A method for calculating porosity spectrum based on microresistivity imaging logging

Abstract

The present application provides a method for calculating porosity spectrum based on microresistivity imaging logging, comprising: obtaining the conductivity C of the ith electrode plate measured by microresistivity imaging logging; i ; Obtain the mud filtrate resistivity R according to the well site water analysis data mf ; Obtain porosity tortuosity T; According to the conductivity C i 、Mud filtrate resistivity R mf , porosity tortuosity T determines the porosity Φ corresponding to the i-th plate i ; According to the porosity Φ corresponding to the i-th plate i Determine the porosity spectrum corresponding to the statistical window length based on microresistivity imaging logging. The present invention provides a porosity spectrum calculation model with simpler parameters, which does not require conventional logging parameters and has wider applicability. Compared with the porosity spectrum interpreted by conventional logging, the method provided by the present invention can obtain a more detailed porosity spectrum interpretation using microresistivity imaging logging with higher resolution.

Description

Technical Field

[0001] The invention relates to the technical field of petroleum exploration reservoir evaluation, and in particular to a method for calculating a porosity spectrum based on microresistivity imaging logging. Background Art

[0002] In the petroleum industry, porosity is the most critical parameter for reservoir evaluation and reserve calculation. Due to the low detection resolution, the porosity interpreted by conventional logging is difficult to accurately characterize reservoirs with more complex pore structures. Compared with conventional logging, microresistivity imaging logging has a higher detection resolution, but the methods for calculating porosity based on microresistivity imaging logging are relatively few and complex (Akbar et al., 2000; Xie et al., 2015). At present, it is necessary to establish a more sophisticated porosity spectrum calculation method based on microresistivity imaging logging to meet the increasingly sophisticated exploration and development needs. Summary of the invention

[0003] The purpose of the present invention is to solve the defects of the above-mentioned prior art and provide a method for calculating the porosity spectrum based on microresistivity imaging logging.

[0004] A method for calculating porosity spectrum based on microresistivity imaging logging, comprising:

[0005] The conductivity C measured by the i-th plate obtained based on microresistivity imaging logging i ;

[0006] Obtain the resistivity R of the mud filtrate based on the well site water analysis data mf ;

[0007] Get the porosity tortuosity T;

[0008] According to the conductivity C i 、Mud filtrate resistivity R mf , porosity tortuosity T determines the porosity Φ corresponding to the i-th plate i ;

[0009] According to the porosity Φ corresponding to the i-th plate i Determine the porosity spectrum corresponding to the statistical window length of microresistivity imaging logging.

[0010] Furthermore, in the above-mentioned method for calculating the porosity spectrum based on microresistivity imaging logging, the conductivity C i 、Mud filtrate resistivity R mf , porosity tortuosity T determines the porosity Φ corresponding to the i-th plate i Including using the following formula to obtain the porosity Φ i

[0011] Φi =C i R mf T 2 .

[0012] Furthermore, in the above-mentioned method for calculating the porosity spectrum based on microresistivity imaging logging, the porosity spectrum is constructed based on a capillary physical model.

[0013] Furthermore, in the above-mentioned method for calculating the porosity spectrum based on microresistivity imaging logging, the conductivity C measured by the i-th plate obtained by microresistivity imaging logging is i include:

[0014] According to the capillary physical model, the resistance R of the pore fluid and the length L of the rock side per unit volume are determined. h ;

[0015] According to the resistance R of the pore fluid and the side length L of the rock h , determine the conductivity C based on single plate measurement of microresistivity imaging logging i .

[0016] Furthermore, in the above-mentioned method for calculating the porosity spectrum based on microresistivity imaging logging, the resistance R of the pore fluid and the side length L of the rock are calculated. h , determine the conductivity C based on single plate measurement of microresistivity imaging logging i Including obtaining the conductivity C according to the following formula i :

[0017]

[0018] Beneficial effects:

[0019] The method for calculating the porosity spectrum of microresistivity imaging logging provided by the present invention obtains the conductivity C i 、Mud filtrate resistivity R mf , the porosity tortuosity T can determine the porosity Φ corresponding to the i-th plate i , and according to the porosity Φ corresponding to the i-th plate i Finally, the corresponding porosity spectrum is determined. This method provides a porosity spectrum calculation model with simpler parameters, does not require conventional logging parameters, and has wider applicability. Compared with the porosity spectrum interpreted by conventional logging, the method provided by the present invention can obtain a more detailed porosity spectrum interpretation using microresistivity imaging logging with higher resolution. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a schematic diagram of the rock resistivity capillary physical model based on microresistivity imaging logging in this application;

[0021] Figure 2 It is the equivalent resistivity diagram of the capillary physical model;

[0022] Figure 3 This application is based on the imaging porosity spectrum of microresistivity imaging logging. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention is described clearly and completely below. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] Figure 1 This is a schematic diagram of the rock resistivity capillary physical model based on microresistivity imaging logging in this application. Figure 2 is the equivalent resistivity diagram of the capillary physical model; Figure 1 , Figure 2 As shown in the figure, based on the capillary physical model in unit volume, a single rock resistivity capillary physical model is constructed from the skeleton and pore throat parts. Assuming that the rock side length in unit volume is L h (The unit of pore throat radius is micrometer. In standard unit calculation, L can be eliminated. h ), the average pore throat radius of the rock is r, the tortuosity is T, and the throat length is L, then L = L h T. Referring to the international standard of pore throat radius, the unit of model length is micrometer.

[0025] The resistivity measured by the microresistivity imaging logging electrode can be regarded as the resistivity of the wellbore flushing zone. Assumptions: ① The fluid in the rock pores of the wellbore flushing zone is completely replaced by mud filtrate, without residual oil and gas. The resistivity of the mud filtrate is R mf ② The rock skeleton is not conductive, and there is no additional conductivity of mud. Based on the capillary physical model, the porosity spectrum is constructed.

[0026] According to the capillary physical model and Ohm's law, the resistance R of the pore fluid can be expressed as:

[0027]

[0028] The resistance of the wellbore rock can be regarded as the parallel connection of the pore throat fluid resistance and the skeleton resistance, which is converted into the conductivity C measured by a single electrode based on microresistivity imaging logging. i :

[0029]

[0030] From formula (2), we can see that the average pore throat radius r can be expressed as:

[0031]

[0032] According to the capillary physical model, the porosity can be expressed as:

[0033]

[0034] Substitute formula (3) into formula (4):

[0035] Φ=C i R mf L h L h T 2 (5)

[0036] In unit volume, L h It can be eliminated in the unit operation, and the porosity calculated based on the corresponding plate i of microresistivity imaging logging is recorded as Φ i :

[0037] Φ i =C i R mf T 2 (6)

[0038] This formula is a porosity expression constructed based on the imaging resistivity of microresistivity imaging logging. i is the porosity calculated by the i-th plate of microresistivity imaging logging; C i is the conductivity measured by the ith plate; R mf is the resistivity of mud filtrate, which can be obtained through well site water analysis data; T is the porosity tortuosity, which can be obtained through core experiments or theoretical values. Among them, Φ is the porosity interpreted by conventional well logging, and m is the porosity index, which can be obtained through rock electrical experiments.

[0039] From the porosity spectrum model, it can be known that by determining the statistical window length based on microresistivity imaging logging, the porosity Φ calculated based on microresistivity imaging logging within the window length can be obtained, and the corresponding porosity spectrum (porosity spectrum) can be output. Figure 3 As shown, the first channel is the depth channel; the second channel is the imaging channel based on microresistivity imaging logging; the third channel is the average porosity channel; and the fourth channel is the porosity spectrum channel, wherein the x-axis is the porosity value component, and the y-axis represents the frequency of occurrence of the corresponding pores. The shape of the porosity spectrum reflects the cumulative components of different porosity sizes of the reservoir.

[0040] The method provided by the present invention provides a porosity spectrum calculation model with simpler parameters, does not require conventional logging parameters, and has wider applicability. Compared with the porosity interpreted by conventional logging, the method of the present invention can obtain a more detailed porosity interpretation by using microresistivity imaging logging with higher resolution.

[0041] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for calculating porosity spectrum based on microresistivity imaging logging, characterized in that: include: The conductivity C measured by the i-th plate obtained based on microresistivity imaging logging i ; Obtain the resistivity R of the mud filtrate based on the well site water analysis data mf ; Get the porosity tortuosity T; According to the conductivity C i 、Mud filtrate resistivity R mf , porosity tortuosity T determines the porosity Φ corresponding to the i-th plate i ; According to the porosity Φ corresponding to the i-th plate i Determine the porosity spectrum corresponding to the statistical window length of microresistivity imaging logging.

2. The method for calculating porosity spectrum based on microresistivity imaging logging according to claim 1, characterized in that: According to the conductivity C i 、Mud filtrate resistivity R mf , porosity tortuosity T determines the porosity Φ corresponding to the i-th plate i Including using the following formula to obtain the porosity Φ i Φ i =C i R mf T 2 。 3. The method for calculating porosity spectrum based on microresistivity imaging logging according to claim 1, characterized in that: The porosity spectrum is constructed based on a capillary physical model.

4. The method for calculating porosity spectrum based on microresistivity imaging logging according to claim 3, characterized in that: The conductivity C measured by the i-th plate obtained based on microresistivity imaging logging i include: According to the capillary physical model, the resistance R of the pore fluid and the length L of the rock side per unit volume are determined. h ; According to the resistance R of the pore fluid and the side length L of the rock h , determine the conductivity C based on single plate measurement of microresistivity imaging logging i .

5. The method for calculating porosity spectrum based on microresistivity imaging logging according to claim 4, characterized in that: The resistance R of the pore fluid and the side length L of the rock h , determine the conductivity C based on single plate measurement of microresistivity imaging logging i Including obtaining the conductivity C according to the following formula i :

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