Methods and systems are provided that combine NMR and IR spectroscopy measurements on a rock sample to determine data representing at least one property of the rock sample. In one embodiment, cuttings can be split into first and second lots. Results of an NMR measurement performed on the first lot of cuttings without cleaning can be analyzed to determine pore volume of the cuttings. Results of an IR spectroscopy measurement performed on the second lot of cuttings after solvent cleaning can be analyzed to determine matrix density of the cuttings. Porosity can be determined from the pore volume and matrix density of the cuttings. In another embodiment, combined NMR and IR spectroscopy measurements can be performed on an unprepared rock sample (without solvent cleaning) to characterize properties of kerogen in the rock sample and porosity. In another aspect, a method is provided that employs multi-nucleic NMR measurements to determine porosity.

Methods and systems are provided that combine NMR and IR spectroscopy measurements on a rock sample to determine data representing at least one property of the rock sample. In one embodiment, cuttings can be split into first and second lots. Results of an NMR measurement performed on the first lot of cuttings without cleaning can be analyzed to determine pore volume of the cuttings. Results of an IR spectroscopy measurement performed on the second lot of cuttings after solvent cleaning can be analyzed to determine matrix density of the cuttings. Porosity can be determined from the pore volume and matrix density of the cuttings. In another embodiment, combined NMR and IR spectroscopy measurements can be performed on an unprepared rock sample (without solvent cleaning) to characterize properties of kerogen in the rock sample and porosity. In another aspect, a method is provided that employs multi-nucleic NMR measurements to determine porosity.

A subterranean earth formation is evaluated by running a process with a logging tool residing in a borehole in the earth formation to collect shallow measurements of a property of the formation and deep measurements of the property of the formation. An inversion is performed on the shallow measurements to produce a group of possible formation models that fit the shallow measurements. A machine-learning algorithm is applied to estimate the shallow formation structure, using the group of possible formation models that fit the shallow measurements, to produce a shallow formation structure. An inversion is performed on the deep measurements to produce a group of possible formation models that fit the deep measurements. The shallow formation structure is expanded using the group of possible formation models that fit the deep measurements to produce a deep formation structure.

A subterranean earth formation is evaluated by running a process with a logging tool residing in a borehole in the earth formation to collect shallow measurements of a property of the formation and deep measurements of the property of the formation. An inversion is performed on the shallow measurements to produce a group of possible formation models that fit the shallow measurements. A machine-learning algorithm is applied to estimate the shallow formation structure, using the group of possible formation models that fit the shallow measurements, to produce a shallow formation structure. An inversion is performed on the deep measurements to produce a group of possible formation models that fit the deep measurements. The shallow formation structure is expanded using the group of possible formation models that fit the deep measurements to produce a deep formation structure.

A method and system for estimating parameters of pipes. The method may comprise disposing an electromagnetic (EM) logging tool into a pipe string, creating a log from a first set of one or more measurements, and creating a synthetic model of one or more nested pipes based at least in part on a well plan. The method may further comprise adding a modeled pipe to the synthetic model, estimating one or more parameters of the modeled pipe through model calibration to form a calibrated model, and performing an inversion with the calibrated model to estimate one or more pipe parameters of the pipe string. The system may comprise an electromagnetic logging tool that may comprise a transmitter, wherein the transmitter is a first coil and is operable to transmit an electromagnetic field, and a receiver, wherein the receiver is a second coil and is operable to measure the electromagnetic field.

A method and system for estimating parameters of pipes. The method may comprise disposing an electromagnetic (EM) logging tool into a pipe string, creating a log from a first set of one or more measurements, and creating a synthetic model of one or more nested pipes based at least in part on a well plan. The method may further comprise adding a modeled pipe to the synthetic model, estimating one or more parameters of the modeled pipe through model calibration to form a calibrated model, and performing an inversion with the calibrated model to estimate one or more pipe parameters of the pipe string. The system may comprise an electromagnetic logging tool that may comprise a transmitter, wherein the transmitter is a first coil and is operable to transmit an electromagnetic field, and a receiver, wherein the receiver is a second coil and is operable to measure the electromagnetic field.

Systems and methods for imaging properties of subterranean formations (136) in a wellbore (106) include a formation sensor (120, 200) for collecting currents (304A, 304B) injected into the subterranean formations (139) and a formation imaging unit (118). The formation imaging unit (118) includes a current management unit for collecting data from the currents injected into the subterranean formations (136) and a formation data unit (116) for determining at least one formation parameter from the collected data. The formation imaging unit (118) also includes an inversion unit for determining at least one formation property by inverting the at least one formation parameter. The inversion unit is suitable for generating an inverted standoff image and an inverted permittivity image for comparison with a composite image of the formation imaging unit.

Systems and methods for imaging properties of subterranean formations (136) in a wellbore (106) include a formation sensor (120, 200) for collecting currents (304A, 304B) injected into the subterranean formations (139) and a formation imaging unit (118). The formation imaging unit (118) includes a current management unit for collecting data from the currents injected into the subterranean formations (136) and a formation data unit (116) for determining at least one formation parameter from the collected data. The formation imaging unit (118) also includes an inversion unit for determining at least one formation property by inverting the at least one formation parameter. The inversion unit is suitable for generating an inverted standoff image and an inverted permittivity image for comparison with a composite image of the formation imaging unit.

A method for evaluating saturation of a kerogen bearing subterranean formation includes obtaining conductivity and permittivity values of the formation and providing an effective medium model relating the conductivity and the permittivity to a water filled porosity of the formation and an effective aspect ratio of graphitic kerogen particulate in the formation. The obtained conductivity and the permittivity values are input into the model which is in turn processed to compute the water filled porosity. The method may further optionally include evaluating the water filled porosity to estimate a hydrocarbon producibility of the formation.

A method for evaluating saturation of a kerogen bearing subterranean formation includes obtaining conductivity and permittivity values of the formation and providing an effective medium model relating the conductivity and the permittivity to a water filled porosity of the formation and an effective aspect ratio of graphitic kerogen particulate in the formation. The obtained conductivity and the permittivity values are input into the model which is in turn processed to compute the water filled porosity. The method may further optionally include evaluating the water filled porosity to estimate a hydrocarbon producibility of the formation.