Chevron U.s.a. Inc.

Ashley D Harris

Tao Sun

Maisha Lara Amaru

Morgan David Sullivan

Fabien J Laugier

Brett M Hern

Brian J Willis

Lewis Li

Martin Perlmutter

Michael James Pyrcz

Sebastien B Strebelle

Martin A Perlmutter

A computational stratigraphy model may be run for M mini-steps to simulate changes in a subsurface representation across M mini-steps (from 0-th subsurface representation to M-th subsurface representation), with a mini-step corresponding to a mini-time duration. The subsurface representation after individual steps may be characterized by a set of computational stratigraphy model variables. Some or all of the computational stratigraphy model variables from running of the computational stratigraphy model may be provided as input to a machine learning model. The machine learning model may predict changes to the subsurface representation over a step corresponding to a time duration longer than the mini-time duration and output a predicted subsurface representation. The subsurface representation may be updated based on the predicted subsurface representation outputted by the machine learning model. Running of the computational stratigraphy model and usage of the machine learning model may be iterated until the end of the simulation.

System and method for accelerated computation of subsurface representations

A method is described for analysis of subsurface data including the use of physics-based modeling and experimental design that allows calculation of probabilities of physical subsurface properties. The method may include calculations of key controlling parameters. The method may include using multiple dimension scaling. The method may be executed by a computer system.

System and method for analysis of subsurface data

Well information may define subsurface configuration of different wells. Marker information defining marker positions within the wells may be obtained. A dissimilarity matrix for the wells may generated, with the element values of the dissimilarity matrix determined based on comparison of corresponding subsurface configuration of the wells. A gated dissimilarity matrix may be generated from the dissimilarity matrix based on the marker positions within the wells. The elements values of the gated dissimilarity matrix corresponding to one set of marker positions and not corresponding to the other set of marker positions may be changed. Correlation between the wells may be determined based on the gated dissimilarity matrix such that correlation exists between a marker position in one well and a marker position in another well.

Comparison of wells using a dissimilarity matrix

A subsurface representation may define simulated subsurface configuration of a simulated subsurface region. The simulated subsurface region may include simulated wells, and the simulated subsurface configuration may define simulated correlation between the simulated wells. Subsurface configuration of wells may be compared with the simulated subsurface configuration to generate similarity maps for the wells. Simulated wells may be matched to the wells based on the similarity maps and the arrangement of the wells. Correlation between the wells may be determined based on the simulated correlation between the matched simulated wells.

Correlation of multiple wells using subsurface representation

Correlation matrices may be used to simultaneously correlate multiple wells. A correlation matrix may be generated for individual pairs of multiple wells. The values of elements of the correlation matrices may be determined based on matching between segments of the multiple wells and segments of one or more computational stratigraphic models. An N-dimensional space including an axis for individual wells may be generated. Directed walk may be performed within the N-dimensional space to generate paths representing scenarios of correlations for segments of the multiple wells.

Correlation matrix for simultaneously correlating multiple wells

A new gridding method is disclosed for forward stratigraphic modeling that allows for syndepositional and/or postdepositional fault movement. The new gridding algorithm may represent both the lateral move of structure block, and provide efficiency that is comparable to the structured grid for forward stratigraphy model accessing previous deposited sediments stored in the grid. Embodiments of the disclosed methods allow for structural moves by performing a set of simple operations on the grid. The operations are generally simple, and do not change the overall topology of the grid. Therefore the operation can be easily repeated and the overall topological structure of the grid remains largely unchanged for simple access by the forward stratigraphic model. Further details and advantages of various embodiments of the method are described in more herein.

Method of stratigraphic modeling of faults

Disclosed is a method and system for identifying simulated basin results and associated input parameter values for simulation of geographic basins by a stratigraphic forward model simulation program that are most likely to represent the actual basin by treating inputs and outputs of the stratigraphic forward model simulation program in a unified manner. An embodiment may calculate probability distributions for input parameters and validation data, and calculate likelihoods of simulated basins as a combination of the combination of the probabilities of the input parameters used to create the simulated basin and of the combination of the probabilities simulation validation results of the simulated basin. An embodiment may then select most likely simulation model result basins based on the results having a higher calculated likelihood. The most likely simulated basins may be used for analysis of exploration and/or production decisions without the need for additional, expensive testing on the actual basin.

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Houston, TX, United States of America

Ashley D Harris