-
公开(公告)号：US20220057368A1
公开(公告)日：2022-02-24
申请号：US17602242
申请日：2020-04-07
Applicant: Chevron U.S.A. Inc. , Triad National Security, LLC
Inventor： Marcel REMILLIEUX , Esteban ROUGIER , Zhou LEI , Timothy James ULRICH , Harvey Edwin GOODMAN
Abstract: Structure information for a substance within a volume may be obtained. The structure information may characterize structural non-linearity of the substance within the volume. A structure model for the substance within the volume may be generated based on the structure information and/or other information. The structure model may simulate one or more characteristics of the substance within the volume. Presentation of information on the characteristic(s) of the substance within the volume may be effectuated based on the structure model and/or other information.
-
公开(公告)号：US11248159B2
公开(公告)日：2022-02-15
申请号：US16259247
申请日：2019-01-28
Applicant: Chevron U.S.A. Inc.
Inventor： Robert George Shong , Varadarajan Dwarakanath , Gregory A. Winslow , Sophany Thach
IPC: C09K8/584 , C07C59/305 , E21B43/16 , C09K8/588
Abstract: The present disclosure relates to the use of a multicarboxylate, such as an alkyl alkoxy dicarboxylate, in enhanced oil recovery processes. Embodiments relate to an aqueous stream and the use thereof. The aqueous stream includes a compound having the chemical formula: R1-R2-R3, wherein R1 includes a branched or unbranched, saturated or unsaturated, cyclic or non-cyclic, hydrophobic carbon chain having an oxygen atom linking R1 and R2; R2 includes an alkoxylated chain comprising ethylene oxide, propylene oxide, butylene oxide, or a combination thereof; and R3 includes a branched or unbranched hydrocarbon chain and 2-5 —COOH or —COOM groups wherein M is a monovalent, divalent, or trivalent cation. R3 includes 2-12 carbon atoms.
-
公开(公告)号：US20220035070A1
公开(公告)日：2022-02-03
申请号：US16947401
申请日：2020-07-30
Applicant: Chevron U.S.A. Inc.
Inventor： Fabien J. Laugier , Alicia Downard , Robert Chadwick Holmes
Abstract: Simulated wells may be selected from a subsurface representation to serve as representation of the corresponding simulated subsurface region. Spatial coverage of a simulated well for the simulated subsurface region may be determined based on extent of similarity between the simulated well and other simulated wells in the subsurface representation. The simulated wells may be selected to achieve desired spatial coverage for the simulated subsurface region and to achieve desired representation of properties of interest for the simulated subsurface region.
-
154.发明申请公开(公告)号：US20220035069A1
公开(公告)日：2022-02-03
申请号：US16945517
申请日：2020-07-31
Applicant: CHEVRON U.S.A. INC. , THE TEXAS A&M UNIVERSITY SYSTEM
Inventor： Shuxing Cheng , Zhao Zhang , Kellen Leigh Gunderson , Reynaldo Cardona , Zhangyang Wang , Ziyu Jiang
Abstract: 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.
-
155.发明申请公开(公告)号：US20220035068A1
公开(公告)日：2022-02-03
申请号：US16945486
申请日：2020-07-31
Applicant: CHEVRON U.S.A. INC.
Inventor： Shuxing Cheng , Zhao Zhang , Kellen Leigh Gunderson , Reynaldo Cardona
Abstract: 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.
-
Patent Agency Ranking
公开(公告)号：US20220033704A1
公开(公告)日：2022-02-03
申请号：US17380502
申请日：2021-07-20
Applicant: Chevron U.S.A. Inc.
Inventor： Mark Charlesworth , Christopher John Kalli , Jon Even Vale , Brendan Francis Graham , Eric Freemantle May
Abstract: Provided herein are methods for inhibiting the formation of scale on equipment in contact with a produced fluid containing a scale-forming divalent cation. Such methods can comprise adding an activated alginate to the produced fluid in an amount effective to react with the divalent cation in the produced fluid to form an activated alginate complex; and separating the activated alginate complex from the produced fluid. Methods can further comprise recycling the activated alginate from the activated alginate complex by dissolving the activated alginate complex. The activated alginate can be prepared by thermally modifying an alginate precursor at a temperature of from 80° C. to 180° C. for a period of at least 24 hours. The activated alginate can be in the form of a solution including 0.1% to 10% by weight activated alginate, based on the total weight of the solution. The activated alginate can exhibit increased solubility in water and kinetics of complexation with the divalent cation compared to the alginate precursor.
-
公开(公告)号：US20220025735A1
公开(公告)日：2022-01-27
申请号：US16937720
申请日：2020-07-24
Applicant: CHEVRON U.S.A. INC.
Inventor： Andrew OGHENA
Abstract: Embodiments of reducing asphaltenes in produced fluids from a wellbore are provided herein. One embodiment comprises injecting a combination of gas and coated nanoparticles into a wellbore during a gas lift operation. The coated nanoparticles adsorb asphaltenes in the wellbore, thereby inhibiting asphaltene deposition, reducing asphaltene molecule interaction, reducing agglomeration of asphaltenes, or any combination thereof. The embodiment further comprises recovering produced fluids through the wellbore.
-
公开(公告)号：US20220024775A1
公开(公告)日：2022-01-27
申请号：US17324206
申请日：2021-05-19
Applicant: CHEVRON U.S.A. INC.
Inventor： Dan XIE
Abstract: An aluminosilicate molecular sieve material of BOG framework type, designated SSZ-122, is provided. SSZ-122 can be synthesized using 1-adamantyl-3-propylimidazolium cations as a structure directing agent. SSZ-122 may be used in organic compound conversion and/or sorptive processes.
-
公开(公告)号：US20220018981A1
公开(公告)日：2022-01-20
申请号：US17369825
申请日：2021-07-07
Applicant: Chevron U.S.A. Inc.
Inventor： Enning Wang
Abstract: A method is described for estimating seismic velocity from seismic data by training a neural network using a subset of a seismic dataset and the velocity model; estimating a second velocity model using the neural network and a second subset of the seismic dataset; and displaying the second velocity model on a graphical user interface. The method may be executed by a computer system.
-
160.发明申请公开(公告)号：US20210382198A1
公开(公告)日：2021-12-09
申请号：US16892050
申请日：2020-06-03
Applicant: Chevron U.S.A. Inc.
Inventor： Shuxing Cheng , Peng L. Ray
Abstract: A Gaussian process is used to provide a nonparametric approach for modeling nonlinear relationships among physical quantities involved in the geomechanics workflow supporting drilling & completion operations. Gaussian process provides a nonparametric framework that enables injection of a prior belief into the basic model format while allowing its specific format to be adaptive in a certain range following an estimated distribution. Both this model-related uncertainty and the pre-assumed input data distributions may be calibrated using non-parametric Bayesian framework with Gaussian process as prior. This approach not only the addresses the uncertainty stemming from the input physical properties but also tackles the uncertainties underlying the adopted physical model, all in this nonparametric Bayesian framework with Gaussian process encoded as prior.
-
-
-
-
-
-
-
-
-
Search Results
1892
records
(took 0.049 seconds)
