CN-121994593-A - Rock elastic modulus prediction method and device, electronic equipment and storage medium

CN121994593ACN 121994593 ACN121994593 ACN 121994593ACN-121994593-A

Abstract

The invention discloses a rock elastic modulus prediction method and device, electronic equipment and a storage medium. The method comprises the steps of respectively obtaining nano indentation test data corresponding to each position point in real time in the process of carrying out nano indentation test on at least two position points of a rock sample, determining mineral component types corresponding to each position point, wherein the mineral component types comprise hard components and soft components, determining the elastic modulus of the hard components and the elastic modulus of the soft components of the rock sample according to the nano indentation test data corresponding to each position point and the mineral component types corresponding to each position point, and determining the elastic modulus of the rock sample based on the elastic modulus of the hard components and the elastic modulus of the soft components. By the technical scheme provided by the embodiment of the invention, the difficult problem that partial parameters are assumed to be difficult to calculate in the existing model is solved, and the accurate prediction of the rock elastic modulus is realized.

Inventors

CHANG LONG
WANG HAIGE
HUANG HONGCHUN
ZHUO LUBIN
ZOU LINGZHAN
LI HONG
JI GUODONG
REN MING
ZHANG JIAWEI

Assignees

中国石油天然气集团有限公司
中国石油集团工程技术研究院有限公司

Dates

Publication Date: 20260508
Application Date: 20241107

Claims (10)

1. A method for predicting the elastic modulus of rock, comprising: Respectively acquiring nano indentation test data corresponding to each position point in real time in the process of carrying out nano indentation test on at least two position points of a rock sample; determining a mineral component type corresponding to each position point, wherein the mineral component type comprises a hard component and a soft component; Determining the hard component elastic modulus and the soft component elastic modulus of the rock sample according to the nano indentation test data corresponding to each position point and the mineral component type corresponding to each position point; the rock elastic modulus of the rock sample is determined based on the hard component elastic modulus and the soft component elastic modulus.
2. The method of claim 1, further comprising, prior to determining the rock elastic modulus of the rock sample based on the hard component elastic modulus and soft component elastic modulus: determining the hard component volume content of the rock sample; determining a rock elastic modulus of the rock sample based on the hard component elastic modulus and soft component elastic modulus, comprising: determining a hard component bulk modulus of the rock sample from the hard component elastic modulus and determining a soft component bulk modulus of the rock sample from the soft component elastic modulus; Determining a rock bulk modulus of the rock sample according to the hard component bulk modulus, the soft component bulk modulus and the hard component bulk content; and determining the rock elastic modulus of the rock sample according to the rock bulk modulus.
3. The method of claim 2, further comprising, prior to determining the rock bulk modulus of the rock sample from the hard component bulk modulus, the soft component bulk modulus, and the hard component bulk content: determining the particle sizes of the hard component mineral particles corresponding to the hard component position points in the at least two position points, and calculating the average value of the particle sizes of the hard component mineral particles of all the hard component position points, wherein the hard component position points are position points with the mineral component type being hard components; Determining the modulus of the cementing surface corresponding to each position point in the at least two position points according to the nano indentation test data, and calculating the average value of the modulus of the cementing surface of all the position points; Calculating an intermediate variable according to the average particle size of the hard component mineral particles and the average modulus of the cementing surface; determining the rock bulk modulus of the rock sample from the hard component bulk modulus, the soft component bulk modulus, and the hard component bulk content, comprising: and determining the rock bulk modulus of the rock sample according to the hard component bulk modulus, the soft component bulk modulus, the hard component bulk content and the intermediate variable.
4. The method of claim 3, wherein the nano-indentation test data comprises an indentation depth and a depth elastic modulus as a function of the indentation depth; Determining the modulus of the cementing surface corresponding to each of the at least two location points according to the nano indentation test data, including: For each of the at least two position points, determining a maximum depth elastic modulus and a stable elastic modulus which remains unchanged as the indentation depth increases according to the depth elastic modulus which corresponds to the position point and changes with the indentation depth; and taking the difference between the maximum depth elastic modulus and the stable elastic modulus as the cementing surface modulus corresponding to the position point.
5. The method of claim 1, wherein the nano-indentation test data comprises an indentation depth and a depth elastic modulus as a function of the indentation depth; according to the nano indentation test data corresponding to each position point and the mineral component type corresponding to each position point, determining the hard component elastic modulus and the soft component elastic modulus of the rock sample comprises the following steps: Determining a first location point of the mineral component type being a hard component and a second location point of the mineral component type being a soft component from the at least two location points; determining a first position elastic modulus corresponding to the first position point according to the depth elastic modulus corresponding to the first position point and changing along with the pressing depth, and determining a second position elastic modulus corresponding to the second position point according to the depth elastic modulus corresponding to the second position point and changing along with the pressing depth; Taking the average value of the elastic modulus of the first position corresponding to all the first position points as the elastic modulus of the hard component of the rock sample, and taking the average value of the elastic modulus of the second position corresponding to all the second position points as the elastic modulus of the soft component of the rock sample.
6. The method of claim 5, wherein determining the first positional elastic modulus corresponding to the first positional point based on the depth elastic modulus corresponding to the first positional point as a function of the depth of penetration comprises: And determining the corresponding maximum depth elastic modulus in a preset indentation depth interval from the depth elastic modulus corresponding to the first position point and changing along with the indentation depth, and taking the maximum depth elastic modulus as the first position elastic modulus corresponding to the first position point.
7. The method of claim 5, wherein determining the second location elastic modulus corresponding to the second location point based on the depth elastic modulus corresponding to the second location point as a function of the depth of penetration comprises: And determining the stable and unchanged depth elastic modulus in the preset depth length from the depth elastic modulus which corresponds to the second position point and changes along with the pressing depth, and taking the stable and unchanged depth elastic modulus as the second position elastic modulus which corresponds to the second position point.
8. A device for predicting the elastic modulus of rock, comprising: the test data acquisition module is used for respectively acquiring nano indentation test data corresponding to each position point in real time in the process of carrying out nano indentation test on at least two position points of the rock sample; the system comprises a mineral component type determining module, a mineral component type determining module and a mineral component determining module, wherein the mineral component type determining module is used for determining a mineral component type corresponding to each position point, and the mineral component type comprises a hard component and a soft component; The component elastic modulus determining module is used for determining the hard component elastic modulus and the soft component elastic modulus of the rock sample according to the nano indentation test data corresponding to each position point and the mineral component type corresponding to each position point; and the rock elastic modulus determining module is used for determining the rock elastic modulus of the rock sample based on the hard component elastic modulus and the soft component elastic modulus.
9. An electronic device, the electronic device comprising: At least one processor, and A memory communicatively coupled to the at least one processor, wherein, The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of predicting the elastic modulus of rock of any one of claims 1-7.
10. A computer readable storage medium, characterized in that the computer readable storage medium stores computer instructions for causing a processor to execute the method of predicting the elastic modulus of rock according to any one of claims 1-7.

Description

Rock elastic modulus prediction method and device, electronic equipment and storage medium Technical Field The invention relates to the technical field of oil and gas field development, in particular to a method and a device for predicting elastic modulus of rock, electronic equipment and a storage medium. Background Currently, the available production of conventional oil and gas resources is gradually decreased year by year, while the demand of the oil and gas resources is gradually increased, and the proportion of ultra-deep and unconventional oil and gas occupied energy sources is gradually increased. Deep oil and gas geological conditions are complex, drilling operation risks are high, unconventional oil and gas resource development cost is high, and key technologies and basic theoretical systems of safe and efficient well drilling and completion are required to be further established to be sound and perfect. Rock mechanical parameter evaluation is the basis of well drilling rock breaking, stratum pressure monitoring, well wall stability evaluation and reservoir fracturing modification, wherein the rock elastic modulus is the key. The traditional method is used for carrying out rock uniaxial compression experiments through drilling coring, the laboratory test is time-consuming and labor-consuming, and the construction cost and time of the drilling site coring operation are increased. In order to predict macroscopic mechanical parameters of rock efficiently, scholars have built a large number of models to solve this problem. Such as Voigt model, reuss model, hill model, hashin-SHTRIKMAN, etc. average model based on rock composition. The model predicts the mechanical parameters of the whole rock by taking the volume ratio of the components forming the rock and the mechanical properties of each component as input parameters. The prediction result is a range, and is often given in the form of upper and lower limits, and the accuracy is required to be improved. Another class of methods considers the interaction of stress and strain between components to predict macroscopic mechanical behavior. Such as Eshelby equivalent inclusion theory, self-consistent methods, mori-Tanaka methods, generalized self-consistent methods, differential methods, and the like. Compared with the former method, the method has certain engineering application value. However, the calculation parameters in the method are complex, and a large number of parameters cannot be obtained by actual test. The method is applied to mechanical parameter prediction of stratum rock, can be calculated by assuming some parameters, and is extremely difficult to apply in engineering. Disclosure of Invention The invention provides a rock elastic modulus prediction method, a device, electronic equipment and a storage medium, solves the problem that partial parameters are assumed to be difficult to calculate in the existing model, and realizes accurate prediction of the rock elastic modulus. According to an aspect of the present invention, there is provided a method for predicting elastic modulus of rock, comprising: Respectively acquiring nano indentation test data corresponding to each position point in real time in the process of carrying out nano indentation test on at least two position points of a rock sample; determining a mineral component type corresponding to each position point, wherein the mineral component type comprises a hard component and a soft component; Determining the hard component elastic modulus and the soft component elastic modulus of the rock sample according to the nano indentation test data corresponding to each position point and the mineral component type corresponding to each position point; the rock elastic modulus of the rock sample is determined based on the hard component elastic modulus and the soft component elastic modulus. According to another aspect of the present invention, there is provided a device for predicting elastic modulus of rock, comprising: the test data acquisition module is used for respectively acquiring nano indentation test data corresponding to each position point in real time in the process of carrying out nano indentation test on at least two position points of the rock sample; the system comprises a mineral component type determining module, a mineral component type determining module and a mineral component determining module, wherein the mineral component type determining module is used for determining a mineral component type corresponding to each position point, and the mineral component type comprises a hard component and a soft component; The component elastic modulus determining module is used for determining the hard component elastic modulus and the soft component elastic modulus of the rock sample according to the nano indentation test data corresponding to each position point and the mineral component type corresponding to each position point; and the rock elastic modulus determining mo