CN-122020270-A - Reservoir flow unit identification method and device, electronic equipment and storage medium

CN122020270ACN 122020270 ACN122020270 ACN 122020270ACN-122020270-A

Abstract

The embodiment of the application provides a method and a device for identifying a reservoir flow unit, electronic equipment and a storage medium. The method comprises the steps of obtaining core analysis data, inputting the core analysis data into a reservoir flow unit identification model to obtain an identification result, determining the reservoir flow unit identification model based on a response curve of a detected well and corresponding historical logging data, and classifying the flow unit of the reservoir to be tested according to the identification result. The method can be used for rapidly and efficiently identifying the reservoir flow unit, and the identification accuracy of the reservoir flow unit is improved.

Inventors

ZHAO YINAN
ZHAO GUOYING
LUO SHENGYONG
Zou Liansong
Wei Tianli
MENG QINGHUA
ZHANG DI
WANG ZHONGXING
WANG QI
YU YAOHAN
HU KAI
JIA HAIYAN
HU QINGHE

Assignees

中国石油集团长城钻探工程有限公司
中国石油天然气集团有限公司

Dates

Publication Date: 20260512
Application Date: 20241112

Claims (11)

1. A method of identifying a reservoir flow unit, comprising: Acquiring core analysis data, wherein the core analysis data is used for indicating lithology and physical properties of a reservoir to be tested; Inputting the core analysis data into a reservoir flow unit identification model to obtain an identification result, wherein the reservoir flow unit identification model is determined based on a response curve of a detected well and corresponding historical logging data; and classifying the flow units of the reservoir to be tested according to the identification result.
2. The method of claim 1, wherein prior to the obtaining core analysis data, the method further comprises: acquiring historical logging data of a plurality of detected wells, and determining a response curve of each detected well based on the historical logging data, wherein the response curve is used for indicating physical properties corresponding to formations at different depths in the detected wells; and constructing the reservoir flow unit identification model based on response curves of the plurality of detected wells.
3. The method of claim 2, wherein the constructing the reservoir flow unit identification model based on the response curves of the plurality of detected wells comprises: Determining, for any one of a plurality of detected wells, a sensitivity intensity of the detected well based on historical log data and response curves for the detected well; determining a target response curve from the plurality of response curves, wherein the sensitivity intensity of the detected well corresponding to the target response curve is highest; and determining a multi-parameter fitting equation based on the target response curve, and constructing the reservoir flow unit identification model based on the multi-parameter fitting equation.
4. A method according to claim 3, wherein said determining a multiparameter fitting equation based on said target response curve comprises: determining first flow unit indexes corresponding to a plurality of reservoir parameters according to the target response curve; The multi-parameter fitting equation is determined based on a plurality of first flow cell indices and fitting coefficients.
5. The method of claim 1, wherein the core analysis data comprises porosity, permeability, and clay content, and wherein the inputting the core analysis data into a reservoir flow unit identification model results in an identification result comprises: And carrying the porosity, the permeability and the argillaceous content into the multi-parameter fitting equation to obtain a flow unit identification result of the reservoir to be tested, wherein the flow unit identification result is used for indicating flow units respectively matched with the porosity, the permeability and the argillaceous content.
6. The method of claim 5, wherein classifying the flow cells of the reservoir to be tested based on the identification results comprises: performing cluster analysis processing based on the identification result and the core analysis data to obtain a cluster analysis spectrogram; And carrying out intersection graph analysis processing on the cluster analysis spectrogram and the identification result to obtain a flow unit classification result of the reservoir to be tested, wherein the classification result is used for indicating types of a plurality of flow units corresponding to the reservoir to be tested and reservoir physical characteristics of each type, and reservoir physical characteristics corresponding to different types of flow units are different.
7. The method of claim 6, wherein the method further comprises: Establishing a logging interpretation model based on response curves of the plurality of detected wells; inputting historical logging data of the plurality of detected wells into the logging interpretation model to obtain a first interpretation of each detected well, the first interpretation being used to indicate a second flow cell index of the detected well; Under the condition that second flow unit indexes of the detected wells are matched with corresponding historical flow unit indexes, inputting the core analysis data into the logging interpretation model to obtain a second interpretation result of the reservoir to be tested, wherein the second interpretation result is used for indicating a third flow unit index of the reservoir to be tested; And based on the third flow unit index, performing accuracy check on the classification result.
8. An identification device for a reservoir flow unit, comprising: the acquisition module is used for acquiring core analysis data, wherein the core analysis data are used for indicating lithology and physical properties of a reservoir to be tested; The processing module is used for inputting the rock core analysis data into a reservoir flow unit identification model to obtain an identification result, the reservoir flow unit identification model is determined based on a response curve of a detected well and corresponding historical logging data, and the response curve of the detected well is determined based on the historical logging data; And the processing module is also used for classifying the flow units of the reservoir to be tested according to the identification result.
9. An apparatus, comprising: a memory; A processor; The memory stores computer-executable instructions; The processor executing computer-executable instructions stored in the memory, causing the processor to perform the method of any one of claims 1-7.
10. A computer readable storage medium having stored therein computer executable instructions which when executed by a processor are adapted to carry out the method of identifying a reservoir flow unit as claimed in any one of claims 1 to 7.
11. A computer program product comprising a computer program which, when executed by a processor, implements a method of identifying a reservoir flow unit as claimed in any one of claims 1 to 7.

Description

Reservoir flow unit identification method and device, electronic equipment and storage medium Technical Field The application relates to the technical field of oil and gas field development, in particular to a method and a device for identifying a reservoir flow unit, electronic equipment and a storage medium. Background Reservoir flow units refer to reservoir rock masses of similar lithology and physical properties of a reservoir within the flow field of the same fluid. Different types of flow cells differ in their lithology and physical properties. The main purpose of reservoir flow unit identification is to subdivide a reservoir into units with similar fluid flow characteristics in order to more accurately describe the reservoir heterogeneity, predict the flow behavior of fluids in the reservoir, and provide a scientific basis for oilfield development. In the existing reservoir flow unit identification method, the identification efficiency and accuracy are low due to fewer key factors adopted in field application. Disclosure of Invention The embodiment of the application provides a method, a device, electronic equipment and a storage medium for identifying a reservoir flow unit, which are used for solving the problems of insufficient accuracy and efficiency caused by the selection difference of key test factors under a complex field environment. In a first aspect, an embodiment of the present application provides a method for identifying a reservoir flow unit, the method including: Acquiring core analysis data, wherein the core analysis data is used for indicating lithology and physical properties of a reservoir to be tested; Inputting the core analysis data into a reservoir flow unit identification model to obtain an identification result, wherein the reservoir flow unit identification model is determined based on a response curve of a detected well and corresponding historical logging data, and the response curve of the detected well is determined based on the historical logging data; and classifying the flow units of the reservoir to be tested according to the identification result. In one possible implementation manner, before the obtaining core analysis data, the method further includes: acquiring historical logging data of a plurality of detected wells, and determining a response curve of each detected well based on the historical logging data, wherein the response curve is used for indicating physical properties corresponding to formations at different depths in the detected wells; and constructing the reservoir flow unit identification model based on response curves of the plurality of detected wells. In one possible implementation, the constructing the reservoir flow unit identification model based on response curves of the plurality of detected wells includes: Determining, for any one of a plurality of detected wells, a sensitivity intensity of the detected well based on historical log data and response curves for the detected well; determining a target response curve from the plurality of response curves, wherein the sensitivity intensity of the detected well corresponding to the target response curve is highest; and determining a multi-parameter fitting equation based on the target response curve, and constructing the reservoir flow unit identification model based on the multi-parameter fitting equation. In one possible implementation, the determining a multi-parameter fitting equation based on the target response curve includes: determining first flow unit indexes corresponding to a plurality of reservoir parameters according to the target response curve; The multi-parameter fitting equation is determined based on a plurality of first flow cell indices and fitting coefficients. In one possible implementation, the core analysis data includes porosity, permeability and clay content, and the inputting the core analysis data into a reservoir flow unit identification model to obtain an identification result includes: And carrying the porosity, the permeability and the argillaceous content into the multi-parameter fitting equation to obtain a flow unit identification result of the reservoir to be tested, wherein the flow unit identification result is used for indicating flow units respectively matched with the porosity, the permeability and the argillaceous content. In a possible implementation manner, the classifying the flow units of the reservoir to be tested according to the identification result includes: performing cluster analysis processing based on the identification result and the core analysis data to obtain a cluster analysis spectrogram; And carrying out intersection graph analysis processing on the cluster analysis spectrogram and the identification result to obtain a flow unit classification result of the reservoir to be tested, wherein the classification result is used for indicating types of a plurality of flow units corresponding to the reservoir to be tested and reservoir physic