Chevron U.s.a. Inc.

Baosheng Liang

Chao Yan

Wei Wei

Gregory Arthur Winslow

Chaoshun Hu

Wei Wang

Amos Sunghyun Kim

Min Li

Wade H Williams

Lauren N DeVoe

Soong Hay Tam

Alicia Sanchez

Clinton C Terry

Sam Kidd

Shahzad Ali Khan

Han Young Park

A method for evaluating a chemical treatment at a subsurface for improved well performance may include obtaining information about a post-reaction fluid that results from a fluid flowing through a testing vessel for a period of time, where the testing vessel comprises a plurality of materials, where the plurality of materials is designed to be representative of the subsurface, and where the plurality of materials comprises rock and proppant. The method may also include performing, using the information, a compatibility test on the post-reaction fluid and the plurality of materials after the period of time. The method may further include evaluating, after performing the compatibility test, an effect of the post-reaction fluid on the plurality of materials.

Optimizing chemical treatment at the subsurface for improved well performance

Characteristics of a reservoir may be used to generate multiple models of the reservoir with hydraulic fractures. Simulated configurations of the hydraulic fractures in the models may be used to select one or more of the models as representative model(s) for the reservoir. The representative model(s) may be used in development of the reservoir. Hydraulic fracturing may increase productivity at shale and tight rock reservoir by creating more effective flow paths to production.

Selection of simulation models using fracture information

A method is described for predicting permeability including receiving a 3-D earth model including a volume of interest; generating 2-D property images; receiving 2-D fracture images; training a physics-guided neural network using the 2-D fracture images; and predicting permeability using the physics-guided neural network applied to the 2-D property images. The method is executed by a computer system.

Artificial learning fracture system and method for predicting permeability of hydrocarbon reservoirs

A method for evaluating and optimizing scale management at a subsurface for improved well performance may include performing multiple first tests, where each first test combines a first fluid with a second fluid, wherein the first fluid comprises a concentration of a scale inhibitor and a chemistry of additional fluid components. The method may also include identifying an optimal mixture of the first fluid among the first tests, where the optimal mixture comprises a minimum concentration of the scale inhibitor that reduces scale deposition. The method may further include performing a second test that combines the first fluid with the scale inhibitor, the second fluid, and rock. The method may also include evaluating a concentration of the scale inhibitor in aqueous phase after a period of time after initiating the second test. The method may further include identifying a target fluid for use in a field operation at the subsurface.

Optimizing scale management at the subsurface for improved well performance

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Houston, TX, United States of America

Baosheng Liang