Method, apparatus and computer storage medium for determining influencing factors of rock resistivity

Abstract

An embodiment of the present application discloses a method, device, and computer storage medium for determining influencing factors of rock resistivity, belonging to the technical field of oil and gas exploration. The method includes: when receiving an instruction for determining influencing factors, obtaining the conductive mineral content, clay mineral content, saturation, and resistivity of at least three rock samples in a target production well; determining the weight parameters corresponding to the respective influencing factors of the rock resistivity in the target production well according to the conductive mineral content, clay mineral content, saturation, and resistivity of the at least three rock samples; and determining the influencing factor with the smallest weight parameter as the main controlling factor of the rock resistivity in the target production well. The embodiment of the present application fully considers the influence of the conductive mineral content, clay mineral content, and saturation on the rock resistivity, and can not only effectively determine the main controlling factor affecting the rock resistivity, but also determine the weight parameters of the respective influencing factors.

Description

Technical Field

[0001] Embodiments of the present application relate to the technical field of oil and gas exploration, and particularly to a method, device and computer storage medium for determining influencing factors of rock resistivity. Background Art

[0002] In geological exploration, the resistivity method has a wide range of applications in mineral prospecting, energy exploration, research on geological structures, engineering geological surveys, etc. One of the bases of the resistivity method is the resistivity of rocks. The resistivity of rocks is a basic parameter characterizing the conductivity of rocks and is a physical quantity reflecting the internal structure and composition of rocks. It is closely related to the elastic modulus, density and fracture occurrence state of rocks, and can effectively reflect the changes in micro-fractures inside rocks, playing an important role in studying the inherent characteristics and occurrence state of rocks. Therefore, in order to accurately divide the geological profile of a drilling well based on resistivity values and solve geological problems, it is necessary to determine the influencing factors of rock resistivity.

[0003] Currently, the method for determining the influencing factors of rock resistivity is as follows: Based on the derivation of the theoretical model of rock-electricity experiments, the theoretical value range and value trend of reservoir rock-electricity experimental data under different pore structures are formed to constitute the reservoir pore structure zoning on the rock-electricity data plate. By testing the distribution of the rock-electricity data on the plate, it is determined that rock samples of different types of reservoirs are in different distinguishable zones remaining on the plate, thereby determining the influencing factors affecting rock resistivity.

[0004] However, when determining the influencing factors of rock resistivity by the above method, the main controlling factors affecting rock resistivity cannot be determined quickly, efficiently and accurately, and the influence magnitudes of various influencing factors cannot be accurately judged. Summary of the Invention

[0005] Embodiments of the present application provide a method, device and computer storage medium for determining influencing factors of rock resistivity, which can be used to solve the problem in related technologies that the main controlling factors affecting rock resistivity cannot be accurately determined and the influence magnitudes of various influencing factors cannot be accurately judged. The technical solutions are as follows:

[0006] On the one hand, a method for determining influencing factors of rock resistivity is provided, and the method includes:

[0007] When receiving an influencing factor determination instruction, obtaining the conductive mineral content, clay mineral content, saturation and resistivity of at least three rock samples in a target production well, and the well depth of any one of the at least three rock samples in the target production well is different from the well depths of other rock samples among the at least three rock samples;

[0008] Determine the weight parameters corresponding to the influencing factors that affect the resistivity of the rock in the target production well according to the conductive mineral content, clay mineral content, saturation, and resistivity of the at least three rock samples, where the influencing factors of the rock resistivity include conductive minerals, clay minerals, and formation water;

[0009] Determine the main controlling factor that affects the resistivity of the rock in the target production well as the influencing factor with the smallest weight parameter.

[0010] In some embodiments, obtaining the conductive mineral content, clay mineral content, saturation, and resistivity of at least three rock samples in the target production well includes:

[0011] Perform X-ray diffraction analysis on the at least three rock samples through an X-ray diffraction device to obtain the conductive mineral content and clay mineral content of the at least three rock samples;

[0012] Obtain the formation water resistivity, rock porosity, and formation resistivity of the target production well, as well as the petrophysical parameters and resistivity of the at least three rock samples from a storage file;

[0013] Determine the saturation of the at least three rock samples according to the formation water resistivity, rock porosity, and formation resistivity of the target production well, and the petrophysical parameters of the at least three rock samples through Archie's formula.

[0014] In some embodiments, determining the weight parameters corresponding to the influencing factors that affect the resistivity of the rock in the target production well according to the conductive mineral content, clay mineral content, saturation, and resistivity of the at least three rock samples includes:

[0015] Determine the relationship between the resistivity of each rock sample among the at least three rock samples and the corresponding clay mineral content;

[0016] When the relationship between the resistivity of each rock sample and the corresponding clay mineral content is positively correlated, determine that the clay mineral is not an influencing factor that affects the resistivity of the rock in the target production well, and process the conductive mineral content, clay mineral content, saturation, and resistivity of any two rock samples among the at least three rock samples through a main controlling factor analysis model to obtain the weight parameter corresponding to the formation water and the weight parameter corresponding to the conductive mineral in the target production well;

[0017] When the relationship between the resistivity of each rock sample and the corresponding clay mineral content is negatively correlated, the conductive mineral content, clay mineral content, saturation, and resistivity of each rock sample among the at least three rock samples are respectively processed through the main control factor analysis model to obtain the weight parameter corresponding to the formation water in the target production well, the weight parameter corresponding to the conductive mineral, and the weight parameter corresponding to the clay mineral.

[0018] In some embodiments, the main control factor analysis model is the following model:

[0019]

[0020] Wherein, R is the resistivity of any one of the rock samples, a, b, n, and m are the petrophysical parameters of any one of the rock samples, and W 导 is the conductive mineral content of any one of the rock samples, W 黏 is the clay mineral content of any one of the rock samples, R w is the resistivity of the formation water in the target production well, Φ is the rock porosity of the target production well, R t is the formation resistivity of the target production well, x is the weight parameter corresponding to the formation water, y is the weight parameter corresponding to the conductive mineral, and z is the weight parameter corresponding to the clay mineral.

[0021] In some embodiments, after determining the influencing factor with the smallest weight parameter as the main control factor affecting the rock resistivity in the target production well, it further includes:

[0022] Prompting the main control factor of the rock resistivity in the target production well through a first prompt message.

[0023] On the other hand, a device for determining the influencing factors of rock resistivity is provided, and the device includes:

[0024] An acquisition module, configured to acquire the conductive mineral content, clay mineral content, saturation, and resistivity of at least three rock samples in the target production well when receiving an influencing factor determination instruction, and the well depth of any one of the at least three rock samples in the target production well is different from the well depths of other rock samples among the at least three rock samples;

[0025] A first determination module, configured to determine the weight parameters corresponding to the respective influencing factors affecting the rock resistivity in the target production well according to the conductive mineral content, clay mineral content, saturation, and resistivity of the at least three rock samples, and the influencing factors of the rock resistivity include conductive minerals, clay minerals, and formation water;

[0026] The second determination module is used to determine the influencing factor with the smallest weight parameter as the main controlling factor affecting the rock resistivity in the target production well.

[0027] In some embodiments, the acquisition module includes:

[0028] an analysis submodule, configured to perform X-ray diffraction analysis on the at least three rock samples using an X-ray diffraction device to obtain the conductive mineral content and the clay mineral content of the at least three rock samples;

[0029] A first acquisition submodule is configured to acquire, from a storage file, the formation water resistivity, rock porosity, and formation resistivity of the target production well, as well as the rock electrical parameters and resistivity of the at least three rock samples;

[0030] The first determination submodule is used to determine the saturation of the at least three rock samples using the Archie formula based on the formation water resistivity, rock porosity and formation resistivity of the target production well and the rock electrical parameters of the at least three rock samples.

[0031] In some embodiments, the first determining module includes:

[0032] a second determination submodule, configured to determine a relationship between the resistivity of each of the at least three rock samples and the corresponding clay mineral content;

[0033] a first processing submodule for determining, when a positive correlation exists between the resistivity of each rock sample and the corresponding clay mineral content, that clay minerals are not a factor affecting the resistivity of the rock in the target production well, and for processing the conductive mineral content, clay mineral content, saturation, and resistivity of any two of the at least three rock samples using a main controlling factor analysis model to obtain weight parameters corresponding to formation water and conductive minerals in the target production well;

[0034] The second processing submodule is used to process the conductive mineral content, clay mineral content, saturation and resistivity of each of the at least three rock samples through the main control factor analysis model when the resistivity of each rock sample is negatively correlated with the corresponding clay mineral content, so as to obtain the weight parameters corresponding to the formation water in the target production well, the weight parameters corresponding to the conductive minerals and the weight parameters corresponding to the clay minerals.

[0035] In some embodiments, the main controlling factor analysis model is the following model:

[0036]

[0037] Wherein, R is the resistivity of any one of the rock samples, a, b, n, and m are the petrophysical parameters of any one of the rock samples, and W 导 is the content of conductive minerals in any one of the rock samples, and W 黏 is the content of clay minerals in any one of the rock samples, R w is the formation water resistivity of the target production well, Φ is the rock porosity of the target production well, and R t is the formation resistivity of the target production well, x is the weight parameter corresponding to the formation water, y is the weight parameter corresponding to the conductive minerals, and z is the weight parameter corresponding to the clay minerals.

[0038] In some embodiments, the device further includes:

[0039] A prompt module, configured to prompt the main control factors of the rock resistivity in the target production well through a first prompt message.

[0040] On the other hand, a computer-readable storage medium is provided, on which instructions are stored, and when the instructions are executed by a processor, any step in the above method for determining the influencing factors of rock resistivity is implemented.

[0041] The beneficial effects brought by the technical solutions provided in the embodiments of the present application at least include:

[0042] In the embodiments of the present application, the main control factors of rock resistivity are determined through the weight parameters corresponding to the content of conductive minerals, the content of clay minerals, and the saturation. Since all factors affecting rock resistivity are fully considered, the integrity and comprehensiveness of determining the main control factors of rock resistivity are improved. At the same time, since no manual operation is required to obtain the determination parameters and no manual calculation is required during the process of determining the main control factors, the accuracy and efficiency of determining the main control factors are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0044] Figure 1 is a schematic diagram of an implementation environment provided by an embodiment of the present application;

[0045] Figure 2 is a flowchart of a method for determining the influencing factors of rock resistivity provided by an embodiment of the present application;

[0046] Figure 3 It is a flowchart of another method for determining the influencing factors of rock resistivity provided by an embodiment of the present application;

[0047] Figure 4 It is a schematic structural diagram of a device for determining the influencing factors of rock resistivity provided by an embodiment of the present application;

[0048] Figure 5 It is a schematic structural diagram of an acquisition module provided by an embodiment of the present application;

[0049] Figure 6 It is a schematic structural diagram of a first determination module provided by an embodiment of the present application;

[0050] Figure 7 It is a schematic structural diagram of another device for determining the influencing factors of rock resistivity provided by an embodiment of the present application;

[0051] Figure 8 It is a schematic structural diagram of a terminal provided by an embodiment of the present application. Detailed implementation manners

[0052] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the following will further describe the embodiments of the present application in detail with reference to the accompanying drawings.

[0053] Before explaining in detail the method for determining the influencing factors of rock resistivity provided by the embodiments of the present application, an application scenario and an implementation environment provided by the embodiments of the present application will be explained first.

[0054] First, the implementation environment provided by the embodiments of the present application will be explained in detail.

[0055] Volcanic rocks belong to the extrusive rock class of igneous rocks. Igneous rock reservoirs exhibit characteristics of low density, low resistivity, and high acoustic time difference logging responses. Due to the strong heterogeneity of igneous rock reservoirs, complex geological structures, the presence of conductive minerals and clay minerals with additional conductivity, and the influence of formation water geological factors, it is difficult to determine the main controlling factors affecting the rock resistivity, and therefore, it is impossible to determine the main reasons for its low resistivity. To further study the transformation of igneous rock reservoirs, well logging interpretation, and the next well location deployment, it is necessary to determine the main controlling factors affecting the rock resistivity. However, currently, only the influencing factors affecting the rock resistivity can be determined, and it is impossible to quickly, efficiently, and accurately determine the main controlling factors affecting the rock resistivity, nor can the influence magnitudes of various influencing factors be accurately judged.

[0056] Based on such an application scenario, the embodiments of the present application provide a method for determining the influencing factors of rock resistivity that can improve the accuracy of determining the main controlling factors.

[0057] Next, an implementation environment provided by an embodiment of the present application will be explained.

[0058] Figure 1 It is a schematic diagram of an implementation environment provided by an embodiment of the present application. This implementation environment includes a terminal 101 and a server 102, and the terminal 101 can be communicatively connected to the server 102 in a wired or wireless manner.

[0059] As an example, the terminal 101 can be any electronic product that can perform human-computer interaction with a user. This electronic product can provide one or more interaction devices such as a keyboard, a touchpad, a touch screen, a remote control, a voice interaction device, or a handwriting device. The terminal 101 can be a personal computer, a mobile phone, a smart phone, a personal digital assistant, a wearable device, a handheld computer PPC (Pocket PC), a tablet computer, a smart vehicle console, a smart TV, a smart speaker, etc.

[0060] The server 102 can be a single server, a server cluster composed of multiple servers, or a cloud computing service center.

[0061] Those skilled in the art should understand that the above-mentioned terminal 101 and server 102 are only examples. Other existing or future possible terminals or servers that can be applied to the present application should also be included within the protection scope of the present application and are hereby incorporated herein by reference.

[0062] After introducing the application scenario and implementation environment of the embodiment of the present application, next, a method for determining the influencing factors of rock resistivity provided by the embodiment of the present application will be introduced in detail with reference to the accompanying drawings.

[0063] Figure 2 It is a flowchart of a method for determining the influencing factors of rock resistivity provided by an embodiment of the present application. This method for determining the influencing factors of rock resistivity can include the following steps:

[0064] Step 201: When receiving an influencing factor determination instruction, obtain the conductive mineral content, clay mineral content, saturation, and resistivity of at least three rock samples in a target production well. The well depth of any one of the at least three rock samples in the target production well is different from the well depths of the other rock samples among the at least three rock samples.

[0065] Step 202: Determine the weight parameters corresponding to the influencing factors that affect the rock resistivity in the target production well according to the conductive mineral content, clay mineral content, saturation, and resistivity of the at least three rock samples. The influencing factors of the rock resistivity include conductive minerals, clay minerals, and formation water.

[0066] Step 203: Determine the main controlling factor affecting the rock resistivity in the target production well as the influencing factor with the smallest weight parameter.

[0067] In the embodiment of the present application, by means of the weight parameters corresponding to the conductive mineral content, clay mineral content, and saturation, the main controlling factor of the rock resistivity is determined. Since all factors affecting the rock resistivity are fully considered, the integrity and comprehensiveness of determining the main controlling factor affecting the rock resistivity are improved. At the same time, since there is no need for manual acquisition of determination parameters and no manual calculation during the process of determining the main controlling factor, the accuracy and efficiency of determining the main controlling factor are improved.

[0068] In some embodiments, obtaining the conductive mineral content, clay mineral content, saturation, and resistivity of at least three rock samples in the target production well includes:

[0069] Performing X-ray diffraction analysis on the at least three rock samples by means of an X-ray diffraction device to obtain the conductive mineral content and clay mineral content of the at least three rock samples;

[0070] Obtaining the formation water resistivity, rock porosity, and formation resistivity of the target production well, as well as the petrophysical parameters and resistivity of the at least three rock samples from a storage file;

[0071] Determining the saturation of the at least three rock samples according to the formation water resistivity, rock porosity, and formation resistivity of the target production well, and the petrophysical parameters of the at least three rock samples by means of Archie's formula.

[0072] In some embodiments, determining the weight parameters corresponding to the respective influencing factors affecting the rock resistivity in the target production well according to the conductive mineral content, clay mineral content, saturation, and resistivity of the at least three rock samples includes:

[0073] Determining the relationship between the resistivity of each rock sample in the at least three rock samples and the corresponding clay mineral content;

[0074] When the relationship between the resistivity of each rock sample and the corresponding clay mineral content is positively correlated, determine that the clay mineral is not an influencing factor affecting the rock resistivity in the target production well, and process the conductive mineral content, clay mineral content, saturation, and resistivity of any two rock samples in the at least three rock samples respectively through a main controlling factor analysis model to obtain the weight parameter corresponding to the formation water and the weight parameter corresponding to the conductive mineral in the target production well;

[0075] When the relationship between the resistivity of each rock sample and the corresponding clay mineral content is negatively correlated, the conductive mineral content, clay mineral content, saturation, and resistivity of each rock sample among the at least three rock samples are respectively processed by the master factor analysis model to obtain the weight parameter corresponding to the formation water, the weight parameter corresponding to the conductive mineral, and the weight parameter corresponding to the clay mineral in the target production well.

[0076] In some embodiments, the master factor analysis model is the following model:

[0077]

[0078] Wherein, R is the resistivity of any one rock sample, a, b, n, m are the petrophysical parameters of any one rock sample, W 导 is the conductive mineral content of any one rock sample, W 黏 is the clay mineral content of any one rock sample, R w is the formation water resistivity of the target production well, Φ is the rock porosity of the target production well, R t is the formation resistivity of the target production well, x is the weight parameter corresponding to the formation water, y is the weight parameter corresponding to the conductive mineral, and z is the weight parameter corresponding to the clay mineral.

[0079] In some embodiments, after determining the influencing factor with the smallest weight parameter as the master factor affecting the rock resistivity in the target production well, it further includes:

[0080] Prompt the master factor affecting the rock resistivity in the target production well through a first prompt message.

[0081] All of the above optional technical solutions can be combined arbitrarily to form optional embodiments of the present application, and the embodiments of the present application will not be elaborated one by one herein.

[0082] Figure 3 It is a flowchart of a method for determining influencing factors of rock resistivity provided by an embodiment of the present application. In this embodiment, an example is given where the method for determining influencing factors of rock resistivity is applied to a terminal. The method for determining influencing factors of rock resistivity may include the following steps:

[0083] Step 301: The terminal receives an influencing factor determination instruction.

[0084] Since when further geological exploration is required, it is necessary to determine the master factor affecting the rock resistivity. At this time, the terminal may receive an influencing factor determination instruction.

[0085] It should be noted that the influencing factor determination instruction can be triggered when a staff member operates on the terminal through a specified operation, and the specified operation can be a click operation, a swipe operation, a voice operation, etc.

[0086] Step 302: When the terminal receives the influencing factor determination instruction, it obtains the conductive mineral content, clay mineral content, saturation, and resistivity of at least three rock samples in the target production well.

[0087] It should be noted that the well depth of any one of the at least three rock samples in the target production well is different from the well depths of the other rock samples among the at least three rock samples. The at least three rock samples are obtained by mining from different well depths of the target production well in advance.

[0088] In an implementation environment, the target production well is the igneous rock well YT1 well. The staff can obtain three rock samples from the YT1 well in advance. The first rock sample is obtained by mining at a well depth of 5761.23 meters, the second rock sample is obtained by mining at a well depth of 5762.98 meters, and the third rock sample is obtained by mining at a well depth of 5768.27 meters.

[0089] In another implementation environment, the target production well is the igneous rock well TF2 well. The staff can obtain three rock samples from the TF2 well in advance. The first rock sample is obtained by mining at a well depth of 5262.27 meters, the second rock sample is obtained by mining at a well depth of 5262.47 meters, and the third rock sample is obtained by mining at a well depth of 5263.68 meters.

[0090] As an example, the operation of the terminal to obtain the conductive mineral content, clay mineral content, saturation, and resistivity of at least three rock samples in the target production well at least includes: performing X-ray diffraction analysis on the at least three rock samples through an X-ray diffraction device to obtain the conductive mineral content and clay mineral content of the at least three rock samples; obtaining the formation water resistivity, rock porosity, and formation resistivity of the target production well, as well as the petrophysical parameters and resistivity of the at least three rock samples from the storage file; and determining the saturation of the at least three rock samples through the Archie formula according to the formation water resistivity, rock porosity, and formation resistivity of the target production well, as well as the petrophysical parameters of the at least three rock samples.

[0091] After obtaining at least three rock samples, the staff can conduct petrophysical parameter experiments on the at least three rock samples to obtain experimental data, and store the obtained experimental data in the storage file in the terminal or the server through a specified operation. When the terminal needs to obtain relevant data of the target production well, it can obtain the experimental data from the local storage file or the server storage file. The experimental data includes the petrophysical parameters of the at least three rock samples, so that the terminal can obtain the petrophysical parameters of the at least three rock samples.

[0092] It should be noted that the petrophysical parameters can include lithology coefficients a and b, and cementation indices m and n. Among them, a is a proportionality coefficient related to lithology, and its value range is 0.6 - 1.5; b is a coefficient related to lithology; m is the cementation coefficient, which varies with the degree of rock cementation, and its value range is 1.5 - 3; n is the saturation index.

[0093] After well logging, a well logging interpretation chart is usually obtained. The well logging interpretation chart includes various relevant information of the target production well. For example, the formation water resistivity, rock porosity, formation resistivity (i.e., the resistivity of the rock when it is partially saturated with formation water), and the resistivity of rocks at different well depths of the target production well. After obtaining the well logging interpretation chart, it is usually stored in a storage file in the terminal or server. When the terminal needs to obtain the relevant data of the target production well, it can also obtain the well logging interpretation chart from the local storage file or the server storage file, and obtain the formation water resistivity, rock porosity, formation resistivity of the target production well, and the resistivity corresponding to at least three rock samples from the well logging interpretation chart.

[0094] In an implementation environment, for Well YT1, the terminal uses an X-ray diffraction device to perform X-ray diffraction analysis on three rock samples in Well YT1, and it is obtained that the rock in Well YT1 contains medium-conductive minerals. The medium-conductive mineral is titanite, and the content of titanite is 6.4% - 24.5%, and it does not contain clay minerals. Among them, the content of conductive minerals in the first rock sample is 19.4%, the content of conductive minerals in the second rock sample is 12.5%, and the content of conductive minerals in the third rock sample is 24.5%. Then, from the well logging interpretation chart, it can be obtained that the resistivity of the first rock sample is 30.73 ohm * m, the resistivity of the second rock sample is 40.03 ohm * m, and the resistivity of the third rock sample is 21.29 ohm * m.

[0095] In another implementation environment, for Well TF2, the terminal uses an X-ray diffractometer to perform X-ray diffraction analysis on three rock samples in Well TF2, and obtains that the rock in Well TF2 contains medium-conductive minerals, which are anatase. The anatase content is between 0.2% and 3%, and Well TF2 may produce formation water and contain clay mineral chlorite. Among them, the conductive mineral content in the first rock sample is 2.1%, and the clay mineral content is 34.4%. The conductive mineral content in the second rock sample is 0.2%, and the clay mineral content is 45.8%. The conductive mineral content in the third rock sample is 0.5%, and the clay mineral content is 19.8%. Subsequently, from the well logging interpretation chart, it can be obtained that the resistivity of the first rock sample is 9.78 ohm·m, the resistivity of the second rock sample is 9.56 ohm·m, and the resistivity of the third rock sample is 12.33 ohm·m.

[0096] In one embodiment, the Archie formula is as follows.

[0097]

[0098] It should be noted that in the above Archie formula (1), S w is the saturation of any rock sample, a, b, n, m are the petrophysical parameters of any rock sample, R w is the resistivity of the formation water of the target production well, Φ is the rock porosity of the target production well, and R t is the formation resistivity of the target production well.

[0099] In one implementation environment, for Well YT1, the terminal obtains the formation water resistivity, rock porosity, and formation resistivity of three rock samples, as well as the petrophysical parameters of these three rock samples. The terminal uses the Archie formula to determine the saturation of the three rock samples respectively, and obtains that the saturation of the first rock sample is 10.2%, the saturation of the second rock sample is 12.3%, and the saturation of the third rock sample is 20.2%.

[0100] In another implementation environment, for Well TF2, the terminal also obtains the formation water resistivity, rock porosity, and formation resistivity of three rock samples, as well as the petrophysical parameters of these three rock samples. The terminal uses the Archie formula to determine the saturation of the three rock samples respectively, and obtains that the saturation of the first rock sample is 65.3%, the saturation of the second rock sample is 66.1%, and the saturation of the third rock sample is 69.8%.

[0101] Step 303: The terminal determines the weight parameters corresponding to the influencing factors that affect the rock resistivity in the target production well according to the conductive mineral content, clay mineral content, saturation, and resistivity of at least three rock samples.

[0102] It should be noted that the influencing factors of rock resistivity at least include conductive minerals, clay minerals and formation water.

[0103] As an example, the operation of the terminal to determine the weight parameters corresponding to the influencing factors of the rock resistivity in the target production well according to the conductive mineral content, clay mineral content, saturation and resistivity of at least three rock samples at least includes: determining the relationship between the resistivity of each rock sample in at least three rock samples and the corresponding clay mineral content; when the relationship between the resistivity of each rock sample and the corresponding clay mineral content is positively correlated, determining that the clay mineral is not an influencing factor for the rock resistivity in the target production well, and processing the conductive mineral content, clay mineral content, saturation and resistivity of any two rock samples in at least three rock samples through the main control factor analysis model respectively to obtain the weight parameter corresponding to the formation water and the weight parameter corresponding to the conductive mineral in the target production well; when the relationship between the resistivity of each rock sample and the corresponding clay mineral content is negatively correlated, processing the conductive mineral content, clay mineral content, saturation and resistivity of each rock sample in at least three rock samples through the main control factor analysis model respectively to obtain the weight parameter corresponding to the formation water, the weight parameter corresponding to the conductive mineral and the weight parameter corresponding to the clay mineral in the target production well.

[0104] Since sometimes clay minerals may affect the resistivity of rocks and sometimes do not, the terminal can first determine the relationship between the resistivity of each rock sample in at least three rock samples and the corresponding clay mineral content. That is, the terminal determines whether the resistivity of the rock sample decreases as the clay mineral content increases according to the resistivity of at least three rock samples. When the resistivity of the rock sample decreases as the clay mineral content increases, it is determined that the relationship between the resistivity of each rock sample in the target production well and the corresponding clay mineral content is negatively correlated. When the resistivity of the rock sample does not decrease as the clay mineral content increases, it is determined that the relationship between the resistivity of each rock sample in the target production well and the corresponding clay mineral content is positively correlated.

[0105] It should be noted that the situation where the resistivity of the rock sample does not decrease as the clay mineral content increases includes that the at least three rock samples do not contain clay mineral content.

[0106] In some embodiments, since when the relationship between the resistivity of the rock sample and the corresponding clay mineral content is positively correlated, it indicates that the clay mineral content does not affect the resistivity of the rock, it can be determined that the clay mineral content does not participate in the subsequent calculation, and the terminal can select any two rock samples from at least three rock samples to determine the weight parameters corresponding to the influencing factors of the rock resistivity in the target production well.

[0107] As an example, the main control factor analysis model is the following model.

[0108]

[0109] It should be noted that in the above main control factor analysis model (2), R is the resistivity of any rock sample, a, b, n, and m are the petrophysical parameters of any rock sample, and W 导 is the content of conductive minerals in any rock sample, and W 黏 is the content of clay minerals in any rock sample, R w is the formation water resistivity of the target production well, Φ is the rock porosity of the target production well, and R t is the formation resistivity of the target production well, x is the weight parameter corresponding to the formation water, y is the weight parameter corresponding to the conductive minerals, and z is the weight parameter corresponding to the clay minerals.

[0110] In some embodiments, when the relationship between the resistivity of the rock sample and the corresponding clay mineral content is positively correlated, the terminal can select any two rock samples from at least three rock samples, and process the conductive mineral content, clay mineral content, saturation, and resistivity of any two rock samples through the main control factor analysis model respectively, so as to obtain two analysis models containing the unknown solutions x and y. Through the two analysis models, the weight parameter x corresponding to the formation water and the weight parameter y corresponding to the conductive minerals can be determined.

[0111] It should be noted that when the relationship between the resistivity of the rock sample and the corresponding clay mineral content is positively correlated, the terminal may not select the clay mineral content to participate in the calculation, or may also select the clay mineral to participate in the calculation. And when selecting the clay mineral content to participate in the calculation, the weight parameter corresponding to the clay mineral in the main control factor analysis model is set to 0.

[0112] In an implementation environment, when the target production well is Well YT1, the terminal can determine that the clay mineral content is positively correlated with the resistivity. Therefore, it is determined that the clay mineral does not affect the rock resistivity. Therefore, the clay mineral content does not participate in the subsequent calculation, and the conductive mineral content, saturation, and resistivity of any two rock samples are processed through the main control factor analysis model respectively, so as to obtain the weight parameter x = 0.00079 corresponding to the formation water and the weight parameter y = 0.00126 corresponding to the conductive minerals.

[0113] In some embodiments, when the clay mineral content is negatively correlated with the resistivity, the terminal can process the conductive mineral content, clay mineral content, saturation, and resistivity of any three rock samples among at least three rock samples through a principal factor analysis model, so as to obtain three analysis models containing unknown solutions x, y, and z. Through the three analysis models, the weight parameter x corresponding to formation water, the weight parameter y corresponding to conductive minerals, and the weight parameter z corresponding to clay minerals can be determined.

[0114] In an implementation environment, when the target production well is Well TF2, the terminal can determine that the clay mineral content is negatively correlated with the resistivity. Therefore, the terminal processes the conductive mineral content, clay mineral content, saturation, and resistivity of any three rock samples through a principal factor analysis model respectively, so as to obtain the weight parameter x = 0.0007 corresponding to formation water, the weight parameter y = 0.016 corresponding to conductive minerals, and the weight parameter z = 0.0012 corresponding to clay minerals.

[0115] Step 304: The terminal determines the influencing factor with the smallest weight parameter as the principal factor affecting the rock resistivity in the target production well.

[0116] Since when the weight parameter is small, it indicates that the influencing factor corresponding to this weight parameter has the greatest influence on the rock resistivity in the target production well. Therefore, the terminal can determine the influencing factor with the smallest weight parameter as the principal factor affecting the rock resistivity in the target production well.

[0117] It should be noted that the principal factor refers to the factor that has the greatest influence on the rock resistivity in the target production well.

[0118] In an implementation environment, when the target production well is Well YT1, since the value of the weight parameter x corresponding to formation water is the smallest, it is determined that the principal factor affecting the rock resistivity in Well YT1, the target production well, is formation water.

[0119] In another implementation environment, when the target production well is Well TF2, since the value of the weight parameter x corresponding to formation water is the smallest, it is determined that the principal factor affecting the rock resistivity in Well TF2, the target production well, is formation water.

[0120] In some embodiments, after the terminal determines the principal factor, it can prompt the principal factor of the rock resistivity in the target production well through a first prompt message.

[0121] In some embodiments, after the terminal determines the weight parameters corresponding to the influencing factors of the rock resistivity in the target production well, it can also sort the influencing factors in ascending order of the weight parameters and prompt the sorted influencing factors through a second prompt message.

[0122] It should be noted that both the first prompt message and the second prompt message can be information in the form of text, image, voice, and / or video, etc.

[0123] In the embodiments of the present application, the terminal can determine the main controlling factors of rock resistivity through the weight parameters corresponding to the conductive mineral content, clay mineral content, and saturation. Since all factors affecting rock resistivity are fully considered, the integrity and comprehensiveness of determining the main controlling factors of rock resistivity are improved. At the same time, in the process of determining the main controlling factors, there is no need for manual acquisition of determination parameters by workers, nor manual calculation, which improves the accuracy and efficiency of determining the main controlling factors. In addition, since the terminal can not only effectively judge the main controlling factors affecting rock resistivity, but also determine the influence magnitude of each influencing factor through the weight parameters of each influencing factor, it points the way for the next geological exploration.

[0124] Figure 4 FIG. 7 is a schematic structural diagram of a device for determining influencing factors of rock resistivity provided by an embodiment of the present application. The device for determining influencing factors of rock resistivity can be implemented by software, hardware, or a combination of both. The device for determining influencing factors of rock resistivity may include: an acquisition module 401, a first determination module 402, and a second determination module 403.

[0125] The acquisition module 401 is configured to, when receiving an influencing factor determination instruction, acquire the conductive mineral content, clay mineral content, saturation, and resistivity of at least three rock samples in a target production well, and the well depth of any one of the at least three rock samples in the target production well is different from the well depths of other rock samples in the at least three rock samples;

[0126] The first determination module 402 is configured to determine the weight parameters corresponding to the respective influencing factors affecting the rock resistivity in the target production well according to the conductive mineral content, clay mineral content, saturation, and resistivity of the at least three rock samples. The influencing factors of the rock resistivity include conductive minerals, clay minerals, and formation water;

[0127] The second determination module 403 is configured to determine the influencing factor with the smallest weight parameter as the main controlling factor affecting the rock resistivity in the target production well.

[0128] In some embodiments, referring to Figure 5 , the acquisition module 401 includes:

[0129] An analysis sub-module 4011 is configured to perform X-ray diffraction analysis on the at least three rock samples through an X-ray diffraction device to obtain the conductive mineral content and clay mineral content of the at least three rock samples;

[0130] The first acquisition sub-module 4012 is configured to acquire the formation water resistivity, rock porosity, and formation resistivity of the target production well from a storage file, as well as the petrophysical parameters and resistivity of the at least three rock samples.

[0131] The first determination sub-module 4013 is configured to determine the saturation of the at least three rock samples according to the formation water resistivity, rock porosity, and formation resistivity of the target production well, and the petrophysical parameters of the at least three rock samples, by using Archie's formula.

[0132] In some embodiments, referring to Figure 6 , the first determination module 402 includes:

[0133] The second determination sub-module 4021 is configured to determine the relationship between the resistivity of each rock sample among the at least three rock samples and the corresponding clay mineral content.

[0134] The first processing sub-module 4022 is configured to, when the relationship between the resistivity of each rock sample and the corresponding clay mineral content is positively correlated, determine that the clay mineral is not a factor affecting the resistivity of the rock in the target production well, and process the conductive mineral content, clay mineral content, saturation, and resistivity of any two rock samples among the at least three rock samples respectively through a main control factor analysis model, to obtain the weight parameter corresponding to the formation water and the weight parameter corresponding to the conductive mineral in the target production well.

[0135] The second processing sub-module 4023 is configured to, when the relationship between the resistivity of each rock sample and the corresponding clay mineral content is negatively correlated, process the conductive mineral content, clay mineral content, saturation, and resistivity of each rock sample among the at least three rock samples respectively through the main control factor analysis model, to obtain the weight parameter corresponding to the formation water, the weight parameter corresponding to the conductive mineral, and the weight parameter corresponding to the clay mineral in the target production well.

[0136] In some embodiments, the main control factor analysis model is the following model:

[0137]

[0138] wherein, R is the resistivity of any one of the rock samples, a, b, n, and m are the petrophysical parameters of any one of the rock samples, W 导 is the conductive mineral content of any one of the rock samples, W 黏 is the clay mineral content of any one of the rock samples, R w is the formation water resistivity of the target production well, Φ is the rock porosity of the target production well, R tis the formation resistivity of the target production well, where x is the weight parameter corresponding to the formation water, y is the weight parameter corresponding to the conductive minerals, and z is the weight parameter corresponding to the clay minerals.

[0139] In some embodiments, referring to Figure 7 , the device further includes:

[0140] A prompt module 404, configured to prompt the main controlling factors of the rock resistivity in the target production well through a first prompt message.

[0141] In the embodiments of the present application, the terminal can determine the main controlling factors of the rock resistivity through the weight parameters corresponding to the content of conductive minerals, the content of clay minerals, and the saturation. Since all factors affecting the rock resistivity are fully considered, the integrity and comprehensiveness of determining the main controlling factors of the rock resistivity are improved. At the same time, since there is no need for manual acquisition of determination parameters and manual calculation during the process of determining the main controlling factors, the accuracy and efficiency of determining the main controlling factors are improved. In addition, since the terminal can not only effectively judge the main controlling factors of the rock resistivity, but also determine the influence magnitude of each influencing factor through the weight parameters of each influencing factor, it points the way for the next geological exploration.

[0142] It should be noted that when the device for determining the influencing factors of rock resistivity provided in the above embodiments determines the influencing factors of rock resistivity, only the above-mentioned division of each functional module is used for illustration. In practical applications, the above functions can be allocated to different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device for determining the influencing factors of rock resistivity provided in the above embodiments and the embodiments of the method for determining the influencing factors of rock resistivity belong to the same concept, and the specific implementation process is detailed in the method embodiments and will not be repeated here.

[0143] Figure 8 shows a structural block diagram of a terminal 800 provided by an exemplary embodiment of the present application. The terminal 800 can be: a smart phone, a tablet computer, a notebook computer, or a desktop computer. The terminal 800 may also be referred to by other names such as a user equipment, a portable terminal, a laptop terminal, a desktop terminal, etc.

[0144] Generally, the terminal 800 includes: a processor 801 and a memory 802.

[0145] The processor 801 may include one or more processing cores, such as a quad-core processor, an octa-core processor, etc. The processor 801 may be implemented in at least one of the following hardware forms: DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 801 may also include a main processor and a coprocessor. The main processor is used to process data in the wake state and is also called the CPU (Central Processing Unit); the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor 801 may be integrated with a GPU (Graphics Processing Unit), and the GPU is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 801 may further include an AI (Artificial Intelligence) processor, which is used to process computational operations related to machine learning.

[0146] The memory 802 may include one or more computer-readable storage media, and the computer-readable storage media may be non-transitory. The memory 802 may further include high-speed random access memory and non-volatile memory, such as one or more disk storage devices and flash storage devices. In some embodiments, the non-transitory computer-readable storage media in the memory 802 is used to store at least one instruction, and the at least one instruction is used to be executed by the processor 801 to implement the method for determining the influencing factors of rock resistivity provided in the method embodiments of the present application.

[0147] In some embodiments, the terminal 800 may further optionally include: a peripheral device interface 803 and at least one peripheral device. The processor 801, the memory 802, and the peripheral device interface 803 may be connected through a bus or signal lines. Each peripheral device may be connected to the peripheral device interface 803 through a bus, signal lines, or a circuit board. Specifically, the peripheral devices include at least one of the following: a radio frequency circuit 804, a display screen 805, a camera assembly 806, an audio circuit 807, a positioning component 808, and a power supply 809.

[0148] The peripheral device interface 803 can be used to connect at least one I / O (Input / Output) related peripheral device to the processor 801 and the memory 802. In some embodiments, the processor 801, the memory 802, and the peripheral device interface 803 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 801, the memory 802, and the peripheral device interface 803 can be implemented on a separate chip or circuit board, and this embodiment does not limit this.

[0149] The radio frequency circuit 804 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 804 communicates with the communication network and other communication devices through electromagnetic signals. The radio frequency circuit 804 converts an electrical signal into an electromagnetic signal for transmission, or converts the received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 804 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a subscriber identity module card, and so on. The radio frequency circuit 804 can communicate with other terminals through at least one wireless communication protocol. The wireless communication protocol includes but is not limited to: metropolitan area network, each generation of mobile communication network (2G, 3G, 4G, and 5G), wireless local area network, and / or WiFi (Wireless Fidelity) network. In some embodiments, the radio frequency circuit 804 may further include a circuit related to NFC (Near Field Communication), and this application does not limit this.

[0150] The display screen 805 is used to display the UI (User Interface). The UI may include graphics, text, icons, videos, and any combination thereof. When the display screen 805 is a touch display screen, the display screen 805 also has the ability to collect touch signals on or above the surface of the display screen 805. The touch signals can be input to the processor 801 as control signals for processing. At this time, the display screen 805 can also be used to provide virtual buttons and / or virtual keyboards, also known as soft buttons and / or soft keyboards. In some embodiments, there may be one display screen 805, which is provided on the front panel of the terminal 800; in other embodiments, there may be at least two display screens 805, which are respectively provided on different surfaces of the terminal 800 or are in a folding design; in other embodiments, the display screen 805 may be a flexible display screen, which is provided on the curved surface or folding surface of the terminal 800. Even, the display screen 805 can also be set to an irregular non-rectangular shape, that is, a special-shaped screen. The display screen 805 can be prepared from materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

[0151] The camera module 806 is used to capture images or videos. Optionally, the camera module 806 includes a front camera and a rear camera. Generally, the front camera is provided on the front panel of the terminal, and the rear camera is provided on the back of the terminal. In some embodiments, there are at least two rear cameras, which are any one of a main camera, a depth-of-field camera, a wide-angle camera, and a telephoto camera, so as to implement the function of background blurring by fusing the main camera and the depth-of-field camera, the function of panoramic shooting by fusing the main camera and the wide-angle camera, and the VR (Virtual Reality) shooting function or other fusion shooting functions. In some embodiments, the camera module 806 may further include a flash. The flash can be a single-color temperature flash or a two-color temperature flash. The two-color temperature flash refers to the combination of a warm light flash and a cold light flash, which can be used for light compensation under different color temperatures.

[0152] The audio circuit 807 may include a microphone and a speaker. The microphone is used to collect sound waves of the user and the environment, and convert the sound waves into electrical signals for input to the processor 801 for processing, or input to the radio frequency circuit 804 to implement voice communication. For the purpose of stereo collection or noise reduction, there may be multiple microphones, which are respectively arranged at different parts of the terminal 800. The microphone may also be an array microphone or an omnidirectional collection microphone. The speaker is used to convert the electrical signal from the processor 801 or the radio frequency circuit 804 into sound waves. The speaker may be a traditional thin film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can not only convert the electrical signal into sound waves audible to humans, but also convert the electrical signal into sound waves inaudible to humans for uses such as ranging. In some embodiments, the audio circuit 807 may further include a headphone jack.

[0153] The positioning component 808 is used to locate the current geographical location of the terminal 800 to implement navigation or LBS (Location Based Service). The positioning component 808 may be a positioning component based on the GPS (Global Positioning System) of the United States, the Beidou system of China, the GLONASS system of Russia, or the Galileo system of the European Union.

[0154] The power supply 809 is used to supply power to each component in the terminal 800. The power supply 809 may be alternating current, direct current, a disposable battery, or a rechargeable battery. When the power supply 809 includes a rechargeable battery, the rechargeable battery may support wired charging or wireless charging. The rechargeable battery may also be used to support fast charging technology.

[0155] In some embodiments, the terminal 800 further includes one or more sensors 810. The one or more sensors 810 include but are not limited to: an acceleration sensor 811, a gyroscope sensor 812, a pressure sensor 813, a fingerprint sensor 814, an optical sensor 815, and a proximity sensor 816.

[0156] The acceleration sensor 811 can detect the magnitudes of accelerations on the three coordinate axes of the coordinate system established with the terminal 800. For example, the acceleration sensor 811 can be used to detect the components of the gravitational acceleration on the three coordinate axes. The processor 801 can control the display screen 805 to display the user interface in a landscape view or a portrait view according to the gravitational acceleration signal collected by the acceleration sensor 811. The acceleration sensor 811 can also be used for collecting game or user's motion data.

[0157] The gyroscope sensor 812 can detect the body direction and rotation angle of the terminal 800. The gyroscope sensor 812 can cooperate with the acceleration sensor 811 to collect the 3D actions of the user on the terminal 800. Based on the data collected by the gyroscope sensor 812, the processor 801 can implement the following functions: motion sensing (such as changing the UI according to the user's tilting operation), image stabilization during shooting, game control, and inertial navigation.

[0158] The pressure sensor 813 can be disposed on the side frame of the terminal 800 and / or under the display screen 805. When the pressure sensor 813 is disposed on the side frame of the terminal 800, it can detect the holding signal of the user on the terminal 800, and the processor 801 can identify the left or right hand or perform a quick operation according to the holding signal collected by the pressure sensor 813. When the pressure sensor 813 is disposed under the display screen 805, the processor 801 can control the operable controls on the UI interface according to the pressure operation of the user on the display screen 805. The operable controls include at least one of a button control, a scroll bar control, an icon control, and a menu control.

[0159] The fingerprint sensor 814 is used to collect the fingerprint of the user. The processor 801 can identify the user's identity according to the fingerprint collected by the fingerprint sensor 814, or the fingerprint sensor 814 can identify the user's identity according to the collected fingerprint. When the identity of the user is identified as a trusted identity, the processor 801 authorizes the user to perform relevant sensitive operations, and the sensitive operations include unlocking the screen, viewing encrypted information, downloading software, making payments, and changing settings, etc. The fingerprint sensor 814 can be disposed on the front, back, or side of the terminal 800. When there is a physical button or a manufacturer's logo on the terminal 800, the fingerprint sensor 814 can be integrated with the physical button or the manufacturer's logo.

[0160] The optical sensor 815 is used to collect the ambient light intensity. In one embodiment, the processor 801 can control the display brightness of the display screen 805 according to the ambient light intensity collected by the optical sensor 815. Specifically, when the ambient light intensity is high, the display brightness of the display screen 805 is increased; when the ambient light intensity is low, the display brightness of the display screen 805 is decreased. In another embodiment, the processor 801 can also dynamically adjust the shooting parameters of the camera module 806 according to the ambient light intensity collected by the optical sensor 815.

[0161] The proximity sensor 816, also known as a distance sensor, is typically disposed on the front panel of the terminal 800. The proximity sensor 816 is used to collect the distance between the user and the front of the terminal 800. In one embodiment, when the proximity sensor 816 detects that the distance between the user and the front of the terminal 800 is gradually decreasing, the processor 801 controls the display screen 805 to switch from the lit state to the off state; when the proximity sensor 816 detects that the distance between the user and the front of the terminal 800 is gradually increasing, the processor 801 controls the display screen 805 to switch from the off state to the lit state.

[0162] Those skilled in the art can understand that Figure 8 the structure shown in does not constitute a limitation on the terminal 800, and may include more or fewer components than shown, or combine certain components, or adopt a different component arrangement.

[0163] The embodiments of the present application also provide a non-transitory computer-readable storage medium. When the instructions in the storage medium are executed by the processor of the terminal, the terminal can execute the method for determining the influencing factors of the rock resistivity provided in the above embodiments.

[0164] The embodiments of the present application also provide a computer program product containing instructions. When it runs on the terminal, the terminal executes the method for determining the influencing factors of the rock resistivity provided in the above embodiments.

[0165] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above embodiments can be completed by hardware, or can be completed by a program instructing related hardware. The program can be stored in a computer-readable storage medium. The above-mentioned storage medium can be a read-only memory, a magnetic disk or an optical disc, etc.

[0166] The above are only the preferred embodiments of the embodiments of the present application, and are not intended to limit the embodiments of the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the embodiments of the present application shall be included in the protection scope of the present application.

Claims

1. A method for determining influencing factors of rock resistivity, characterized in that, The method includes: When receiving an influencing factor determination instruction, obtaining the conductive mineral content, clay mineral content, saturation, and resistivity of at least three rock samples in a target production well, where the well depth of any one of the at least three rock samples in the target production well is different from the well depths of the other rock samples among the at least three rock samples; According to the conductive mineral content, clay mineral content, saturation, and resistivity of the at least three rock samples, determining the weight parameters corresponding to each influencing factor that affects the rock resistivity in the target production well, where the influencing factors of the rock resistivity include conductive minerals, clay minerals, and formation water; Determining the influencing factor with the smallest weight parameter as the main controlling factor that affects the rock resistivity in the target production well; The determining the weight parameters corresponding to each influencing factor that affects the rock resistivity in the target production well according to the conductive mineral content, clay mineral content, saturation, and resistivity of the at least three rock samples includes: Determining the relationship between the resistivity of each rock sample among the at least three rock samples and the corresponding clay mineral content; When the relationship between the resistivity of each rock sample and the corresponding clay mineral content is positively correlated, determining that the clay mineral is not an influencing factor that affects the rock resistivity in the target production well, and respectively processing the conductive mineral content, clay mineral content, saturation, and resistivity of any two rock samples among the at least three rock samples through a main controlling factor analysis model to obtain the weight parameter corresponding to the formation water and the weight parameter corresponding to the conductive mineral in the target production well; When the relationship between the resistivity of each rock sample and the corresponding clay mineral content is negatively correlated, respectively processing the conductive mineral content, clay mineral content, saturation, and resistivity of each rock sample among the at least three rock samples through the main controlling factor analysis model to obtain the weight parameter corresponding to the formation water, the weight parameter corresponding to the conductive mineral, and the weight parameter corresponding to the clay mineral in the target production well; The main controlling factor analysis model is the following model: Wherein, R is the resistivity of any one of the rock samples, a, b, n, and m are the petrophysical parameters of any one of the rock samples, and W 导 is the content of conductive minerals in any one of the rock samples, and W 黏 is the content of clay minerals in any one of the rock samples, R w is the formation water resistivity of the target production well, Φ is the rock porosity of the target production well, R t is the formation resistivity of the target production well, x is the weight parameter corresponding to the formation water, y is the weight parameter corresponding to the conductive minerals, and z is the weight parameter corresponding to the clay minerals.

2. The method according to claim 1, characterized in that The obtaining the conductive mineral content, clay mineral content, saturation, and resistivity of at least three rock samples in a target production well includes: Performing X-ray diffraction analysis on the at least three rock samples through an X-ray diffraction device to obtain the conductive mineral content and clay mineral content of the at least three rock samples; Obtaining the formation water resistivity, rock porosity, and formation resistivity of the target production well, as well as the petrophysical parameters and resistivity of the at least three rock samples from a storage file; According to the formation water resistivity, rock porosity, and formation resistivity of the target production well, as well as the petrophysical parameters of the at least three rock samples, determining the saturation of the at least three rock samples through Archie's formula; 3. The method according to claim 1, wherein After determining the influencing factor with the smallest weight parameter as the main controlling factor that affects the rock resistivity in the target production well, it further includes: Prompting the main controlling factor of the rock resistivity in the target production well through a first prompt message; 4. An apparatus for determining influencing factors of rock resistivity, characterized in that, The device includes: An acquisition module, configured to acquire the conductive mineral content, clay mineral content, saturation, and resistivity of at least three rock samples in a target production well when receiving an influencing factor determination instruction, wherein the well depth of any one of the at least three rock samples in the target production well is different from the well depths of other rock samples among the at least three rock samples; A first determination module, configured to determine the weight parameters corresponding to the influencing factors that affect the rock resistivity in the target production well according to the conductive mineral content, clay mineral content, saturation, and resistivity of the at least three rock samples, wherein the influencing factors of the rock resistivity include conductive minerals, clay minerals, and formation water; A second determination module, configured to determine the influencing factor with the smallest weight parameter as the main control factor that affects the rock resistivity in the target production well; The first determination module includes: A second determination sub-module, configured to determine the relationship between the resistivity of each rock sample among the at least three rock samples and the corresponding clay mineral content; A first processing sub-module, configured to, when the relationship between the resistivity of each rock sample and the corresponding clay mineral content is positively correlated, determine that the clay mineral is not an influencing factor that affects the rock resistivity in the target production well, and process the conductive mineral content, clay mineral content, saturation, and resistivity of any two rock samples among the at least three rock samples through a main control factor analysis model respectively, to obtain the weight parameter corresponding to the formation water and the weight parameter corresponding to the conductive mineral in the target production well; A second processing sub-module, configured to, when the relationship between the resistivity of each rock sample and the corresponding clay mineral content is negatively correlated, process the conductive mineral content, clay mineral content, saturation, and resistivity of each rock sample among the at least three rock samples through the main control factor analysis model respectively, to obtain the weight parameter corresponding to the formation water, the weight parameter corresponding to the conductive mineral, and the weight parameter corresponding to the clay mineral in the target production well; The main control factor analysis model is the following model: Among them, R is the resistivity of any one of the rock samples, a, b, n, and m are the petrophysical parameters of any one of the rock samples, and W 导 is the content of conductive minerals in any one of the rock samples, and W 黏 is the content of clay minerals in any one of the rock samples, R w is the formation water resistivity of the target production well, Φ is the rock porosity of the target production well, R t is the formation resistivity of the target production well, x is the weight parameter corresponding to the formation water, y is the weight parameter corresponding to the conductive minerals, and z is the weight parameter corresponding to the clay minerals.

5. The device according to claim 4, characterized in that, The acquisition module includes: An analysis sub-module, configured to perform X-ray diffraction analysis on the at least three rock samples through an X-ray diffraction device to obtain the conductive mineral content and clay mineral content of the at least three rock samples; A first acquisition sub-module, configured to acquire the formation water resistivity, rock porosity, and formation resistivity of the target production well, as well as the petrophysical parameters and resistivity of the at least three rock samples from a storage file; A first determination sub-module, configured to determine the saturation of the at least three rock samples according to the formation water resistivity, rock porosity, and formation resistivity of the target production well, and the petrophysical parameters of the at least three rock samples through Archie's formula; 6. The device according to claim 4, characterized in that The device further includes: A prompt module, configured to prompt the main control factor of the rock resistivity in the target production well through a first prompt message; 7. A computer-readable storage medium, characterized in that, Instructions are stored on the computer-readable storage medium, and when the instructions are executed by a processor, the steps of the method described in any one of claims 1 to 3 above are implemented.

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