Schlumberger Technology Corporation

Chevron U.s.a. Inc.

Neil Francis Hurley

Tuanfeng Zhang

Weishu Zhao

Mustafa A Al Ibrahim

Ridvan Akkurt

Andriy Gelman

David McCormick

Guangping Xu

Lili Xu

Mirna Slim

Shu Zhang

Saturation-height functions in oil and gas reservoirs are determined using methods that include quantifying the microporosity of the subterranean formation; determining the distribution of facies and microporosity as a function of depth; and calculating the saturation-height function for a given formation.

Methods for determining a saturation-height function in oil and gas reservoirs

Methods of generating structural models of highly deviated or horizontal wells may be generated from the measurement of true stratigraphic thickness in three dimensions (TST3D). In one aspect, methods may include generating a structural model from one or more deviation surveys of a horizontal well, one or more single channel log measurements, and a three-dimensional reference surface.

Stratigraphic and structural interpretation of deviated and horizontal wellbores

The present disclosure introduces methods and apparatus for acquiring a borehole image corresponding to a sidewall surface of a borehole that penetrates a subterranean formation, wherein the subterranean formation comprises structural elements and a varying geophysical characteristic. The borehole image comprises structure corresponding to the structural elements, texture corresponding to the varying geophysical characteristic, and coverage gaps () in which the structure and texture are missing. Trends corresponding to the structure are extracted from the borehole image. Missing structure within the gaps () is reconstructed based on the extracted trends. Missing texture within the gaps is simulated based on the borehole image and the reconstructed structure. A fullbore image is constructed based on the borehole image, the reconstructed structure within the gaps, and the simulated texture within the gaps.

Borehole image gap filling

Methods for characterizing a geological formation, the methods include retrieving measured data provided by a measuring tool along one or more logged borehole length for a borehole, another borehole or both in order to produce a borehole imaging log. Selecting depth-defined intervals of the borehole imaging log as training images for inputting in a multi-point geostatistical model. Determining pattern based simulations for each training image using a pixel-based template of the multi-point geostatistical model so as to obtain training image patterns. Using the pattern based simulation of each training image to assign to each of the training image a corresponding training image pattern. Constructing from the training image patterns one or more fullbore image log of a borehole wall of the borehole. Repeat the second to fourth steps through the one or more logged borehole length in order to construct fullbore images from successive, adjacent training images.

Method for characterizing a geological formation traversed by a borehole

A method is disclosed for determining wettability in a subsurface reservoir. Embodiments of the method utilize image analysis techniques for determining wettability indicator values. Wettability indicator values may be determined based on a hydrocarbon wet fraction and a water wet fraction of pore linings, which may both be determined by image analysis of pore walls lined with hydrocarbons using images of sections obtained from core samples. Further details and advantages of various embodiments of the method are described in more detail herein.

Method to determine wettability of rock samples using image analysis

Methods for upscaling digital rock modeling data are described. Core-plug samples for pore-scale modeling are chosen using whole-core mini-permeability grids and conventional CT scans. Pore models or pore-network models are used for flow modeling. Borehole-scale models use MPS (Multi-Point Statistics) to combine mini-permeability grids and conventional CTscans of whole core with electrical borehole images to create 3D numerical pseudocores for each RRT (Reservoir Rock Type). Effective SCAL properties computed from various MPS borehole-scale realizations or models are used to populate interwell-scale models for each RRT. Effective properties computed from flow simulations for interwell volumes are used to populate full-field scale models. At the full-field scale, outcrop analogs, sequence stratigraphy, forward stratigraphic models, diagenetic models, and basin-scale models are combined using MPS to improve flow simulations. At every stage, REVs (representative element volumes) are computed to be certain rock heterogeneities have been captured.

Multiscale digital rock modeling for reservoir simulation

This subject disclosure describes methods to build and/or enhance 3D digital models of porous media by combining high- and low-resolution data to capture large and small pores in single models. High-resolution data includes laser scanning fluorescence microscopy (LSFM), nano computed tomography (CT) scans, and focused ion beam-scanning electron microscopy (FIB-SEM). Low-resolution data includes conventional CT scans, micro computed tomography scans, and synchrotron computed tomography scans.

Methods to build 3D digital models of porous media using a combination of high- and low-resolution data and multi-point statistics

This disclosed subject matter is generally related to methods for characterizing two-dimensional (2D) and three-dimensional (3D) samples to determine pore-body and pore-throat size distributions and capillary pressure curves in porous media using petrographic image analysis. Input includes high-resolution petrographic images and laboratory-derived porosity measurements. Output includes: (1) pore-body and pore-throat size distributions, and (2) simulated capillary pressure curves for both pore bodies and pore throats.

Petrographic image analysis for determining capillary pressure in porous media

Methods and systems for creating a numerical pseudocore model, comprising: a) obtaining logging data from a reservoir having depth-defined intervals of the reservoir, and processing the logging data into interpretable borehole image data having unidentified borehole image data; b) examining one of the interpretable borehole image data, other processed logging data or both to generate the unidentified borehole image data, processing the generated unidentified borehole image data into the interpretable borehole image data to generate warped fullbore image data; c) collecting one of a core from the reservoir, the logging data or both and generating a digital core data from one of the collected core, the logging data or both such that generated digital core data represents features of one or more depth-defined interval of the reservoir; and d) processing generated digital core data, interpretable borehole image data or the logging data to generate realizations of the numerical pseudocore model.

Method to generate numerical pseudocores using borehole images, digital rock samples, and multi-point statistics

Methods for characterizing a sample of porous media using a measuring device along with a multipoint statistical (MPS) model. Retrieving a set of reflected measured data provided by the measuring device of a surface of the sample in order to produce a sample imaging log, wherein the retrieved set of measured data is communicated to a processor. Selecting depth-defined surface portions of the sample from the sample imaging log as a training image for inputting in the MPS model. Determining pattern based simulations from the training image using one of a pixel-based template which is applied to the training image. Constructing from the pattern based simulations a complete-sampling image log of surface portions of the sample. Repeat the above steps in order to construct three dimensional (3D) sample images from stacked successive pattern based simulations so as to construct at least one 3D model of the sample.

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Boston, MA, United States of America

Neil Francis Hurley