Method for constructing comprehensive parameters of pore structure based on conventional logging information

Abstract

A method for constructing pore structure comprehensive parameters based on conventional logging information belongs to the technical field of pore structure parameter construction methods, and comprises the following steps: extracting a density and interval transit time curve reflecting reservoir physical properties, a natural gamma curve reflecting lithology and a natural potential curve reflecting reservoir permeability, and adopting a weighting mode to calculate the pore structure comprehensive parameters; the method comprises the following steps: constructing a comprehensive classification parameter beta of the pore structure, evaluating the pore structure of the reservoir by using beta, extracting a density and interval transit time curve reflecting physical properties of the reservoir, a natural gamma curve reflecting lithology and a natural potential curve reflecting permeability of the reservoir, and constructing the comprehensive classification parameter beta of the pore structure by adopting a weighting mode. According to the reservoir classification method established by utilizing the calculated pore structure comprehensive parameter beta, the coring well and the key exploratory well in the research area are processed and explained, the explanation result conforms to the oil testing result, the daily oil production of oil testing of the oil well layer taking the first type of reservoir as the main is high, and the practicability of the method is proved.

Description

Technical Field

[0001] The present invention belongs to the technical field of methods for constructing pore structure parameters, and in particular relates to a method for constructing comprehensive pore structure parameters based on conventional well logging data. Background Art

[0002] The evaluation of reservoir pore structure mainly relies on core experimental analysis and new logging technology. The laboratory mainly obtains relevant information about reservoir pore structure through experimental methods such as scanning electron microscope, cast thin section, mercury injection, centrifuge, nuclear magnetic resonance, CT scanning imaging, etc., but this method is limited by the number of coring wells and samples, and is expensive; and the evaluation of reservoir pore structure with the help of logging data can better solve the above problems. At present, the most widely used methods mainly include nuclear magnetic resonance logging and imaging logging. However, under the current low oil price situation, in order to reduce costs and increase efficiency, most new wells only carry out conventional logging data acquisition, especially development wells, and rarely carry out special logging operations, resulting in this method not being able to serve oilfield production well. Therefore, how to further explore the information of conventional logging data and develop a low-permeability reservoir pore structure evaluation method based on conventional logging data is of great significance. Summary of the invention

[0003] In order to solve the above-mentioned problems, the present invention proposes: a method for constructing comprehensive pore structure parameters based on conventional logging data, extracting density and acoustic time difference curves reflecting reservoir physical properties, natural gamma curves reflecting lithology and natural potential curves reflecting reservoir permeability, and constructing a comprehensive pore structure classification parameter β in a weighted manner, and using β to evaluate the reservoir pore structure.

[0004] Furthermore, the density and acoustic time difference curves reflecting reservoir physical properties, the natural gamma curve reflecting lithology and the natural potential curve reflecting reservoir permeability are extracted, and a weighted method is used to construct a comprehensive classification parameter β of the pore structure.

[0005] Furthermore, the following steps are included: S1. For the well logging curves in the study area, a standard layer is selected and the well logging curves are standardized to ensure that the calculated geological parameters such as density, acoustic wave time difference, natural gamma and natural potential reach a uniform accuracy.

[0006] Furthermore, S2, the distribution of parameters of density, acoustic time difference, natural gamma and natural potential of different reservoirs are statistically analyzed, and they are classified and evaluated.

[0007] Further, S3, weight coefficients are given to each parameter according to the classification situation, and the comprehensive parameter β of the pore structure is calculated.

[0008] Furthermore, the well logging curves were standardized, mainly by using histogram normalization using regional standard layers.

[0009] Furthermore, the parameter distributions of density, acoustic time difference, natural gamma and natural potential of different reservoirs are statistically analyzed and classified and evaluated.

[0010] Furthermore, a weight coefficient is given to each parameter according to the classification situation, and the comprehensive pore structure parameter β is calculated. The calculation formula for the comprehensive pore structure parameter β is as follows:

[0011] β=∑klogi=k den +k ac +k gr +k sp .

[0012] The beneficial effects of the present invention are as follows: a reservoir classification method established by using the calculated pore structure comprehensive parameter β is used to process and interpret the core wells and key exploration wells in the study area, and the interpretation results are consistent with the oil test results. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a flow chart of the main operation process of the present invention;

[0014] Figure 2 It is the relationship diagram between resistivity and comprehensive parameters of pore structure;

[0015] Figure 3 It is a reservoir example application diagram of pore structure parameter classification. DETAILED DESCRIPTION

[0016] With the continuous deepening of exploration and development, the reservoir evaluation work faced is becoming more and more complicated. Complex reservoir evaluation has become one of the hot spots, and reservoir pore structure evaluation is a difficult point in complex reservoir evaluation. Based on conventional logging data, the present invention adopts a weighted approach to construct a comprehensive classification parameter β of pore structure, and uses β to evaluate the pore structure of the reservoir, thereby proposing a method for constructing comprehensive pore structure parameters based on conventional logging data.

[0017] A method for constructing comprehensive pore structure parameters based on conventional logging data, extracting density and acoustic time difference curves reflecting reservoir physical properties, natural gamma curves reflecting lithology and natural potential curves reflecting reservoir permeability, and constructing a pore structure comprehensive classification parameter β in a weighted manner, and using β to evaluate the reservoir pore structure.

[0018] Among them, the density and acoustic time difference curves reflecting reservoir physical properties, the natural gamma curve reflecting lithology and the natural potential curve reflecting reservoir permeability are extracted, and a weighted method is used to construct the comprehensive classification parameter β of pore structure.

[0019] The following steps are included: S1. For the well logging curves in the study area, a standard layer is selected and the well logging curves are standardized to ensure that the calculated geological parameters such as density, acoustic wave time difference, natural gamma and natural potential reach a uniform accuracy.

[0020] Among them, S2, statistical distribution of parameters of different reservoir density, acoustic wave time difference, natural gamma and natural potential; and classification and evaluation.

[0021] Among them, S3, gives weight coefficients to each parameter according to the classification situation, and calculates the comprehensive parameter β of the pore structure.

[0022] Among them, the logging curves were standardized, mainly using the histogram standardization of the regional standard layer.

[0023] Among them, the parameter distributions of different reservoir density, acoustic wave time difference, natural gamma and natural potential are statistically analyzed, and they are classified and evaluated.

[0024] Among them, the weight coefficient is given to each parameter according to the classification situation, and the pore structure comprehensive parameter β is calculated. The calculation formula for the pore structure comprehensive parameter β is as follows:

[0025] β=∑klogi=k den +k ac +k gr +k sp .

[0026] like Figure 1 As shown, a method for constructing pore structure parameters based on conventional logging data specifically includes the following steps: extracting density and acoustic time difference curves reflecting reservoir physical properties, natural gamma curves reflecting lithology and natural potential curves reflecting reservoir permeability, and constructing a comprehensive pore structure classification parameter β in a weighted manner.

[0027] 1) For the well logging curves in the study area, select standard layers and standardize the well logging curves to ensure that the calculated geological parameters such as density, acoustic wave time difference, natural gamma and natural potential reach a uniform accuracy;

[0028] 2) Statistical distribution of parameters of different reservoir density, acoustic wave time difference, natural gamma and natural potential; and classify and evaluate them;

[0029] 3) According to the classification, weight coefficients are given to each parameter to calculate the comprehensive parameter β of the pore structure;

[0030] Step 1) First, the well logging curves were standardized, mainly by using the regional standard layer and adopting histogram standardization.

[0031] Step 2) Statistical distribution of parameters of different reservoir density, acoustic wave time difference, natural gamma and natural potential; and classify and evaluate them, such as Figure 3shown.

[0032] The evaluation table of reservoir classification standards for conventional logging curves is as follows:

[0033]

[0034] Step 3) According to the classification, weight coefficients are given to each parameter, and the comprehensive parameter β of the pore structure is calculated, such as Figure 2 shown.

[0035] The standard table of weight coefficients for evaluating reservoir pore structure using conventional logging curves is as follows:

[0036]

[0037] The calculation formula for the comprehensive pore structure parameter β is as follows:

[0038] β=∑klogi=k den +k ac +k gr +k sp .

[0039] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical solutions and concepts of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for constructing comprehensive pore structure parameters based on conventional well logging data, characterized in that: The density and acoustic time difference curves reflecting reservoir physical properties, the natural gamma curve reflecting lithology and the natural potential curve reflecting reservoir permeability are extracted, and a weighted method is used to construct a comprehensive classification parameter β of the pore structure, which is used to evaluate the reservoir pore structure.

2. The method for constructing comprehensive pore structure parameters based on conventional well logging data according to claim 1, characterized in that: The density and acoustic time difference curves reflecting reservoir physical properties, the natural gamma curve reflecting lithology and the natural potential curve reflecting reservoir permeability are extracted, and a weighted method is used to construct the comprehensive classification parameter β of pore structure.

3. The method for constructing comprehensive pore structure parameters based on conventional well logging data according to claim 2, characterized in that: The method includes the following steps: S1. For the well logging curves in the study area, a standard layer is selected and the well logging curves are standardized to ensure that the calculated geological parameters such as density, acoustic wave time difference, natural gamma and natural potential reach a uniform accuracy.

4. The method for constructing comprehensive pore structure parameters based on conventional well logging data according to claim 3, characterized in that: S2. Statistical distribution of parameters of different reservoir density, acoustic wave time difference, natural gamma and natural potential; and classify and evaluate them.

5. The method for constructing comprehensive pore structure parameters based on conventional well logging data according to claim 4, characterized in that: S3. Give weight coefficients to each parameter according to the classification and calculate the comprehensive parameter β of the pore structure.

6. A method for constructing pore structure parameters based on conventional well logging data according to claim 1, characterized in that: The well logging curves were standardized, mainly using histogram standardization using regional standard layers.

7. The method for constructing pore structure parameters based on conventional well logging data according to claim 1, characterized in that: The distribution of parameters of density, acoustic wave time difference, natural gamma and natural potential of different reservoirs were statistically analyzed, and they were classified and evaluated.

8. The method for constructing pore structure parameters based on conventional well logging data according to claim 1, characterized in that: According to the classification, weight coefficients are given to each parameter to calculate the comprehensive pore structure parameter β. The calculation formula for the comprehensive pore structure parameter β is as follows: β=∑klogi=k den +k ac +k gr +k sp 。

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