in different phases. The global magnetization minimizes, even without considering the re-orientation by the T1 mechanism.

(50) As used herein, the term “spin echo” refers to the process of producing the maximal NMR signal after the RF pulse is turned off, explaining the term “echo”. The phenomenon arises due to the presence of leading and lagging elements measured relative to the position of the global transverse magnetization vector M. Some spins “flip” first and some remain aligned with the primary field producing the lagging elements. The additional energy is supplied producing 180 degrees flip. In that stronger transverse magnetization environment, the individual spins feel the local field M as well as B and become synchronized in M not unlike the iron spin domains in a ferromagnetic after the magnetizing current is turned off. Since this focusing leads to maximization of the signal and takes place after the excitation energy is not provided any more, it was termed “echo”.

(51) As used herein, the term “NMR-derived diffusion coefficient” refers to the process of producing a signal in the detector coil by supplying RF energy to produce 90 degree or lower flip angle, destroying the signal by forcefully decohering the transverse magnetization vector by a magnetic gradient pulse, waiting a pre-set interval of time for the initial phase-labelled population of spins to diffuse away, refocusing the phase-labeled spins by a combination of a RF pulse and a magnetic gradient pulse. Phase-labeling means that that the spins that interacted with the first pair of RF and magnetic pulses will interact with the second pair, restoring the signal. The described process, with variations, is termed “a sequence”. The difference between the initial and the restored signal can be related to the diffusion coefficient by the Stejskal and Tanner sequence equations.

(52) FIG. 1 presents the simplified scheme of a typical apparatus for modern NMR analysis. The installation comprises the main magnet, the gradient coils, the radiofrequency (RF) coils, RF electronics, gradient amplifiers, control electronics, operator console, pulse sequence computer and image reconstruction computer. In operation, the main magnet produces a strong magnetic field in the range 0.5-3 Tesla. The gradient coils superimpose the additional (+) or (−) 0.1 Tesla contributions in the direction transverse to the axis Z (the axis of rotation inside the main magnet, the axis Z is aligned with the direction of the main magnetic field). Typically, one gradient is created in the direction of the axis X and another in the direction of Y. The extent of the gradient varies along Z. The result of the gradient application is partitioning of the space within the combined magnetic fields into small elements—voxels, which produce the diverse and voxel-specific resonance conditions. Based on Fourier series deconvolution it is possible to trace the spin echoes to the individual voxels (see below) and therefore reconstruct the spatial orientation of the factors affecting the signal magnitude (concentrations) and relaxation times (diffusion coefficients).

(53) The magnetic fields interact with the nuclei possessing uncompensated spins (odd number of protons or neutrons, counted separately in a nucleus). The spins are quantum qualities, but they manifest empirically as circular currents running around the nuclei at very high velocity and creating magnetic momenta, expressed as a product of the current by the area of the conductive contour (Amper×m.sup.2). The momenta are vector values and behave at a schematic level analogously to a macroscopic frame with an electric current placed in a magnetic field. Such a frame will align its normal vector (“magnetic momentum vector”) with the direction of the field (axis Z), the macroscopic frame will “freeze” perpendicularly to the field.

(54) The nuclei suitable for NMR comprise, without limiting, the following list of isotopes: .sup.27Aluminium, .sup.39Argon, .sup.75Arsenic, .sup.135Barium, .sup.137Barium, .sup.9Beryllium, .sup.209Bismuth, .sup.10Boron, .sup.11Boron, .sup.79Bromine, .sup.81Bromine, .sup.111Cadmium, .sup.113Cadmium. .sup.43Calcium, .sup.13Carbon, .sup.133Cesium, .sup.35Chlorine, .sup.37Chlorine, .sup.53Chromium, .sup.63Copper, .sup.65Copper, .sup.59Cobalt, .sup.2Deuterium, .sup.19Fluorine, .sup.69Gallium .sup.71Gallium, .sup.73Germanium, .sup.3Helium, .sup.1Hydrogen, .sup.2Hydrogen, .sup.3Hydrogen, .sup.113Indium, .sup.115Indium, .sup.127Iodine, .sup.57Iron, .sup.83Krypton, .sup.138Lanthanum, .sup.139Lanthanum .sup.207Lead, .sup.6Lithium, .sup.7Lithium, .sup.25Magnesium, .sup.55Manganese, .sup.199Mercury, .sup.201Mercury, .sup.95Molybdenum, .sup.97Molybdenum, .sup.21Neon, .sup.61Nickel, .sup.14Nitrogen, .sup.15Nitrogen, .sup.187Osmium, .sup.189Osmium, .sup.17Oxygen, .sup.31Phosphorus, .sup.195Platinum, .sup.39Potassium, .sup.40Potassium, .sup.41Potassium, .sup.1Proton, .sup.103Rhodium, .sup.85Rubidium, .sup.87Rubidium, .sup.45Scandium, .sup.77Selenium, .sup.29Silicon, .sup.107Silver, .sup.109Silver, .sup.23Sodium, .sup.87Strontium, .sup.33Sulfur, .sup.123Tellurium, .sup.125Tellurium, .sup.115Tin, .sup.117Tin, .sup.119Tin, .sup.47Titanium, .sup.49Titanium, .sup.3Tritium, .sup.183Tungsten, .sup.235Uranium, .sup.50Vanadium, .sup.51Vanadium, .sup.129Xenon. .sup.131Xenon, .sup.67Zinc. Of note, deuterium (2H) has the spin value+1, despite having an even number of protons and neutrons. However, the Pauli principle guiding filling of energy levels in all quantum systems applies to each particle type individually; therefore the combination of a proton and a neutron with parallel spins is not banned at the same energy level and has a lower energy than an antiparallel combination, explaining the almost exclusive dominance of the triplet deuterium vs. a possible singlet state with the antiparallel spins. By contrast, two neutrons or two protons at the same energy level must have antiparallel mutually compensating spins being of the same nature.

(55) The magnetic momenta of the nuclei should ideally align strictly along the axis Z, following the direction of the magnetic field B. However, this is impossible due to thermal motion conferring variable quantity of torque to the spinning nuclei, oriented in the magnetic field. Analogously to a mechanical toy “spinning top” or a gyroscope in gravitational fields, the introduction of the torque by the external forces alters the orbital momentum of the spinning system.

(56) Newton's second law of motion can be expressed mathematically,
F=m×a  (4)

(57) or force=mass×acceleration. The rotational equivalent for point particles may be derived as follows:
L=I×ω  (5)

(58) Wherein I—is the momentum of inertia and ω—is the angular velocity. Thus, the torque τ (i.e. the time derivative of the angular momentum) is given as:
τ=(dI/dt)×ω+I×(dω/dt)  (6)

(59) The equation (6) is the rotational analogue of Newton's Second Law and the torque is not always proportional or parallel to the angular acceleration. The external torque introduces a perpendicular component to the original orbital momentum L.sub.z of the body spinning relative to the axis Z. Under the stationary conditions, this permanent perpendicular component is directed along the tangent to a circular trajectory of motion accepted by the top of the spinning body. The circular motion that establishes after reaching the stationarity phase (after dampening of nutational motion at the non-stationary phase) is termed precession. More than one precession motions are possible simultaneously, but for simplicity, only one is assumed in the plane X0Y, normal to the axis Z. Under these simplifying assumptions, the precession angular velocity is:

(60) $\begin{array}{cc}{\omega }_p=\frac{\mathrm{mgr}}{I_s{\omega }_s}=\frac{\tau }{I_s{\omega }_s}& \left(7\right)\\ T_p=\frac{4{\pi }^2{I}_s}{{\mathrm{mgrT}}_s}=\frac{4{\pi }^2{I}_s}{\tau T_s}& \left(8\right)\end{array}$

(61) Where ω.sub.p—is the precession movement angular velocity, T.sub.p—precession movement period, I.sub.s—is the inertia momentum vs. the spinning axis, ω.sub.s—is the angular velocity vs. the spinning axis, τ is the applied torque. Analogously to mechanical systems, a spinning particle in a magnetic field experiences a precession movement due to its interactions. When a magnetic moment is placed in a magnetic field B, it experiences a torque which can be expressed in the form of a vector product:
τ=μ×B  (9)

(62) Where μ is the magnetic momentum and B is the magnetic field. For the momentum coinciding with B, the torque is zero but is non-zero for a system permuted by thermal motion or charge-charge interactions. When a torque is exerted perpendicular to the angular momentum L, it produces a change in angular momentum ΔL which is perpendicular to L, causing it to precess about the Z-axis. Labelling the precession angle as φ, we can describe the effect of the torque as follows:

(63) $\begin{array}{cc}\tau =\frac{\Delta L}{\Delta t}=\frac{L\sin \mathrm{\theta \Delta \varphi }}{\Delta t}=.Math.\mu B\sin \theta .Math.=\frac{e}{2m_e}\mathrm{LB}\sin \theta & \left(10\right)\end{array}$
The L sin θ is the projection of the original orbital momentum L aligned with the axis Z onto the perpendicular plane X0Y as a result of torque. ΔL is the change of orbital momentum, and this change is equal to a vector difference ΔL between the component L sin θ at the time t.sub.1 and the same component at the time t.sub.2, resulting due to covering the angle Δϕ in the precession. Also, μ=(e/2m.sub.e) L—the equation (10) provides a link between torque expressed through magnetic momentum and its equivalent expressed through angular momentum, both being proportional via gyromagnetic ratio (e/2m.sub.e).

(64) Considering the definition of torque according to (9) and elementary transformations produces the final form (11) below. The precession angular velocity (Larmor frequency) is

(65) $\begin{array}{cc}{\omega }_{\mathrm{Larmor}}=\frac{d\varphi }{\mathrm{dt}}=\frac{e}{2m_e}B& \left(11\right)\end{array}$

(66) The analysis of (9)-(11) shows that both the original orbital momentum L and the perpendicular component L sin θ induced by the external torque are canceling in the final expression (11). This canceling is absent in the mechanical analogy above. The resulting precession frequency is inversely proportional to the inertia m.sub.e of the spinning particle, directly proportional to the charge e and the strength of the magnetic field B. The Larmor precession frequency is a characteristic of a particle in a magnetic field and does not reflect the strength of the permutations causing deflections from the axis Z (L sin θ is canceled). Yet as a quantum system, a single particle in this minimal energy state would absorb electromagnetic energy at the same frequency as Larmor precession.

(67) A mechanical analogy is helpful to illustrate why the resonance condition is reached at the Larmor frequency. Assuming a heavy spinning top with an infinite momentum of inertia and periodic impacts by an external force, the energy transfer is the most effective when the period between the impacts is exactly equal to the period of precession. Moving from a laboratory coordinate system to the one originating in the precession spinning top leads to the external force arriving at different positions on the precession trajectory if the periods between the impacts and the precession period are different. Over an extended timeframe, the positions of impacts will find the opposing and equal counterparts, thus mutually neutralizing. For equal periods, the impacts arrive always at the same position, leading to the maximized accumulation of the transferred energy. The similar principle of the external force applied at the inner or natural frequency of oscillations defines the better-known conventional resonance.

(68) The individual nuclei oriented along the field B are at the minimal energy and when excited by the electromagnetic wave originating in the radiofrequency coils (RF coil), they experience a resonance transition and “flip” the spins in the opposite direction (against the field). This process is time-dependent, and with longer exposure to the excitation energy at the frequency of Larmor precession, the progressively greater proportion of the individual nuclei changes orientation. If originally the summary magnetization vector (vector sum of all individual magnetic momenta) was directed along the axis Z with the field, upon “flipping” the summary magnetization vector rotates by 90, 180 or an arbitrary optimized angle without limitation. FIG. 2 demonstrates the scheme of “flipping” by 90 degrees of the collective magnetization vector.

(69) According to FIG. 2, the initial orientation of the magnetic momenta is random for the nuclei in the background state (aligned with the field with Boltzmann equilibrium distribution describing the population of the energy levels). The only net magnetization component is the difference between the populations of the background and the excited states, with the predominant population in the background state (spin polarization). The upper position in FIG. 2 describes this stage. Upon sensing the RF pulse, the system gains energy by the alignment of the magnetic momenta in the same phase (lower entropy state, middle position). This phase coherence is a general property of resonance absorbance. For example, all mechanical pendulums experiencing resonance by the same external force are also expected to swing in the same phase. Also, the proportion of the energy levels changes due to the quantum transition to the excited states, corresponding to flipping some of the spins shown in the lowest position of the figure. The resulting “flipped” collective magnetic vector is the original collective magnetic vector turned by 90 degrees. In this orientation the net magnetic flux of the sample gyrates in the contour of the RF coils with the Larmor frequency, producing the maximal initial post-flip signal current. The current represents the decaying oscillations which reflect dephasing and relaxation of the high-energy magnetized state after RF pulse is turned off. The signals are proportional to the square of the primary magnetic field and directly proportional to the molar percent of the resonating nuclei. The signals can also be deconvoluted as exponential decays with the relaxation times T1 and T2, providing the most useful information about the state of the system. T1 relaxation is the process by which the net magnetization (M) grows/returns to its initial maximum value (Mo) parallel to Bo in FIG. 2. Synonyms for T1 relaxation include longitudinal relaxation, thermal relaxation and spin-lattice relaxation. The net magnetization along Z is zero during the action of the RF pulse due to the M vector flip. The net magnetization returns back to its Boltzmann distribution maximum by the equation:
M.sub.t=M.sub.max(1−e.sup.−t/T1)  (12)

(70) Where M.sub.t is the magnetization at time=t, the time after the 90° pulse, M.sub.max is the maximum magnetization at full recovery. This type of relaxation was termed “spin-lattice” due to lattice or other external environments being the acceptors of the excessive energy in the magnetized material.

(71) As the individual magnetization vectors align with the primary magnetic field, they simultaneously de-cohere since the completely random orientation of the precessions are more favourable energetically as a more probable state with higher entropy. T2 relaxation is the process by which the transverse components of magnetization (Mxy) decay or dephase. T2 relaxation is considered to follow first-order kinetics, resulting in a simple exponential decay (like a radioisotope) with time constant T2. Thus, T2 is the time required for the transverse magnetization to fall to approximately 37% (1/e) of its initial value. Synonyms for T2 relaxation are transverse relaxation and spin-spin relaxation (See Bloch F. Nuclear induction. Phys Rev 1946; 70:460-474, 1946, incorporated herein by reference in entirety). T2 relaxation occurs whenever there is T1 relaxation. Some additional processes also exist (such as static local fields and spin “flip-flops”) that cause T2 relaxation without affecting T1. T2 relaxation always proceeds at a faster rate than T1 relaxation.

(72) FIG. 3 presents vector diagrams of the individual nuclei explaining acquisition of the 180 “flip angle” in the collective magnetization state. Such “flip” angles require twice as much energy absorbed by the sample from the RF pulse, due to either longer duration or higher intensity of the excitation pulsing. If in case of 90 degree “flip”, the individual magnetization vectors are coherent and 50% are in the excited state (producing transverse orientation of the global vector, see FIG. 2), in case of 180 degree “flip” 100% of the individual nuclei are in the excited state. Upon reaching the exact 180 “flip”, no transverse precession of the global magnetization vector takes place and the receiving RF coil detects no signal. Only after relaxation begins, the global magnetization vector begins to approach the 90 degree “flip” angle when the signal is maximized before it begins to decay. Simultaneously with the T1 relaxation, decoherence and T2 relaxation takes place all the way from the 180 degree “flip” to the final “flip” state (see below). The 180 degree regime produces more complex relaxation patterns and communicates qualitatively different information supplementing the lower degree regimes. In any real NMR experiment, however, the transverse magnetization decays much faster than would be predicted by natural atomic and molecular mechanisms; this rate is denoted T2* (“T2-star”). T2* can be considered an “observed” or “effective” T2, whereas the first T2 can be considered the “natural” or “true” T2 of the formation being imaged. T2* is always less than or equal to T2. T2* results principally from inhomogeneities in the main magnetic field. These inhomogeneities may be the result of intrinsic defects in the magnet itself or from susceptibility-induced field distortions produced by the formation or other materials placed within the field.

(73) The 180 degree “flips” can be measured not only vs. the original up-field orientation of the magnetization vector but vs. the initial 90 degree “flip” in the sophisticated “spin echo” sequences of the present invention. FIG. 4A-F demonstrates such an interpretation of the 180 degree “flip”.

(74) Ideally, in each voxel of the apparatus space, all points should experience the same magnetic field and the same synchronized resonance conditions. However, inhomogeneity of the main magnetic field (“shimming”), local field shielding at some nuclei by valence electrons, different kinetics of re-orientation create a distribution of resonance frequencies. Some individual nuclei experience the spin “flip” earlier at lower delivered energy, some proceed together with the population average and some lag behind requiring a greater RF energy inputs to “flip”. As a result, not all components participate in formation of NMR signal, since some “overshoot” the transverse spin orientation in the plane X0Y that is a prerequisite for signal detection, while the others remain in the original Z-axis aligned orientation. Thus, the information about the properties of these components remains unavailable, and the overall analysis becomes incomplete.

(75) The application of saturating levels of RF energy leading to the 180 degree “flips” and “spin echo” phenomena addresses these problems (See Malcolm H. Levitt; Ray Freeman “NMR population inversion using a composite pulse”. Journal of Magnetic Resonance, 1979, 33 (2): 473-476; Carr, H. Y.; Purcell, E. M. “Effects of Diffusion on Free Precession in Nuclear Magnetic Resonance Experiments”. Physical Review, 1954, 94 (3): 630-638; Hahn, E. L. “Spin echoes”. Physical Review, 1950, 80 (4): 580-594, incorporated herein by reference in entirety). The sequence of vector diagrams illustrating the individual and collective magnetization is provided in FIGS. 4A-4F, representing still images from the animation of a Hahn echo. The red arrows can be thought of as the individual spins. Applying the first pulse rotates the spins by 90 degrees, producing an equal superposition of spin up and spin down (FIG. 2). The spins subsequently “spread out” because each is in a slightly different environment. This spreading out looks like decoherence, but it can be refocused by a second pulse which rotates the spins by 180 degrees. Several simplifications are used in this animation: no decoherence is included, and each spin experiences perfect pulses during which the environment provides no spreading. The individual spins continue focusing after disconnection of RF excitation because the surviving global transverse magnetization persists for several dozen or hundred milliseconds and the lagging individual elements experience the greatest focusing force, being perpendicular to the transverse magnetization vector M.

(76) FIG. 5 presents a qualitative diagram and quantitative data comparing T.sub.1 and T.sub.2 relaxation times in different materials, as a function of the bound vs. free character of the protons and as a function of the molecular masses of each spin-bearing moiety. FIG. 5 illustrates that T.sub.1 and T.sub.2 are the longest for freely moving molecules of smaller mass, but T.sub.1 passes through a minimum and begins to increase again for macromolecules, polymers and nanoparticles. T.sub.2 is always shorter than T.sub.1 and is especially short for solid-phase or bound species, also demonstrating a much broader dynamic range, thus indicating why T.sub.2 is the parameters of choice for assessing the condition of hydrocarbon-bearing formation activated by aqueous acidic emulsion. Both T.sub.1 and T.sub.2 are shorter for hydrocarbons vs. free water.

(77) Rationalizing of these trends is possible recalling that the detected NMR signal is produced by an ensemble of the flipped spin precessions, rotating in the transverse X0Y plane in the same phase (a necessary simplification). This assembly stores the energy absorbed from the RF pulse in the two major forms: (a) decreased entropy component by maintaining phase coherence and (b) orientation of the magnetic momenta perpendicularly to the acting base field B.sub.0. This accumulated excessive potential energy of the ensemble is transferred to the environment, and the efficiency of energy transfer determines the duration of the relaxation period.

(78) The precession movements represent a form of oscillations, and if the elements of the environment also oscillate with the same natural frequency as the precession frequency, the energy transfer becomes very efficient, by the same reason as NMR excitation becoming efficient when the external RF energy has the same period of oscillations. In case of relaxation, it is the oriented molecule in the collective magnetic field that plays the role of the external source and the molecules of the environment may or may not provide resonance absorbance, rapidly depleting the excessive energy of the ensemble. In free water, the own natural rotational frequency (“tumbling rate”) exceeds the typical Larmor precession frequencies by orders of magnitude. Thus, the energy transfer is ineffective, and the relaxation times can be 3-5 seconds long for both T.sub.1 and T.sub.2. Hydrocarbons represent heavier molecules than water with slower “tumbling rate” producing more efficient energy transfer and dissipation for both T.sub.1 and T.sub.2. Polymers are too slow, and once they acquire transverse magnetization, the passage of energy becomes inefficient due to the “tumbling rate” (own rotation frequency) of the entire molecules becoming much slower than the precession rate of the nuclei within them. Thus, T.sub.1 increases. Due to a very larger number of degrees of freedom, maintaining of precession phase coherence in large molecules requires a very large entropy constraint which is not a probable state. Thus, the magnetizations in these particles decohere rapidly even if the entire molecules do not re-orient rapidly along Z-axis, leading to the shortened T.sub.2 at longer T.sub.1. In ice, re-orientation of the magnetization vector in parallel to Z axis is hindered by the participation of the water molecules in close order crystal structure, leading to the “tumbling rates” much slower than the nuclear precession frequency and therefore high T.sub.1. An ice crystallite can be considered as a polymer-like structure in which maintaining magnetization phase coherence would require large entropy constrain and therefore decohering is energetically favorable, producing short T.sub.2 and long T.sub.1.

(79) Pore walls provide charged sites, hydrogen bonds, orbital acceptor sites and hydrophobic patches to the solution interactors. Water on the pore side complexing these active sites is immobilized one the wall and moving such a molecule to a different position requires activation energy comparable to the entire ensemble of its interactions. The next layer is partially immobilized due to increased intramolecular assistance effect of the directly immobilized water, acting similarly to chelators on the next layer. This effect subsides toward the center of the pore but is substantial over several molecular diameters. In case of hydrophobic molecules on hydrophobic surfaces, Van-der-Waals interaction between the immobilized first layer and the next layer is also strengthened by intramolecular assistance of the bound first layer. The effect similarly to the water case dwindles toward the center of the pore but can persist. The greater activation energy of self-diffusion in the boundary layers produces higher viscosities, lower rotational rates and more efficient T.sub.2 dissipation of magnetization energy in the near-wall regions, decreasing relaxation times for both water and hydrocarbons. Carr-Purcell-Meiboom-Gill (CPMG) pulse train sequence is a non-limiting example of the radiofrequency pulse sequences and it is the one most suitable for T.sub.2 measurements (discussed further below)

(80) T.sub.2 is an important parameter obtained from NMR measurements and it is a function of pore size distribution (surface relaxation), fluid type (diffusion relaxation) and fluid viscosity (bulk relaxation) as shown in equation (13). For the bulk fluid, there is no surface relaxation effect, so the only relaxations are bulk and diffusion:

(81) $\begin{array}{cc}\frac{1}{T_2}=\frac{1}{T_{2,\mathrm{bulk}}}+\frac{1}{T_{2,\mathrm{surface}}}+\frac{1}{T_{2,\mathrm{diffusion}}}=\frac{1}{T_{2,\mathrm{bulk}}}+\frac{\rho A_S}{V_{p}S}+\frac{1}{12}{\gamma }^2{G}^2{T}_E^2{D}^2& \left(13\right)\end{array}$

(82) The condition (13) is energy balance for a pore, since the relaxation time reciprocals indicate the rate of magnetization energy loss in a unit volume. T.sub.2, bulk—is the relaxation time in the bulk fluid; T.sub.2, surface—is the relaxation time on the pore walls; T.sub.2, diffusion—is the relaxation time, associated with the loss of T.sub.2 magnetization component by diffusion.

(83) Applying CPMG pulse sequences reduces the field inhomogeneity so the relaxation from diffusion is negligible so the last term in equation (13) is cancelled as shown in equation (14).

(84) 0$\begin{array}{cc}\frac{1}{T_2}=\frac{1}{T_{2,\mathrm{bulk}}}+\frac{1}{T_{2,\mathrm{surface}}}=\frac{1}{T_{2,\mathrm{bulk}}}+\frac{\rho A_S}{V_{p}S}& \left(14\right)\end{array}$

(85) Wherein: A.sub.s—is the pore surface; V.sub.pS—is the pore volume; ρ—is the pore wall relaxivity, the amount of magnetization energy scattering per a unit of pore surface.

(86) Examining (14) shows that the sum of bulk and pore surface relaxation losses characterizes magnetization decay in pores. If the T.sub.2 surface effect is significant, the fluid strongly interacts with the walls to ensure the formation of the high viscosity structured surface layer. By contrast, if there is no interaction with the wall, the tumbling rate of the molecules in the pores is close or identical to that in the bulk.

(87) FIGS. 6A-D illustrate the principles of diffusion NMR with a magnetic pulse gradient. As shown in FIG. 6A, the magnetization vector is already 90 degrees “flipped” by the RF pulse, producing a detectable signal in the transverse detector coil. The precession movement of the nuclei is synchronized in the resonance transition. The term “dephasing pulse-field gradient” refers to the gradient of the magnetic field generated by the gradient magnetic coils (FIG. 1), to be differentiated from the RF pulse generated by RF coils. The imposition of different B values in the analyzed volume by the magnetic gradient pulse leads to different precession frequencies and therefore decoheres the initial magnetized environment post 90 degree “flip”. No signal can be detected, since the global magnetization vector becomes zero. “Refocusing pulse field gradient” re-orients the nuclei that were in phase after the 90 degree “flip” and restores the signal in the detector, however, the diffusion of the species out of the volume that communicates with the detector coil diminishes the restored signal. Thus, the difference between signals before and after the sequence cycle provides the basis for estimating the diffusion coefficients. FIG. 6B illustrates the refocusing aspect. After a period of Δ/2 a 180° radiofrequency pulse inverts the dispersed magnetization such that after a period of Δ the magnetization is the negative of what it was following the gradient pulse. At this point, a second gradient pulse is applied to refocus the signal. The refocusing develops due to two contributions: one is the 180 degree “flip” counted vs. the initial 90 degree “flip” as typical in echo sequences and accomplished by an RF pulse (blue upper signals in FIG. 6B). The magnetization focusing by this mechanism was disclosed above. The second mechanism is the reversal of the magnetic pulse (the second pulse of the magnetic gradient), shown in red in FIG. 6B. The phase diagram in FIG. 6C illustrates the interaction between the 180-degree RF pulse and the second magnetic gradient pulse. The FIG. 6C clarifies that the individual magnetic momenta of the nuclei that lag behind the neighbors or overtake them in terms of precession movement return to the previous position after the 180 degree RF and the second magnetic gradient pulse (inverted vs. the first gradient pulse), restoring the coherence and allowing to observe the signal. The PGSE sequence leads to identification and diffusion coefficient measurement for the diverse species, including acidic protons, including, without limiting 2H and 3H substitutions (see below).

(88) In PGSE in the case of self-diffusion of molecules, the normalized signal amplitude E/E0 decays as a Gaussian curve with increasing magnetic gradient pulse amplitude G:

(89) $\begin{array}{cc}\frac{S\left(\mathrm{TE}\right)}{S_0}=\exp \left[-{\gamma }^2{G}^2{\delta }^2\left(\Delta -\frac{\delta }{3}\right)D\right]& \left(15\right)\end{array}$
where S.sub.0 is the signal intensity without the diffusion weighting, S (TE) is the signal with the magnetic field gradient, γ is the gyromagnetic ratio, G is the strength of the gradient pulse, δ is the duration of the pulse, Δ is the time between the two pulses, and finally, D is the diffusion coefficient.

(90) FIG. 6D shows the stacked experiment, where the strength of the residual signal S(TE) is plotted as a function of the magnetic field gradient G. The FIG. 6D illustrates how the resonance signal emerges at the resonance RF frequency fl and how the signal decreases in the serial measurements as a function of dephasing magnetic gradient pulse.

(91) In a preferred embodiment, the apparatus and software support partial flip angles with the more rapid accumulation of multiple data points to produce logarithmic plots. The plots are linear in the coordinates [ln S(TE)/S0=k G.sup.2] where the coefficient k includes the diffusion coefficient and the cycle pulse parameters. The rate of data point accumulation is important to increase the signal-to-noise ratio, which may be high in the NMR method of diffusion measurement due to high propagated error. In this embodiment, the partial flip angles range from 10 to 85 degrees without reaching the 90 degrees, which is achievable by softer RF pulses. The increased rate of data acquisition is achievable under these conditions due to shorter periods of magnetization energy accumulation and relaxation. In addition, partial flip angles alleviate the limitations on sensitivity that arise from the quantum-mechanical nature of the phenomenon. For quantum states separated by energy equivalent to radio frequencies, thermal energy from the environment causes the populations of the states to be close to equal. Since incoming radiation is equally likely to cause stimulated emission (a transition from the upper to the lower state) as absorption, the NMR effect depends on an excess of nuclei in the lower states. Several factors can reduce sensitivity, including increasing temperature, which evens out the population of states.

(92) Conversely, low-temperature NMR can sometimes yield better results than room-temperature NMR, providing the sample remains liquid. Saturation of the sample with energy applied at the resonant radiofrequency (complete flip angles, 90 degrees or above) is another sensitivity-reducing factor. This manifests in both constant wave (CW) and pulsed NMR. In the first case (CW) this happens by using too much continuous power that keeps the upper spin levels completely populated. In the second case (pulsed), each pulse (that is at least a 90° pulse) leaves the sample saturated, and four to five times the (longitudinal) relaxation time (5T1) must pass before the next pulse or pulse sequence can be applied. For single pulse experiments, shorter RF pulses that tip the magnetization by less than 90° can be used, which loses some intensity of the signal, but allows for shorter recycle delays. The optimum “flip” angle is called an Ernst angle. The relaxation times for the protons in free water are relatively short, but in the drilling conditions, nanoparticles and hydrocarbon-based aggregates contribute slowly relaxing components, and the use of partial angles can be advantageous.

(93) In another preferred embodiment, multiple diffusion coefficients are simultaneously measured in combination by pulsed NMR, with the device and software supportive of data generation and analysis. FIG. 7 presents Diffusion-Ordering Spectroscopy NMR (DOSY). The figure presents a 2D plot with the abscissa being the chemical shifts and the ordinate being the magnitude of the magnetic gradient (See equation 13). The chemical species are identified by the shifts, and the decay of the signal is a function of magnetic gradient pulse strength G is plotted for each chemical shift. As far as data processing of raw PFG-NMR spectra is concerned, the goal is to transform the N×M data matrix S into an N×R matrix (2D DOSY spectrum) as shown in FIGS. 8A and 8B. The horizontal axis of the DOSY map D is identical to that of S and encodes the chemical shift of the nucleus observed (generally 1H). The vertical dimension, however, encodes the diffusion coefficient D. In the ideal case of non-overlapping component lines and no chemical exchange, the 2D peaks align themselves along horizontal lines, each corresponding to one sample component (molecule). The horizontal cut along such a line should show that the component's ‘normal’ spectrum of chemical shifts. Vertical cuts show the diffusion peaks at positions defining the corresponding diffusion constants. The mapping S=>D is called the DOSY transformation. This transformation is, unfortunately, far from straightforward. Practical implementations of the procedure include mono and biexponential fitting, Maximum Entropy, and multivariate methods such as DECRA ‘Speedy Component Resolution’ (See M. Nilsson and Gareth A. Morris in Anal. Chem., 2008, 80, 3777-3782 incorporated herein by reference in entirety) as an improved variation of the Component Resolved (CORE) method (J. Phys. Chem, 1996, 100, 8180, incorporated herein by reference) providing a multivariate-based that shows an advantageous performance of the algorithm.

(94) In another preferred embodiment, the apparatus and software support the additional sequences suitable for the diffusion coefficient measurements: the Hahn stimulated echo (STE) with pulsed field gradients (FIG. 9). The sequence is analogous to PGSE but differs by providing two 90 degrees RF pulses in place of one 180-degree RF pulse in PGSE and by insertion of an additional “crusher” magnetic gradient pulse step. The LED (longitudinal encode decode) pulse sequence used in the NMR diffusion experiments is shown in FIG. 10. The radiofrequency pulses are shown as filled vertical rectangles with the flip angles denoted above each pulse. The magnetic field gradient pulses are shown as hatched rectangles, and the data acquisition is indicated with a vertically hatched triangle. Bipolar gradient longitudinal encode-decode pulse sequence (BPP-LED) is shown in FIG. 11. The BPPLED method cancels the adverse effects of eddy currents using two gradient pulses with identical areas but different polarities. Other embodiments comprise, respectively, the gradient compensated stimulated spin-echo pulse sequences (GCSTE), the double stimulated echo sequence (DSTE), the STE-INEPT pulse sequences for heteronuclear detected DOSY with coherence transfer, shuttle based fringe field 2D-DOSY, and the Alternating Pulsed Field Gradient Stimulated Echo Nuclear Magnetic Resonance (APGSTE) sequence (FIG. 12) without limiting. The APGSTE sequence is especially preferred for analyzing anisotropic diffusional systems, such as hydrocarbon-bearing formations with anisotropic porosity and tortuosity distributions. The sequence comprises focusing and de-coherence by the series of magnetic gradient pulses in 3 dimensions, explaining its unique suitability for more realistic modelling of diffusional coefficient tensors. All sequences lead to processing and data collection/transform by the DOSY methodology, with the Tanner and Stejskal equation modified for each specific sequence (See Jan Hrabe, Gurjinder Kaur, and David N. Guilfoyle, “Principles and limitations of NMR diffusion measurements” in J Med Phys., 2007 January-March; 32(1): 34-42; Davy Sinnaeve, “The Stejskal-Tanner Equation Generalized for Any Gradient Shape—An Overview of Most Pulse Sequences Measuring Free Diffusion” in Concepts in Magnetic Resonance Part A, 2012, Vol. 40A(2) 39-65, incorporated herein by reference in entirety).

(95) CPMG is a nuclear magnetic resonance (NMR) measurement, referring to the cycle of radiofrequency pulses designed by Carr, Purcell, Meiboom and Gill to produce pulse echoes and counteract dephasing due to magnetic field inhomogeneities (FIG. 13). In the CPMG sequence, an initial radiofrequency pulse is applied long enough to tip the protons into a plane perpendicular to the static magnetic field (the 90° pulse). Initially the protons precess in unison, producing a large signal in the antenna, but then quickly dephase due to the inhomogeneities. Another pulse is applied, long enough to reverse their direction of precession (the 180° pulse) and causing them to come back in phase again after a short time. Being in phase, they produce another strong signal called an echo. They quickly dephase again but can be rephased by another 180° pulse. Rephasing is repeated many times, while measuring the magnitude of each echo. This magnitude decreases with time due to molecular relaxation mechanisms surface, bulk and diffusion. One measurement typically may comprise many hundreds of echoes, while the time between each echo (the echo spacing) is of the order of 1 ms or less. In this regime, the diffusional component of relaxation is suppressed (See: Carr H Y and Purcell E M: Effects of Diffusion on Free Precession in Nuclear Magnetic Resonance Experiments, Physical Review 94, no. 3 (1954): 630-638. Meiboom S and Gill D: Modified Spin-Echo Method for Measuring Nuclear Relaxation Times. The Review of Scientific Instruments 29, no. 8 (1958): 688-691; incorporated herein by reference in entirety).

(96) Having considered the physical basis of the NMR methodologies, pertinent to the inventive method, the most preferred embodiments are presented in more detail. In a preferred embodiment, the method of the present disclosure is intended to be a rapid bridging laboratory procedure, establishing correlation with the benchmark Amott-Harvey approach and purely in-situ downhole measurements. The method of the present disclosure comprises saturation of the sample by oil, which may not be feasible in a borehole. The depth of drilling is in the range 0.5-5 km, while the borehole diameter is 0.12-1 m. However, the rapid and precise NMR procedure of the present disclosure can be used in a field laboratory to recalibrate for multiple secondary NMR methods which are compatible with the in-situ downhole applications. Such secondary methods offer the benefits of scale, precise positional address, measurement in depth from the borehole edge, measurement in dynamics by flooding at variable pressures, measurements in dynamics by including surfactants, simultaneous measurement of multiple signals, including NMR, conductance and sonic sources. The log data are massive, mutually supportive, amenable to machine learning analysis and sharing with multiple commercial packages. But they need validation by a reliable benchmark method or its faster and more convenient NMR proxy.

(97) At its laboratory stage, the method is implemented as a kit, preferably with equipment, reagents, instructions and software, designed to complete one measurement within 20 minutes of sample delivery. The samples are delivered from a recorded vertical section of the well. The samples upon arrival are rinsed in brine, broken into small fragments 3-5 mm in diameter and loaded into a high-pressure NMR tube under a layer of brine. The suitable tubes are represented, without limitation, by: Extreme Series Valved NMR Sample Tubes from NORELL® (FIG. 14), High Pressure NMR tubes by Daedalus Innovations, 5 mm Heavy Wall Precision Pressure/Vacuum Valve NMR Sample Tube 7″ by Wilmad Lab Glass. Other components of the kit include the protective screens while operating high pressure NMR tubes (up to 10 atm), buffers and brine, standardized oil, supply of pressurized nitrogen to force brine and oil in the sample at the respective stages of the test, gloves and goggles. In operation, the test tube is loaded by the rock fragments under the layer of brine, closed and pressurized. The brine invades the pores. The bulk brine T.sub.2 is measured. The test tube is extracted from the device, opened, decanted and the rock sample is rinsed by oil. The oil layer tops the fragments, and the test tube is pressurized again until water becomes irreducible (practically—up to 10 atm, below the 13 atm limit for the test tubes). The T.sub.2 values are measured for oil in the bulk, oil in the pores and irreducible water in the pores. Next, the test-tubes are opened, the oil is decanted by a thin vacuum-connected pipette and the brine is returned to expel oil under the pressure. The T.sub.2 values are measured for the bulk brine, brine in the pores after expelling oil, and the residual non-reducible oil. The combined results enable computing the wettability index of the present method. The wettability index computed for several samples is compared with the secondary metrics that are suitable for downhole use establishing a correlation with the inventive method. The secondary metrics are described further and the NMR-based information required to compute them is derived while processing the samples by the inventive calibration method.

(98) The secondary in-situ methods rely on submersible equipment, compatible with downhole regimes. The Measuring While Drilling (MWD) alternatives to sample extraction, delivery to a laboratory and application of the results to the process upon completion of the laboratory study are advantageous (See Prammer, M. G., Drack, E., Goodman, G. et al. The Magnetic-Resonance While-Drilling Tool: Theory and Operation. SPE Res Eval & Eng, 2001, 4 (4): 270-275. SPE-72495-PA; Appel, M., Radcliffe, N.J., Aadireddy, P. et al. Nuclear Magnetic Resonance While Drilling in the U.K. Southern North Sea. Presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Tex., USA, 2002, 29 September-2 October. SPE-77395-PA; Morley, J., Heidler, R., Horkowitz, J. et al. Field Testing of a New Nuclear Magnetic Resonance Logging-While-Drilling Tool. Presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Tex., USA, 2002, 29 September-2 October. SPE-77477-MS; Poitzsch, M., Scheibal, J. R., Hashem, M. et al. Applications of a New Magnetic Resonance Logging-While-Drilling Tool in a Gulf of Mexico Deepwater Development Project. Presented at the SPWLA 43rd Annual Logging Symposium, Oiso, Japan, 2002, 2-5 June. SPWLA-2002-EEE; Heidler, R., Morriss, C., and Hoshun, R. 2003. Design and Implementation of a New Magnetic Resonance Tool for the While Drilling Environment. Presented at the SPWLA 44th Annual Logging Symposium, Galveston, Tex., USA, 2002, 22-25 June. SPWLA-2003-BBB; Borghi, M., Porrera, F., Lyne, A. et al. Magnetic Resonance While Drilling Streamlines Reservoir Evaluation. Presented at the SPWLA 46th Annual Logging Symposium, New Orleans, 2005, 26-29 June. Paper 2005-HHH).

(99) In one embodiment, the method relies on the commercially available drilling assemblies incorporating NMR apparatus among other sensors for providing the real-time multifactorial feedback. The non-limiting examples are ProVision Plus (magnetic resonance while drilling apparatus by Schlumberger). The apparatus and the software acquires the T.sub.2 data derived from pore size and fluid properties within several seconds, the T.sub.2 data can be further processed to quantify bound- and free-fluid volume and capillary-bound water. MR signal decay data helps ascertain permeability, producible porosity, and irreducible water saturation as well as capillary pressure curves, hydrocarbon identification, and facies analysis. A real-time permeability log enables predicting production rates to optimize completion and stimulation programs.

(100) Analogously, Halliburton Sperry Drilling apparatus and software offers logging-while-drilling (LWD) nuclear magnetic resonance (NMR) source-less porosity solutions to help gain insight into the key petrophysical properties of the reservoir through a mineralogy-independent porosity assessment. The apparatus (MRIL®-WD™ Magnetic Resonance Imaging Logging-While-Drilling Sensor) determine the total porosity of a reservoir, movable fluid volume, capillary bound fluid volume, and micro-porosity—essential information to allow a user to determine which fluids produce hydrocarbons upon stimulation. By calculating a qualitative estimate of permeability, the user identifies which reservoir intervals have greater flows, and can better target the optimal spots for increased production.

(101) Other providers of the small-diameter borehole-adapted NMR apparatuses comprise Mount Sopris Instruments, Baker Hughes Incorporated tools, Dart, Javelin, and Javelin Wireline tools by VISTA-CLARA INC without limitation. These and the additional MRWD (magnetic resonance while drilling) designs are disclosed in U.S. Ser. No. 10/197,698, U.S. Ser. No. 10/401,313, U.S. Ser. No. 10/473,600, U.S. Ser. No. 10/295,627, U.S. Ser. No. 10/338,267, US20190033483, U.S. Ser. No. 10/191,178 incorporated herein by reference in entirety.

(102) In a preferred embodiment, the NMR device can function both as a submerged device and as the main analytical tool in a field laboratory. It is provided with a software fitting relaxation, chemical shifts, signal intensity, diffusivity data extracted at different time-points and lengths of sequences to the geometry, composition and wettability of the pores. In a preferred embodiment, the software provides decision support pointing to the optimal vertical position in the borehole, suitable as a perforation node (branching point) for the secondary channels originating from the primary cased vertical well, where the inventive method is applied.

(103) In one preferred non-limiting embodiment of a secondary wettability in-situ metric, the software quantitates the presence of hydrocarbon in the formation as a function of water flooding. If hydrocarbon does not compete with water for the affinity to the pore surface, the decline in the intensity of the signals resonating at hydrocarbon chemical shift frequencies is sharp after flooding. The decline decreases if there is competition and the pore surface is amphiphilic. The decline is minimal if hydrocarbon is absorbed by the pore surfaces tightly and outcompetes water for the wall affinity sites. These profiles can be calibrated by the inventive method which in turn, correlates strongly to the benchmark test. The quantitative expression of the metric is [change of hydrocarbon signal]/[initial hydrocarbon signal×flooding pressure].

(104) In another preferred non-limiting embodiment, the secondary metric is the ratio of: [irreducible water]/[porosity×tortuosity/pore diameter]. The expression reflects the ratio of the irreducible water and inner pore surface. If the interaction with the pore wall material is strong (water wetted), the number of molecular layers retained per a unit of pore surface is high and can be correlated to Amott-Avery test via the inventive bridging NMR test. All required components are identifiable by several variations each (See: Chang D, Vinegar H J, Morriss C, Straley C. Effective porosity, producible fluid and permeability in carbonates from NMR logging. In SPWLA 35th Annual Logging Symposium 1994 Jan. 1. Society of Petrophysicists and Well-Log Analysts; Gao H, Li H. Determination of movable fluid percentage and movable fluid porosity in ultra-low permeability sandstone using nuclear magnetic resonance (NMR) technique. Journal of Petroleum Science and Engineering. 2015 Sep. 1; 133:258-67; Anferova S, Anferov V, Rata D G, Blumich B, Arnold J, Clauser C, Blumler P, Raich H. A mobile NMR device for measurements of porosity and pore size distributions of drilled core samples. Concepts in Magnetic Resonance Part B: Magnetic Resonance Engineering: An Educational Journal. 2004 October; 23(1):26-32; Prammer M G. NMR pore size distributions and permeability at the well site. In SPE annual technical conference and exhibition 1994 Jan. 1. Society of Petroleum Engineers; Strange J H, Webber J B. Spatially resolved pore size distributions by NMR. Measurement Science and Technology. 1997 May; 8(5):555; Pape H, Tillich J E, Holz M. Pore geometry of sandstone derived from pulsed field gradient NMR. Journal of Applied Geophysics. 2006 Mar. 1; 58(3):232-52; Zecca M, Vogt S J, Connolly P R, May E F, Johns M L. NMR measurements of tortuosity in partially saturated porous media. Transport in Porous Media. 2018 Nov. 1; 125(2):271-88; Tourell M C, Pop I A, Brown L J, Brown R C, Pileio G. Singlet-assisted diffusion-NMR (SAD-NMR): redefining the limits when measuring tortuosity in porous media. Physical Chemistry Chemical Physics. 2018; 20(20):13705-13; Xiao L, Mao Z Q, Jin Y. Calculation of irreducible water saturation (S wirr) from NMR logs in tight gas sands. Applied Magnetic Resonance. 2012 Feb. 1; 42(1):113-25; Xuan D, Fu S, Xie R. Study on NMR logging bulk volume of the irreducible water model. Nuclear Electronics and Detection Technology. 2007; 27(3):578-82; Fleury M, Deflandre F. Quantitative evaluation of porous media wettability using NMR relaxometry. Magnetic resonance imaging. 2003 Apr. 1; 21(3-4):385-7; incorporated herein by reference in entirety). Most typically, porosities are estimated based on signal intensity of the fluid expected to be in the pores, tortuosity is estimated by restricted diffusion, pore size distribution by T.sub.2 distribution, and irreducible water in the presence of oil by the combination of T.sub.1 and T.sub.2 of the surface components.

(105) In a further preferred non-limiting embodiment, the secondary metric is the ratio of hydrocarbon and water in the larger pores to the content in the smaller pores. The rationale for this measurement is the unequal distribution between the wetted surface and the bulk of pore. In case of smaller pores, the surface to volume ratio is greater and the more wetting component may develop a bulk concentration gradient between the pore categories, following the surface affinity. The gradient of signal with the given chemical shift is corroborated by greater T2 and restricted diffusion shifts between the pores of different size.

(106) In a still further preferred secondary measurement, the NMR logging is accompanied by conductivity logging. In a more water-wetting environment, the conductivity is higher at the same brine-to-oil saturation ratio. The rationale for this trend is spreading of the water phase, maximized in a wetting environment at the same opposing content of oil. In a non-wetting situation, the injected brine forms isolated drops and the conductance of hydrocarbon is lower by orders of magnitude. At a certain extent of formation flooding by the brine, the continuous phase forms even in a non-wetting environment, but at lower saturations, the differences can be dramatic. Measuring conductance in depth before and after flooding and having the drilling chippings available for the calibration study by the inventive method allows to align the vertical profile of in-depth conductance pre- and post-flooding and the “true” wettability data. Typically, the amount of drilling mud intended for cooling the drilling assembly is several cubic meters and it fills the region of drilling operation only, with the rest of the well emerging empty. After covering a significant stretch of depth, a steel casing pipe is inserted and the annulus between the pipe and the well wall is fortified by concrete. The measurements should precede this strengthening step. Due to the limited volume of mud that follows the drilling assembly, this volume of mud represents the composition of the rocks in the proximity to the current drilling region and therefore can be delivered to the surface and aligned with NMR and conductance logging data. The samples delivered to the field laboratory for processing by the inventive method are labeled by the vertical position of the drilling assembly and can be attributed to the depth with a minimal error (mostly arising from the perfect mixing regime and the presence of the material from the other depth levels).

(107) In another preferred embodiment, the secondary metrics are the wettability estimates of the commercially available software, validated by the field laboratory employing the inventive method. The non-limiting examples of the commercially available log-interpreting software are: Core analysis software CYDAR™ (CYDAREX), PerGeos package, ECLIPSE 100 or 300/500 reservoir simulation software, ECLIPSE Blackoil, RSTPro (Reservoir Saturation Tool) and WFL (Water Flow Log) by Schlumberger, GEMS by Computer Modelling Group, CMG Software Solutions by Computer Modelling Group. The packages are trained on dozens and hundreds of formation cores and field conditions, however, cannot anticipate all specific situations. The wettability and permeability are directly linked while also independently affect the productivity and yield of the reservoir. If the local conditions fall outside of the training method and its ability to extrapolate, the results are likely to skew the economic model, with significant cost consequences. There is a value in an independent inexpensive express validation of the predicted results using a portable field NMR device, accompanied by a rapid measurement kit. Re-testing a statistically viable (8-10) number of vertical sections by the inventive method validates the entire log interpretation and assures that the given reservoir falls in the range of predictability and extrapolation by the commercial software and the latter can be further used for the local situation. If the result is negative, the log data are imported into an alternative package and validation is repeated, until a correct commercial analytical software is identified.

(108) In a further preferred embodiment, customized software is written for exploratory wells located in the same geographic region. The non-limiting examples of such broad regions are the Permian Basin, the Orinoco Oil Belt, the Guyana offshore region, the TX-LA-MS Salt Basin, The Western Gulf Basin, The Ft. Worth Basin, The Palo Duro Basin, The Anadarko Basin. Bound by a common geological history, the formations within such regions are more uniform as compared to variation between different global regions. While the outliers of petrophysical properties are possible, they are less likely and the economic models are more precise if a customized package replaces the commercial software. In this embodiment, the customized package is written by relating the metrics emulating log measurements (the secondary metrics) to a combination of laboratory calibrating metrics. Such a combination comprises the estimate of wettability by the inventive NMR method, measurement of permeability as the at least two levels of core brine flooding, measurement of conductivity at the at least two levels of core brine flooding, and measurement of tortuosity and porosity by the benchmarks. The primary (benchmark) and the secondary (log-imitating) measurements are performed on a library of the formation cores originating in the geographic region of interest. The first step in this methodology is reaching the collection of sandstones or carbonates cores. These categories of porous rocks are analyzed separately. Commercial providers manufacture and sell the cylindrical rock cores representing hydrocarbon reservoirs: Kocurek Industries INC., Vinci Technologies, Rockman, Bureau Veritas Commodities Canada Ltd. without limiting.

(109) Core Research Center was established to coordinate these efforts and preserves valuable rock cores for scientists and educators from government, industry, and academia. Other core depositories include Alabama Geological Survey State Oil and Gas Board Core Warehouse, Alabama Geological Survey State Oil and Gas Board Core Warehouse, Alaska Geologic Materials Center, Alaska Geologic Materials Center Online Inventory, Arizona Geological Survey (AZGS) 1993 Core Repository Report, Arkansas Geological Survey Norman F. Williams Well Sample Library, California Well Sample Repository, Connecticut Geological Survey Bedrock Core Repository, Delaware Geological Survey Outer Continental Shelf Core and Sample Repository, Florida Geological Survey Core and Cuttings Repository, Illinois State Geological Survey Geological Samples Library, Search Illinois Geological Samples Library, Iowa Geological Survey Oakdale Rock Library and Research Facility, Kansas Geological Survey Kansas Core Library, Kansas Geological Survey Kansas Rotary-cutting samples, Kentucky Geological Survey Well Sample and Core Library, Well Sample and Core Library Database Search, LACCORE National Lacustrine Core Repository, Louisiana Geological Survey Resource Center Core Repository, Maine Geological Survey Core Repository and Exploration Records, Michigan Geological Repository for Research and Education, Minnesota Department of Natural Resources Division of Lands and Minerals Drill Core Library, Mississippi Department of Environmental Quality, Environmental Geology Division, Office of Geology, Core and Sample Library Missouri Department of Natural Resources McCracken Core Library and Research Center Nebraska Conservation and Survey Division Geological Sample Repository, Nevada Bureau of Mines and Geology Great Basin Science Sample and Records Library, New Mexico Subsurface Data and Core Libraries, North Carolina Geological Survey Coastal Plain Office Core Repository, North Dakota Geological Survey Wilson M. Laird Core and Sample Library, Ohio Department of Natural Resources Geological Survey Core and Sample Repository, Oklahoma Geological Survey Core and Well Cutting Research Facility, Pennsylvania Department of Conservation and Natural Resources (DCNR), South Carolina Geological Survey Core Repository, South Dakota Geological Survey Core and Cuttings Repository, Core and Cuttings Repository Database, Texas Bureau of Economic Geology Core Research Facilities, Integrated Core and Log Database, Utah Geological Survey Core Research Center, Wisconsin Geological & Natural History Survey Research Collections and Education Center (Core Repository).

(110) The USGS maintains the most diverse public-access core collections in the USA. A variety of core sub-collections are available in the repository, including those from oil shale development; Eniwetok Atoll; Cajon Pass, Calif.; Yellowstone Park; and off-shore wells. In addition, CRC curates collections of cuttings (rock chips) brought to the surface during drilling operations. The core and cuttings collection is also accompanied by a large collection of thin sections, which are used to examine microscopic details of the rocks. Images of the thin sections and photographs of some cores are available for viewing and download. Files containing chemical and physical analyses, core descriptions, stratigraphic charts, and various other analyses performed by previous users of the collection can also be downloaded. The CRC houses about 2 million feet of core in the general collection of petroleum exploration and development holes as well as in specialized collections. These cores come from 33 states and about 95 percent were donated by petroleum and mining companies, State geological surveys, other Federal agencies, and universities; about 5 percent are special scientific cores drilled by the USGS. In addition, the CRC maintains over 25,000 thin sections taken from cataloged cores and cuttings. Cuttings from over 52,000 wells in 27 States are also housed at the repository. This unique collection of cuttings represents around 240 million feet of drilling at a replacement cost of over $80 billion. Analogous infrastructure exists outside of the USA, without limitation: Kochi Core Center Kochi University, Japan and the University of Bremen, Germany. The samples are available via an application process and released by a decision of a research board.

(111) The cylindrical cores are sealed in a high-pressure testing cell and are subjected to permeability test using a fluid with known viscosity or with a viscosity profile emulating natural hydrocarbon (another sample of heavy oil, cracking residue, tar). Alternatively, gas permeability is measured. Prior to pressing through the core, the fluid (or gas) is equilibrated with water (or water vapor) and passes a pre-filter eliminating potential sediments (dust). The core is wetted by water to the extent matching the non-reducible level or to a fixed level of water content. The permeability test is repeated at 2 water saturation levels and with several oil (gas) models. After completion of the realistic permeability test, the wetted cores with the model hydrocarbons entrapped in the pores together with water are subjected to NMR, resistivity and sonic characterization. The NMR examination includes measuring overall signal strength at different chemical shifts, measuring of relaxation times for all components at different orientations of the sample, measuring water restricted diffusion coefficients, measuring diffusion anisotropy, computing porosity, pore size distribution and tortuosity based on NMR data. The core next undergoes resistivity studies at the initial and varied water contents, with the several directions of the current, to measure the anisotropy of formation factor, resistivity index and the empirical coefficients n and min Archie's Law form. The core also undergoes acoustic studies at several water contents and directions. After completing these tests, the core is repeatedly extracted by hot diesel oil (to prevent asphaltene deposition), the diesel oil is displaced and dissolved by heptane, and the core is dried. The dried core is subjected by a detailed porometric study and “true” tortuosity determination by xenon NMR or microscopy (See Wang R, Pavlin T, Rosen M S, Mair R W, Cory D G, Walsworth R L. Xenon NMR measurements of permeability and tortuosity in reservoir rocks. Magnetic resonance imaging. 2005 Feb. 1; 23(2):329-31; Albers B, Wilmanski K. Acoustics of two-component porous materials with anisotropic tortuosity. Continuum Mechanics and Thermodynamics. 2012 Nov. 1; 24(4-6):403-16; Wang R, Mair R W, Rosen M S, Cory D G, Walsworth R L. Simultaneous measurement of rock permeability and effective porosity using laser-polarized noble gas NMR. Physical Review E. 2004 Aug. 31; 70(2):026312; incorporated herein by reference in entirety). At some point, the core also undergoes the benchmark study by the present wettability-prediction method.

(112) The procedure is repeated for multiple samples, separately for carbonates and sandstones. The number of samples included in the training set for each group is not less than 50, preferably 75, even more preferably >100. For each sample, multiple compositions are analyzed (water contents and oil models), thus the training set may include 1000-2000 data rows, relating the high-throughput logging parameters to the observed permeabilities (wettability, mechanical strengths). For cost-efficiency, the training sets are expected to be maximally diversified to ensure that they represent the entire variety of hydrocarbon cores within a basin (for example, the samples extracted in Arabian Basin).

(113) At the next step, the parameters measured by high-throughput logging tools such as NMR, resistivity and acoustic probes are fit to the true values of wettability permeability, porosity and tortuosity obtained in careful laboratory experiments. Multiple fitting methods are possible, with multiple convergences and residual minimization criteria (the Least Square Method is one non-limiting embodiment). In one non-limiting embodiment, the following expression is fitted to the experimental wettability W measured by the inventive method:
A.sub.1×[τ.sub.NMR.sup.B1]×[R.sup.B2]×[Φ.sub.NMR.sup.B3]×[(τ.sub.NMRZ).sup.B4/(τ.sub.NMRXY).sup.B4]×S.sub.w.sup.B5×S.sub.wir.sup.B6×(ΔH/H).sup.B7×[D].sup.B8=W  (16)
Where: W—is dimensionless wettability index in the range (−1, 1), A.sub.1—is the empirical proportionality factor, [τ.sub.NMR.sup.B1]—is the diffusional tortuosity determined by NMR and B1 is the respective exponent of the fitting model to be determined in the training process. [R.sup.B2]—is the relative resistivity at the given extent of brine flooding (related to the resistivity of pure brine) and B2 is the respective exponent of the fitting model to be determined in the training process. [Φ.sub.NMR.sup.B3]—is the overall porosity determined by NMR and the respective fitting coefficient B3. [(τ.sub.NMRZ).sup.B4/(τ.sub.NMRXY).sup.B4]—is the ratio of diffusional tortuosity in the direction Z to one measured in the plane XY and the respective fitting coefficient B6. S.sub.w.sup.B5—is the water saturation fraction with the respective fitting factor. S.sub.wir.sup.B6—is the irreducible water content with the respective fitting factor. (ΔH/H).sup.B7—is the fraction of hydrocarbon expelled from the sample at the given S.sub.w, with the respective fitting factor. (D).sup.B8—is the weight-averaged diameter of the pores with the respective fitting factor.

(114) All definitions above apply to water flooding the innermost 0-5 mm of the borehole wall, the closest to the drilling in progress.

(115) The formula (16) effectively combines the secondary metrics defined earlier. It accounts for the dynamics of hydrocarbon expulsion per a unit of saturating brine pressure and volume, the changes in resistivity in response to the pressure and volume of the injected brine, the thickness of surface water layer measured by combining [S.sub.wir.sup.B6], [D.sup.B8], [Φ.sub.NMR.sup.B3], [τ.sub.NMR.sup.B1] and [(τ.sub.NMRZ).sup.B4/(τ.sub.NMRXY).sup.B4] as well as asymmetries in water and hydrocarbon distribution based on the pore size. The 9-coefficient metric is fitted to the inventive results and provides a reliable local estimate of wettability, which needs field laboratory validation less frequently than the commercial package, but still needs it occasionally.

(116) Having generally described this disclosure, a further understanding can be obtained by reference to certain specific examples which are provided herein for purposes of illustration only and are not intended to be limiting unless otherwise specified.

EXAMPLE 1: ROCK SAMPLES

(117) Two Indiana limestone rock samples named 1H, 2H and two Berea sandstone samples named 1S, 2S were cut form a 12 inches length core. Berea samples were fired at 900° C. for 8 hours to eliminate clay effects such as swelling and then they were used in the study. The samples porosity and permeability were determined using the AP-608 Automated Permeameter-Porosimeter. Table 1 presents the properties of the rock samples. Rock mineral composition was identified using the PAN-alytical Empyrean Multi-Function XRD as shown in FIG. 15.

(118) TABLE-US-00001 TABLE 1 Rock sample properties Sample Diameter (cm) Length (cm) φ (%) K (md) 1H 3.797 4.631 18.858 281.3108 2H 3.804 4.907 18.539 274.2349 1S 3.788 5.194 22.048 189.831 2S 3.789 5.172 21.613 157.4979

EXAMPLE 2: FLUIDS

(119) 8% NaCl brine and Uthmaniyah Crude oil are the fluids used in this study. Brine was prepared by adding NaCl salt to deionized water and mixing for 30 minutes. The crude oil was filtered to remove any solid particles and impurities. The fluid density and viscosity were measured at different temperatures with hydrometer and Oswald viscometer and a temperature-controlled oil bath as presented in FIG. 16, 17 and, respectively asphaltene content of the oil was determined to be 5.045 g/100 ml using ASTM D2007-80 standard procedure.

EXAMPLE 3: NMR

(120) Oxford Instruments' Geospec2-75, operating at 2.2 MHz was used for NMR measurements. The experiments were conducted at room temperatures and pressure. CPMG (Carr-Purcell-Meiboom-Gill) pulse sequence was used for T2 measurements with the signal to noise ratio above 100 and tau time of 0.05 ms.

EXAMPLE 4: FLOW CHART OF THE METHOD AND OVERVIEW OF THE MODEL

(121) FIG. 18 shows the detailed procedure followed, which is evaluating rock wettability from T2 NMR, and validate NMR results with Amott-Harvey wettability index. The wetting phase contacts or coats the pore space surface exhibiting surface relaxation effect which means it shows lower value of T2 compared to its bulk T2 while the non-wetting phase is not affected by surface properties and tends to behave like a bulk fluid. Based on this fact, a wettability index from T2 NMR measurements is provided in Equations 17-19:

(122) $\begin{array}{cc}{\mathrm{WI}}_w=\frac{T_{2,\mathrm{WB}}-T_{2,\mathrm{Sor}}}{T_{2,\mathrm{WB}}}& \left(17\right)\\ {\mathrm{WI}}_o=\frac{T_{2,OB}-T_{2,\mathrm{Swr}}}{T_{2,OB}}& \left(18\right)\\ I_{\mathrm{NMR}}={\mathrm{WI}}_w-{\mathrm{WI}}_o& \left(19\right)\end{array}$
Wherein: WI.sub.w, and WI.sub.o are the water, and oil sub-indices, respectively. T.sub.2,WB, T.sub.2,OB, T.sub.2,Swr, and T.sub.2,Sor are the T.sub.2 values at predominant peak of bulk water, bulk oil, irreducible water saturation, and residual oil saturation status. I.sub.NMR is the wettability index from NMR.

(123) The model classifies wettability into three types as shown in

(124) Table 2 below.

(125) TABLE-US-00002 TABLE 2 Developed Wettability Index criteria. I.sub.NMR Wettability Type Below −0.4 Oil-wet −0.4 to 0.4 Intermediate or mixed wet Above 0.4 Water wet

EXAMPLE 5: RELAXATION BEHAVIOR OF BRINE AND OIL IN 1H and 2H SAMPLES (INDIANA LIMESTONE)

(126) First, T.sub.2 distribution for the bulk fluid was constructed as shown in FIG. 19. There is a clear separation between the oil and water T.sub.2 peak in FIG. 19 due to the significant contrast in their viscosity such that the oil is almost 40 times more viscous than the brine as we see in FIG. 17. From FIG. 19, the T.sub.2 of brine is 2.78 seconds which is the standard value for water while the oil predominant peak is at T.sub.2=0.0864 seconds and the smaller peak is at 0.005572 seconds. The reason that oil has two peaks is attributed to its composition variety from light to heavy components.

(127) The T.sub.2 distribution of sample 1H fully saturated with brine is shown in FIG. 20 (a). Since brine is the only phase inside the pore space, it exhibits surface relaxation and the predominant peak T.sub.2 has been shifted to the left (0.373 s) compared to the bulk fluid T.sub.2 represented by the black dotted line (2.78 s). Furthermore, for fully water-saturated sample, T.sub.2 predicts the pore size distribution as two connected pore systems (macro and micro). When oil is injected until S.sub.wr, first—the larger pores were filled by oil and then smaller pores reached the irreducible water saturation. In FIG. 20 (b), the predominant peak T.sub.2 was shifted to the exact bulk oil T.sub.2 represented by the red dotted line (0.0864 s) which indicates that oil is not the wetting phase and does not show any surface relaxation effect. Once the rock was aged for one week, the wettability starts to change in favor of oil-wet conditions and this is clearly indicated by the shift of the predominant peak T.sub.2 to 0.0599 s compared to 0.0864 s before aging as shown in FIG. 20 (c). However, the shift is not that significant, which indicates that the wettability is closer to intermediate-wet and more likely water-wet and higher aging time is needed to convert the wettability to oil-wet. Next, water was injected until S.sub.or and FIG. 20 (d) confirms that the wettability is intermediate and more likely water-wet since the predominant peak T.sub.2 was shifted to the right 0.93 s compared to the fully water-saturated T.sub.2 (0.373 s) which means that the surface relaxation effect on water is reduced due to oil starting also to contact some of the pore surface but it is more likely water wet. This conclusion is confirmed by comparing the T.sub.2 after imbibition (0.93 s) to the bulk brine T.sub.2 (2.78) and the fully water-saturated T.sub.2 (0.373 s). T.sub.2 after brine imbibition is still closer to T.sub.2 of the fully water-saturated case which is under surface relaxation effect than the bulk brine T.sub.2 which is free of surface relaxation effect.

(128) The same behavior was noticed in sample 2H. However, it is more intermediate-wet compared to sample 1H. The conclusion is revealed in FIG. 7 by the shift to the left in T2 after aging and more shift to the right in T2 after imbibition compared to sample 1H. The predominant peak T.sub.2 when fully brine saturated is 0.373 s which is the same for sample 1H. When oil was injected until S.sub.wr, the predominant peak T.sub.2 was shifted to 0.072 s which is almost the same as the bulk oil T2 represented by the red dotted line (0.0864 s) which indicates that oil is not the wetting phase. After aging the sample for one week, the wettability was restored closer to the oil-wet conditions and this is indicated by the shift of the predominant peak T2 to 0.0416 s compared to the bulk oil T2 (0.0864 s) as shown in FIG. 21. In addition, the predominant peak T.sub.2 after imbibition was shifted to 1.12 s due to the reduction of surface effect on the water phase but it is still intermediate wet since the surface relaxation effect on water is still existing so the T.sub.2 is not the same as that of the bulk brine.

(129) Table 3 summarizes the predominant peak T.sub.2 values after aging and after imbibition for Indiana limestone samples. The developed wettability index was applied to evaluate wettability quantitatively. Detailed example of the calculation for sample 1H is provided below.

(130) TABLE-US-00003 TABLE 3 Summary of the predominant peak T2 values at different saturations for carbonate samples. Sample T.sub.2 at S.sub.wr T.sub.2 at S.sub.or 1H 0.0599 0.93 2H 0.0416 1.12

(131) ${\mathrm{WI}}_w=\frac{T_{2,\mathrm{WB}}-T_{2,\mathrm{Sor}}}{T_{2,\mathrm{WB}}}=\frac{2.78-0.93}{2.78}=0.6655$${\mathrm{WI}}_o=\frac{T_{2,OB}-T_{2,\mathrm{Swr}}}{T_{2,OB}}=\frac{0.0864-0.0599}{0.0864}=0.3067$$I_{\mathrm{NMR}}={\mathrm{WI}}_w-{\mathrm{WI}}_o=0.6655-0.3067=+0.3588$

(132) The example of the computation illustrates the pairing of data: water bulk (T.sub.2, WB) is compared to the signal when water is imbibed or injected (T.sub.2, Sor). Imbibition is a fast process as compared to complete saturation, and this makes the method rapid. Likewise, oil bulk (T.sub.2, OB) is compared to the signal when oil is imbibed or injected (T.sub.2, Swr). This is also a fast process, not requiring careful monitoring of complete displacement. The water term shows a greater range of changes between the bulk and the injected state (2.78 and 0.93 sec) as compared to the respective changes for the oil term (0.0864 and 0.0599 sec), even if the oil term was enhanced by thermal aging. The greater spread between the bulk and injected state for water points to water-wet pore surface. The narrow spread for oil points to oil being in the bulk-like state in the pores, that is non-interacting with the pore surfaces.

(133) Table 4 shows the wettability Index for Indiana limestone samples from the NMR-based model and Amott-Harvey benchmark test. Amott-Harvey wettability index showed a value of +0.32 which indicates an intermediate wettability. The wettability index was determined for 1H as +0.3588 and +0.0786 for 2H which also indicates intermediate wettability condition. There is excellent agreement between the developed model and Amott-Harvey index.

(134) TABLE-US-00004 TABLE 4 Wettability Index for carbonate samples from our model and Amott-Harvey model for carbonate samples. Sample I.sub.NMR I.sub.Amott-Harvey 1H +0.3588 +0.32 2H +0.07860

EXAMPLE 6: RELAXATION BEHAVIOR OF BRINE AND OIL IN S and 2S SAMPLES (BEREA SANDSTONE)

(135) FIG. 22 (a) presents the T.sub.2 distribution of sample 1S fully saturated with brine. The predominant peak T.sub.2 has been shifted to the left (0.149 s) compared to the bulk fluid T.sub.2 represented by the black dotted line (2.78 s) which indicates the surface relaxation effect. When oil is injected until S.sub.wr, FIG. 22 (b), the predominant peak T.sub.2 was shifted to the to 0.072 s which is almost the same as the bulk oil T.sub.2 represented by the red dotted line (0.0864 s) which indicates that oil is not the wetting phase so it does not shows any surface relaxation effect. In addition, the T.sub.2 distribution at S.sub.wr is almost the same as the bulk oil distribution as shown in FIG. 22 (b) which indicates that the sample is strongly water-wet since oil behaves exactly like the bulk fluid although it is inside a pore space. Water was injected until S.sub.or and FIG. 22 (c) confirms that the rock is strongly water-wet since the predominant peak T.sub.2 was shifted to the exact value of T.sub.2 when fully brine saturated (0.149 s) and the T.sub.2 distribution for the two cases is identical. Sample 2S shows the exact behavior of S quantitatively and qualitatively as shown in FIG. 23.

(136) Like the carbonate samples, the sandstone samples show the same trends. The injected water is strongly shifted (0.149 s) vs. bulk (2.78 s). The injected oil does not much differ from the bulk (0.072 s vs. 0.0864 s). The overall index is dominated by the polar water term.

(137) Table 5 summarizes the predominant peak T.sub.2 values after primary drainage and after imbibition for Berea sandstone samples. The developed wettability index was applied to evaluate wettability quantitatively.

(138) TABLE-US-00005 TABLE 5 Summary of the predominant peak T.sub.2 values at different saturations for sandstone samples. Sample T.sub.2 at S.sub.wr T.sub.2 at S.sub.or 1S 0.072 0.149 2S 0.072 0.149

(139) Table 6 shows the wettability Index for Berea sandstone samples. Amott-Harvey wettability index showed a value of +0.79 which indicates a strong water-wet condition. The model determines the wettability index for 1S and 2S as +0.7797 that also indicates a strong water-wet condition. There is excellent agreement between the developed model and Amott-Harvey model.

(140) TABLE-US-00006 TABLE 6 Wettability Index for sandstone samples from present disclosure and Amott-Harvey model for sandstone samples. Sample I.sub.NMR I.sub.Amott-Harvey 1S +0.7797 +0.79 2S +0.7797