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    ELEMENTAL SULFUR ANALYSIS IN FLUIDS
    32.
    发明公开
    ELEMENTAL SULFUR ANALYSIS IN FLUIDS 审中-公开

    公开(公告)号：US20230324361A1

    公开(公告)日：2023-10-12

    申请号：US18335664

    申请日：2023-06-15

    Applicant: CONOCOPHILLIPS COMPANY

    Inventor： Jay LOCKLEAR ,  Clinton CROWE

    IPC: G01N33/28 ,  G01N21/75

    CPC classification number: G01N33/287 ,  G01N21/75 ,  Y10T436/188 ,  Y10T436/109163

    Abstract: Robust methods for quantitating the amount of elemental sulfur in a fluid whereby a caustic solution is mixed with the fluid, and the elemental sulfur present in the fluid reacts to form a colored solution that can be compared to a series of standards. The methods can be performed in a laboratory or the field and allow for real time feedback. Once the concentration of the elemental sulfur is known, appropriate methods of treatment can proceed. Test kits for performing the methods in the field are also described.

    MACHINE LEARNING BASED RESERVOIR MODELING
    34.
    发明公开
    MACHINE LEARNING BASED RESERVOIR MODELING 审中-公开

    公开(公告)号：US20230237225A1

    公开(公告)日：2023-07-27

    申请号：US18100928

    申请日：2023-01-24

    Applicant: ConocoPhillips Company

    Inventor： Chung-Kan Huang ,  Qing Chen

    IPC: G06F30/27

    CPC classification number: G06F30/27

    Abstract: Systems and methods for reservoir modeling use reservoir simulation and production data to predict future production for one or more wells. The system receives static data of a reservoir or well, receives dynamic data of the reservoir or well, and processes the static data and the dynamic data to generate a reservoir model. For instance, the static data and dynamic data can be used to generate a Voronoi grid, which is used to create a spatio-temporal dataset representing time steps for a focal well and offset wells. The reservoir model can predict reservoir performance, field development, production metrics, and operation metrics. By using one or more Machine Learning (ML) models, the systems disclosed herein can determined reservoir physics in minutes and replicate the physical properties calculated by more complex and computationally intensive reservoir modeling.

    SYSTEMS AND METHODS FOR NUCLEAR MAGNETIC RESONANCE (NMR) WELL LOGGING)
    35.
    发明公开
    SYSTEMS AND METHODS FOR NUCLEAR MAGNETIC RESONANCE (NMR) WELL LOGGING) 审中-公开

    公开(公告)号：US20230236337A1

    公开(公告)日：2023-07-27

    申请号：US18100876

    申请日：2023-01-24

    Applicant: ConocoPhillips Company

    Inventor： Tianmin Jiang ,  Ronald J.M. Bonnie

    IPC: G01V3/32 ,  E21B49/00

    CPC classification number: G01V3/32 ,  E21B49/00

    Abstract: Systems and method for nuclear magnetic resonance (NMR) well logging use an inversion pulse sequence with a Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence to improve spin magnetization calculations. Improved Bloch equation-based calculations consider conditions where a longitudinal relaxation time and a transverse relaxation time of the hydrogen nuclei (e.g., of a subterranean hydrocarbon pool and/or water) are within an order of magnitude of pulse durations for the inversion pulse sequence and the CPMG pulse sequence. Accordingly, an NMR response to the inversion pulse sequence and the CPMG pulse can be detected and used to calculate one or more spin magnetization values with higher accuracy amplitudes. Reservoir characteristics are determined based on the one or more spin magnetization values. As such, improved well operations (e.g., selecting a drilling site, determining a drilling depth, and the like) can be performed.

    BEHIND CASING WASH AND CEMENT
    36.
    发明公开
    BEHIND CASING WASH AND CEMENT 审中-公开

    公开(公告)号：US20230228173A1

    公开(公告)日：2023-07-20

    申请号：US18116744

    申请日：2023-03-02

    Applicant: CONOCOPHILLIPS COMPANY

    Inventor： Rick WATTS ,  Stein HAAVARDSTEIN ,  Lars HOVDA ,  James C. STEVENS ,  Dan MUELLER ,  Brett Borland ,  Amal PHADKE ,  Praveen GONUGUNTLA

    IPC: E21B41/00 ,  E21B37/00

    CPC classification number: E21B41/0078 ,  E21B37/00

    Abstract: The invention relates to a method of conducting a perf wash cement (“P/W/C”) abandonment job in an offshore oil or gas well annulus (2), in particular the washing or cementing operation using a rotating head (6, 8) with nozzles (7, 9) dispensing wash fluid or cement at pressure. Certain values of parameters of a washing or cementing job have been found surprisingly to affect the quality of the job, or the degree to which they affect the quality of the job has been unexpected. These include including rotation rate of the tool, the direction of translational movement of the tool, and the volume flow rate and pressure per nozzle of cement or wash fluid (and hence nozzle size).

    SYSTEMS AND METHODS FOR DETERMINING SURFACTANT IMPACT ON RESERVOIR WETTABILITY
    38.
    发明公开
    SYSTEMS AND METHODS FOR DETERMINING SURFACTANT IMPACT ON RESERVOIR WETTABILITY 审中-公开

    公开(公告)号：US20230152255A1

    公开(公告)日：2023-05-18

    申请号：US17988517

    申请日：2022-11-16

    Applicant: ConocoPhillips Company

    Inventor： Hesham F. El-Sobky ,  Ronald J.M. Bonnie ,  Tianmin Jiang

    IPC: G01N24/08 ,  G01V3/32

    CPC classification number: G01N24/081 ,  G01V3/32

    Abstract: Implementations described and claimed herein provide systems and methods for determining surfactant impact on reservoir wettability. In one implementation, a nuclear magnetic resonance T1 measurement of a sample is obtained before surfactant imbibition is applied to the sample, and a second nuclear magnetic T2 measurement of the sample is made after forced imbibition of the surfactant. Moreover, another nuclear magnetic resonance T1 measurement (e.g., omitting surfactant imbibition) can be obtained simultaneously with the nuclear magnetic resonance T2 measurement using a twin core sample. The nuclear magnetic resonance T1 measurement and the nuclear magnetic resonance T2 measurement are captured under simulated reservoir conditions. A fluid typing map is generated using the nuclear magnetic resonance T1 measurement and the nuclear magnetic resonance T2 measurement. An impact of the surfactant on fluid producibility is determined based on the fluid typing map.

    SYSTEMS AND METHODS OF PREDICTIVE DECLINE MODELING FOR A WELL
    39.
    发明公开
    SYSTEMS AND METHODS OF PREDICTIVE DECLINE MODELING FOR A WELL 审中-公开

    公开(公告)号：US20230142526A1

    公开(公告)日：2023-05-11

    申请号：US17982926

    申请日：2022-11-08

    Applicant: ConocoPhillips Company

    Inventor： Qing Chen ,  Xin Luo ,  Amir Nejad ,  Bo Hu ,  Christopher S. Olsen ,  Alexander J. Wagner ,  Iman Shahim ,  Curt E. Schneider ,  David D. Smith ,  Andy Flowers ,  Liu Chao Zhang

    IPC: G06F30/28

    CPC classification number: G06F30/28

    Abstract: Systems and method for predicting production decline for a target well include generating a static model and a decline model to generate a well production profile. The static model is generated with supervised machine learning using an input data set including historical production data, and calculates an initial resource production rate for the target well. The decline model is generated with a neural network using the input data and dynamic data (e.g., an input time interval and pressure data of the target well), and calculates a plurality of resource production rates for a plurality of time intervals. The system can perform multiple recursive calculations to calculate the plurality of resource production rates, generating the well production profile. For instance, the predicted resource production rate of a first time interval is used as one of inputs for predicting the resource production rate for a second, subsequent time interval.

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