Unconventional Well Interference Detection Using Physics Informed Data Driven Model

    公开(公告)号:US20240410271A1

    公开(公告)日:2024-12-12

    申请号:US18680148

    申请日:2024-05-31

    Abstract: A method of detecting one or more well interference events at a well penetrating a reservoir in a subterranean formation is provided. The method includes: receiving wellhead pressure and flowrates of oil, gas, and water for the well during production; calculating a bottom hole pressure (BHP) of the well based on the wellhead pressure and flowrate of oil, gas, and water; calculating an average reservoir pressure based at least on the BHP; determining a productivity index (PI) for the well for a plurality of time steps based at least on the average reservoir pressure; determining a dataset of PI values and corresponding cumulative fluid production values from the well; analyzing the dataset to determine one or more breakpoints in a relationship between PI and cumulative fluid production representing one or more well interference events; and producing fluids from the reservoir based at least on the one or more breakpoints.

    Real Time Artificial Lift Timing and Selection Using Hybrid Data-Driven and Physics Models

    公开(公告)号:US20240344447A1

    公开(公告)日:2024-10-17

    申请号:US18631756

    申请日:2024-04-10

    CPC classification number: E21B47/06 E21B2200/20

    Abstract: A method of forecasting production using an artificial lift operation in a well penetrating a reservoir in a subterranean formation, comprising: receiving sensor feedback from the well during well production; receiving a flowrate of oil, gas, and water for the well; calculating average reservoir pressure and productivity index (PI) of the well based on a cumulative liquid rate; estimating reservoir deliverability based on the PI and average reservoir pressure; estimating well deliverability, based on one or more artificial lift parameters; estimating a bottomhole pressure (BHP) of the well based, at least in part, on the estimated reservoir deliverability and well deliverability; generating a multiphase forecast of an estimated liquid, gas, water, and oil production of the well, based, at least in part, on the estimated BHP and the sensor feedback; and producing fluids from the well based on the estimated liquid, gas, water, and oil production of the well.

    Data Driven Discovery of Unconventional Reservoir Physics

    公开(公告)号:US20240386169A1

    公开(公告)日:2024-11-21

    申请号:US18663520

    申请日:2024-05-14

    Abstract: A method of forecasting production of a well penetrating a reservoir in a subterranean formation, including: receiving a plurality of bottomhole pressures for the well; receiving a plurality of flowrates for the well; determining rate normalized pressure (RNP) data for the well over a period of time based on the plurality of bottomhole pressure and the plurality of flowrates; performing a sparse identification of nonlinear dynamics (SINDy) analysis on the RNP data to identify a relationship between flowrate and bottomhole pressure for the well, wherein the SINDy analysis is based on a plurality of physics features; providing a forecast of future production for the well based on the identified relationship between flowrate and bottomhole pressure for the well; and producing fluids from the reservoir based, at least in part, on the forecast of future production.

    Gas-oil ratio forecasting in unconventional reservoirs

    公开(公告)号:US11767750B1

    公开(公告)日:2023-09-26

    申请号:US18076921

    申请日:2022-12-07

    CPC classification number: E21B47/008 E21B47/07 G01V99/005 E21B2200/20

    Abstract: An apparatus for estimating a gas-oil ratio for a well in an unconventional reservoir comprises a processor associated with a control system. The processor is configured to determine a bottomhole pressure for the well. The processor is further configured to determine one or more pressure, volume, and temperature (PVT) properties associated with fluid flow and to determine transient well performance. The processor is further configured to determine a Productivity Index (PI) for the well for a plurality of time steps and to determine an inflection point. The processor is further configured to estimate the gas-oil ratio of the well after the inflection point based on the determined transient well performance and to perform the fluid production rate forecast based on the determined PI. The processor is further configured to apply the fluid production rate forecast to the estimated gas-oil ratio to determine an instantaneous gas-oil ratio.

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