A portion of an anisotropy formation through which a wellbore is formed can be identified. An estimate of an elastic anisotropy parameter for the portion can be adjusted based on a first quality control analysis using the elastic anisotropy parameter for the portion. The first signal representing the elastic anisotropy parameter for the portion. The estimate of the elastic anisotropy parameter for the portion can be adjusted based on a second quality control analysis using estimates for the elastic anisotropy parameters for two or more portions of the anisotropy formation.

A method, including: obtaining, with a computer, an initial geophysical model; modeling, with a computer, a forward wavefield based on the initial geophysical model with wave equations including a second order z-derivative in a rotated coordinate system that accounts for a tilted transverse isotropic (TTI) medium; modeling, with a computer, an adjoint wavefield with adjoint wave equations including a second order z-derivative in a rotated coordinate system that accounts for a tilted transverse isotropic (TTI) medium, wherein the wave equations and the adjoint wave equations include relaxation terms accounting for anelasticity of earth in an update of a primary variable and an evolution relationship for the relaxation terms; and obtaining, with a computer, a gradient of a cost function based on a combination of a model of the forward wavefield and a model of the adjoint wavefield.

A method for characterizing a sand-pack or gravel-pack in a subsurface formation includes inducing a pressure change to induce tube waves in fluid in a well drilled through the subsurface formation. At a location proximate to a wellhead at least one of pressure and a time derivative of pressure in the well is measured for a selected length of time. At least one of a physical parameter and a change in the physical parameter with respect to time, of the sand-pack or gravel-pack, is determined using the measured pressure and/or the time derivative of pressure.

The shape and size of a borehole may be characterized downhole, using measurements of the borehole shape in conjunction with a catalog of shapes against which the measured shape is matched. A unique identifier for the measured borehole shape, and optionally a size parameter, may be transmitted to a surface facility, generally saving bandwidth compared with the transmission of the raw measured borehole-shape data. Alternatively or additionally, downhole measurements may be adjusted based on the measured shape. Additional methods, apparatus, and systems are disclosed.

A method for estimating a fluid pressure required to stimulate a subsurface formation includes using seismic signals detected by a plurality of seismic sensors disposed proximate the subsurface formation. Spatial positions and times of origin (“hypocenters”) of each of a plurality of microseismic events induced by pumping fluid into the subsurface formation are estimated. Magnitudes and directions of principal stresses are estimated from the hypocenters and from amplitude and phase of the detected seismic signals for each of the microseismic events. Shear and normal stresses of induced fractures are from the estimated principal stresses. A fluid pressure required to cause formation failure on each fracture is estimated using the estimated shear and normal stresses.

A method of predicting pore pressure based on seismic data can include obtaining seismic inversion data based in part on seismic data collected from a formation. The method also includes calculating a pore-pressure transform, wherein the pore-pressure transform comprises parameters derived using measured pore pressure data, upscaled sonic logs, and density logs, wherein the pore-pressure transform comprises an objective function to reduce unphysical variations in predicted pore pressure corresponding to depth. Additionally, the method can include adjusting the pore-pressure transform for sampling bias caused by pore pressure measurements being restricted to a plurality of lithologies by accounting for a difference between upscaled seismic velocities and average sonic velocities within each of the lithologies. Furthermore, the method can include generating pore pressure prediction values based on the pore-pressure transform for the lithologies and the seismic inversion data, and modifying a seismic model based on the generated pore pressure prediction values.

A method may include obtaining core image data regarding a geological region of interest. The method may further include obtaining well log data regarding the geological region of interest from one or more wells. The method may further include determining a sliding window that corresponds to a predetermined window size. The method may further include determining various quantitative image attributes using the core image data, the well log data, and the sliding window. The quantitative image attributes may be determined in a continuous manner by moving the sliding window along the core image data. The method may further include generating predicted rock data for the geological region of interest using the quantitative image attributes, a machine-learning algorithm, and a machine-learning model.

A method for fluid identification (water, oil, gas or CO.sub.2) and saturation estimation in subsurface rock formations using the prestack inverted Seismic by calculating the target fluid saturation (S.sub.fl) (114) in a reservoir given the magnitude obtained from the P- to S-wave velocity ratio (Vp/Vs) (103), and acoustic impedance (AI) (102) extracted from the seismic data inversion, comprising the following steps: a) obtaining wireline log data within a zone of interest in a nearby well (101) and determining the suitable cementation and mineralogy factors by calibrating the background water-bearing sand trend with the reference 0% (or 0 fraction) S.sub.fl curve onto the acoustic impedance-Vp/Vs ratio plane (110), b) calibrating S.sub.fl computed from the acoustic impedance-Vp/Vs ratio curves with S.sub.fl obtained from a conventional method by iterating P-wave velocity (Vp.sub.f) and density (ρ.sub.fl) of the target fluid (111), c) obtaining inverted seismic data in the form of Acoustic Impedance (AI) (102) and Vp/Vs ratio (103) cubes, and d) calculating the target fluid saturation using the calibrated rock physics model inputting the obtained parameters from model calibration (cementation factor, mineralogy factor, density and P-wave velocity of the target fluid) along with inverted Vp/Vs ratio and acoustic impedance cubes data (113), resulting in a S.sub.fl cube (114).

A method and apparatus for machine learning for use with automated seismic interpretation include: obtaining input data; extracting patches from a pre-extraction dataset based on the input data; transforming data of a pre-transformation dataset based on the input data and geologic domain knowledge and/or geophysical domain knowledge; and generating augmented data from the extracted patches and the transformed data. A method and apparatus for machine learning for use with automated seismic interpretation include: a data input module configured to obtain input data; a patch extraction module configured to extract patches from a pre-extraction dataset that is based on the input data; a data transformation module configured to transform data from a pre-transformation dataset that is based on the input data and geologic domain knowledge and/or geophysical domain knowledge; and a data augmentation module configured to augment data from the extracted patches and the transformed data.

A method including obtaining, for a subterranean region, a set of sedimentary pathways, a sediment attribute map, and an area of interest. From these inputs, a sedimentary fairway, and a sedimentary fairway attribute based on the location of the origin point of each member of the set of sedimentary pathways, and a spatial location of the terminal point of each member of the set of sedimentary pathways are determined. Further, the method includes dividing the sedimentary fairway into one or more sedimentary pathway domains and a sediment attribute profile for each sedimentary pathway domain based on a trajectory of each sedimentary pathway, and determining an intersection of the trajectory of each sedimentary pathway with one or more boundaries of the area of interest. The method also includes determining a sedimentary attribute at the entry points, and a sedimentary attribute at the exit points of the set of sedimentary pathways with the area of interest, and a change in the sedimentary attribute between the entry and exit points.