Saudi Arabian Oil Company

Weihua Wang

Yunsheng Li

Maan A Hawi

Otto Meza Camargo

Kaiming Xia

Yufeng Cui

Si-Hai Zhang

Hasan Algheryafi

Ibrahim A Makrami

Systems and methods for generating synthetic borehole image logs include logging rate of penetration (ROP) data, resistivity data, and gamma ray data while drilling a borehole in a subsurface formation to generate logged data. The generating includes determining an effective dip angle of the subsurface formation along the borehole and generating a depth shift table based on the effective dip angle and a well deviation angle, the well deviation angle being between the borehole and a vertical reference. Datasets are generated based on the ROP data, resistivity data, and gamma ray data, the generated datasets having higher sampling rates than the logged data. Synthetic borehole images are generated based on the generated datasets and the depth shift table, and the synthetic borehole images are oriented with respect to a reference point of the borehole.

Generating synthetic borehole image logs

A system and method for performing a reservoir evaluation are disclosed. The method includes obtaining a nuclear magnetic resonance (NMR) dataset for a plurality of samples and obtaining an NMR log for a wellbore penetrating a reservoir. The method further includes determining a rock facies description for each sample, determining an NMR transverse relaxation time (NMR T) distribution from the NMR dataset, and determining a set of parameters characterizing the NMR Tdistribution based on one or more predetermined parameters. The method still further includes identifying a plurality of NMR facies based, at least in part, on the set of parameters for each sample, determining a transformation that maps a subset of rock facies to a subset of the plurality of NMR facies, and performing the reservoir evaluation based, at least in part, on applying the transformation to the NMR log.

Parameterization of nuclear magnetic resonance transverse relaxation time distribution

A method includes gathering data about the well and the deep and tight sandstone reservoir, evaluating a diagenetic rock typing and a flow index of the reservoir using the data, and determining a first set of perforation locations based on the diagenetic rock typing and the flow index. The method also includes calibrating in-situ stresses based on the data and determining a breakdown pressure envelope and optimal perforation directions using the in-situ stresses, maximum horizontal stress direction, formation mechanical properties, and well trajectory. The method further includes narrowing the first set of perforation locations to a second set of perforation locations based on the breakdown pressure envelope, comparing the breakdown pressure envelope of the second set of perforation locations to a maximum downhole pressure to determine a perforation method, and performing a fracturing operation on the well using the second set of perforation locations, the perforation method, and the optimal perforation directions.

Method to identify perforation locations for fracturing deep and tight sandstone reservoir

Systems and methods include a computer-implemented method for creating artificial real-time gamma ray (GR) images for well placement. Real-time azimuthal density data is determined from drilling of a well. An azimuthal density data set is generated using the real-time azimuthal density data. The azimuthal density data set is generated with a greater sampling rate than a real-time sampling rate of the real-time azimuthal density data. An azimuthal density curve depth match is performed using the azimuthal density data set. Performing the azimuthal density curve depth match includes creating a depth shift match table. A high-resolution sector near-bit gamma ray (GR) image is generated using the azimuthal density curve depth match and the depth shift match table. The high-resolution sector near-bit GR image is oriented to a top of a wellbore for the well.

Creation of near bit gamma ray image from a gamma ray curve

A computer-implemented method that enables lithofacies guided core description using unsupervised machine learning is described herein. The method includes obtaining well log curves for a wells in a zone. The method also includes predicting lithofacies for the wells using a machine learning model. The machine learning model is trained with input data comprising additional well log curves and well cores. The method includes grouping the wells based on the predicted lithofacies, and updating core descriptions of the wells based on the grouped wells.

Lithofacies guided core description using unsupervised machine learning

Systems and methods include a computer-implemented method: Total clay, effective porosity (PHIE) values, and gas volume are determined for a tight gas sandstone reservoir characterization using petrophysical evaluation results. Regions of the tight gas sandstone reservoir are characterized, including performing diagenetic rock typing for the regions using the total clay and PHIE values, where the diagenetic rock typing reflects porosity/permeability and clay content change. Sweet spots are determined based on the diagenetic rock typing and gas volume variation. Ranked sweet spots are determined by indexing and ranking the sweet spots by category. Optimized infill drilling locations and target zones are determined, and well placements in the tight gas sandstone reservoir are assisted using the diagenetic rock typing and the ranked sweet spots.

Log based diagenetic rock typing and sweet spot identification for tight gas sandstone reservoirs

A method is disclosed that includes: obtaining a seismic data volume for a subterranean region of interest; transforming, by a computer processor using a non-stationary series analysis, the seismic data volume into a seismic spectral volume where the seismic spectral volume includes a seismic spectrum for each of a plurality of voxels; and determining a seismic attribute volume composed of a seismic attribute for each of the plurality of voxels. The seismic attribute for a voxel of the plurality of voxels is based, at least in part, on an integral of the seismic spectrum for the voxel over a range bounded by a first frequency and a second frequency. The method further includes determining a presence of hydrocarbon in the subterranean region of interest based on the seismic attribute volume. A system for performing the method is also disclosed and described.

System and method of hydrocarbon detection using nonlinear model frequency slope

A horizontal or deviated core sample is received from a wellbore. A presence of geologic indicators within the horizontal or deviated core sample is determined. The horizontal or deviated core sample is rotated to a position based on the presence and orientation of the geologic indicators. A top of the horizontal or deviated core sample is marked after the core has been rotated.

Orienting geologic core samples

Systems, methods, and computer readable media for the determination of hydrogen sulfide (HS) concentration and distribution in carbonate reservoirs using a mechanical earth model. Hydrogen sulfide (H2S) concentration in a carbonate reservoir n may be measured and correlated with horizontal maximum stresses of stress ratios determined using mechanical earth model for a strike-slip fault regime. The hydrogen sulfide (H2S) concentration at different depths in the carbonate reservoir may be determined using the correlation.

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Dhahran, Saudi Arabia

Weihua Wang