Chevron U.s.a. Inc.

The Texas A&m University System

Kellen Leigh Gunderson

Reynaldo Cardona

Shuxing Cheng

Zhao Zhang

Ziyu Jiang

Chris Anthony Guzofski

Zhangyang Wang

Systems and methods are disclosed for identifying subsurface features as a function of position in a subsurface volume of interest. Exemplary implementations may include obtaining target subsurface data; obtaining a conditioned subsurface feature model; applying the conditioned subsurface feature model to the target subsurface data, which may include generating convoluted target subsurface data by convoluting the target subsurface data; generating target subsurface feature map layers by applying filters to the convoluted target subsurface data; detecting potential target subsurface features in the target subsurface feature map layers; masking the target subsurface features; and estimating target subsurface feature data by linking the masked subsurface features to the target subsurface feature data.

Systems and methods for identifying subsurface features as a function of position in a subsurface volume of interest

Systems, devices, and methods are disclosed for identifying subsurface features as a function of position in a subsurface volume of interest. A computer-implemented method may include obtaining training subsurface data and corresponding training subsurface feature data; obtaining an initial subsurface feature model including tiers of elements; generating a conditioned subsurface feature model by training the initial subsurface feature model using the training subsurface data and the corresponding training subsurface feature data; and storing the conditioned subsurface feature model in the non-transient electronic storage.

Systems and methods for identifying subsurface features as functions of feature positions in a subsurface volume of interest

A method is described for assessing subsurface structure uncertainty based on at least one subsurface horizon. The method calculates seismic continuity attributes to determine a mappability of the subsurface horizon(s); determines horizontal uncertainty for each fault in vertical uncertainty for each horizon; generates probabilistic scenarios for a subsurface geometry for at least one conceptual model; and generates a map of geological model uncertainty based on the probabilistic scenarios. In some embodiments, the probabilistic scenarios are stochastic simulations. In some embodiments, generating a map of geological model uncertainty is based on information entropy. The method may be executed by a computer system.

System and method for subsurface structural interpretation

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Houston, TX, United States of America

Kellen Leigh Gunderson