A method for quantitatively evaluating complex sandstone rock components by using conventional logging curves

Abstract

The application provides a method for quantitatively evaluating complex sandstone rock components by using conventional logging curves, classifying rock components according to thin section analysis data, establishing a statistical relationship between conventional logging characteristic curves and total content of each type of rock component according to historical data of the total content of each type of rock component, and calculating the total content of each type of rock component according to the obtained statistical relationship and current conventional logging characteristic curves. The method provided by the application is proved by thin section analysis data, and has high precision in quantitatively evaluating complex sandstone rock components by using conventional logging data, which helps to solve the problem of difficult evaluation of complex sandstone physical property parameters.

Description

Technical Field

[0001] This invention relates to the field of reservoir evaluation technology, and in particular to a method for quantitatively evaluating the rock composition of complex sandstone using conventional logging curves. Background Technology

[0002] The H layer in the study area of ​​this invention consists of lithic sandstone, lithic quartz sandstone, and feldspathic sandstone. Quartz content varies greatly, and sedimentary, metamorphic, and igneous rock fragments are all present in the lithic fragments. Metamorphic rock fragments are mainly quartzite, with higher contents of phyllite, metamorphic sandstone, and slate in some areas. Sedimentary rock fragments are mainly argillaceous and calcified clasts, while cryptocrystalline rocks are the most abundant igneous rock fragments. The main interstitial materials are kaolinite, hydromica, as well as ferroalloy calcite, tuff, chlorite, silica, dolomite, and siderite. The interstitial material content varies greatly and its composition is complex, containing heavy minerals such as dolomite and siderite. The illite contained within is formed from the alteration of tuff and exhibits low radioactivity.

[0003] Quantitative evaluation of complex sandstone composition is crucial for calculating the physical properties of complex sandstone reservoirs using conventional logging curves; therefore, quantitative evaluation of rock composition is necessary. Currently, the most accurate logging methods for quantitative evaluation of rock composition are elemental scanning logging or formation elemental logging, but these require core analysis data for calibration of synthetic mineral categories, and the logging costs are high. Electrical imaging logging can evaluate formation lithology, but lacks methods for quantitative evaluation of rock composition. While there have been some attempts at quantitative evaluation of complex sandstone rock composition using conventional logging, widely accepted methods and techniques are currently lacking. Summary of the Invention

[0004] To improve the accuracy of quantitative evaluation of complex sandstone rock components, this invention provides a method for quantitatively evaluating complex sandstone rock components using conventional well logging curves.

[0005] This invention is achieved through the following technical solution:

[0006] A method for quantitatively evaluating the rock components of complex sandstone using conventional logging curves is proposed. The rock components are classified according to thin section analysis data. A statistical relationship between the conventional logging characteristic curves and the total content of each rock component category is established based on historical data of the total content of each rock component category. The total content of each rock component category is calculated based on the obtained statistical relationship and the current conventional logging characteristic curves.

[0007] Preferably, the rock components are divided into five categories: quartz, potassium-bearing minerals, heavy minerals, interstitial materials without heavy minerals and illite, and rock fragments without quartzite.

[0008] Furthermore, the quartz rock components include at least one of quartz, flint, and quartzite fragments; the heavy mineral rock components include at least one of ferrocalcite, ferrodolithite, and siderite.

[0009] Furthermore, the method for calculating the total content of quartz rock components is as follows:

[0010] Establish a statistical relationship between the natural gamma logging value and the total content of quartz components in the conventional well logging characteristic curve, and then calculate the total content of quartz components based on this statistical relationship and the natural gamma curve in the current conventional well logging characteristic curve;

[0011] Alternatively, establish a statistical relationship between the photoelectric absorption cross section index in conventional well logging characteristic curves and the total content of quartz rock components, and then calculate the total content of quartz rock components based on this statistical relationship and the photoelectric absorption cross section index curve in the current conventional well logging characteristic curves.

[0012] Furthermore, the statistical relationship between natural gamma logging values ​​and the total content of quartz components is as follows:

[0013] V Quartz =93.174-0.4684GR

[0014] The statistical relationship between the photoelectric absorption cross-section index of well logging and the total content of quartz components is as follows:

[0015] V Quartz =83.202-3.8136PE

[0016] Among them, V Quartz 1 represents the total content of quartz rock components, %; GR represents the natural gamma ray logging value, API; PE represents the logging photoelectric absorption cross section index, Ba / E.

[0017] Furthermore, the method for calculating the total content of heavy mineral rock components is as follows:

[0018] A statistical relationship was established between the natural gamma ray logging value and the photoelectric absorption cross section index in the conventional well logging characteristic curve. Based on this statistical relationship, the calculated photoelectric absorption cross section index characterizing the influence of clay was calculated using the natural gamma ray logging value. The difference between the calculated photoelectric absorption cross section index characterizing the influence of clay and the logging photoelectric absorption cross section index was calculated, and a statistical relationship was established between this difference and the total content of heavy mineral rock components. Based on the statistical relationship between the natural gamma ray logging value and the photoelectric absorption cross section index, the statistical relationship between the difference and the total content of heavy mineral rock components, and the natural gamma ray curve and photoelectric absorption cross section index curve in the current conventional well logging characteristic curve, the total content of heavy mineral rock components was calculated.

[0019] Furthermore, the statistical relationship between natural gamma logging values ​​and photoelectric absorption cross-section index is as follows:

[0020] PE C =2.2171+0.0063GR

[0021] The difference between the calculated photoelectric absorption section index, which characterizes the effect of clay, and the well logging photoelectric absorption section index is calculated as follows:

[0022]

[0023] The statistical relationship between the difference and the total content of heavy mineral rock components is as follows:

[0024] V HM =1.0439 + 9.6367D PE

[0025] Among them, PE C The photoelectric absorption cross section index, representing the influence of clay, is calculated based on natural gamma logging values. GR is the natural gamma logging value, and API is the index. PE The difference between the calculated photoelectric absorption cross-section index and the well logging photoelectric absorption cross-section index is used to characterize the influence of clay; PE is the well logging photoelectric absorption cross-section index, Ba / E; V HM The percentage represents the total content of heavy mineral rock components.

[0026] Furthermore, the method for calculating the total content of interstitial rock components is as follows:

[0027] Establish a statistical relationship between the total content of interstitial rock components excluding heavy minerals and illite and the thorium logging values ​​in conventional well logging characteristic curves. Calculate the total content of interstitial rock components excluding heavy minerals and illite based on this statistical relationship and the thorium logging values ​​in current conventional well logging characteristic curves.

[0028] Furthermore, the statistical relationship between the total content of interstitial rock components excluding heavy minerals and illite and thorium logging values ​​is as follows:

[0029] V interm =3.0573 + 1.4057TH

[0030] Among them, V interm The percentage represents the total content of interstitial rock components excluding heavy minerals and illite; TH represents the thorium logging value, in PPM.

[0031] The preferred method for calculating the total content of potassium-containing mineral rock components is as follows:

[0032] Establish a statistical relationship between the potassium curve in conventional well logging characteristic curves and the total content of potassium-bearing mineral rock components. Use this statistical relationship and the potassium curve in current conventional well logging characteristic curves to calculate the total content of potassium-bearing mineral rock components.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] This invention primarily utilizes the differences in rock chemical composition to classify rock components. Correlation analysis is then performed between conventional well logging characteristic curves and thin section data to establish relevant computational models, enabling quantitative evaluation of the rock components of complex sandstone. Thin section analysis data confirms that the method provided by this invention achieves high accuracy in quantitatively evaluating the rock components of complex sandstone using conventional well logging data, thus helping to solve the problem of difficult evaluation of the physical properties of complex sandstone.

[0035] Furthermore, there is a good correlation between natural gamma and the total content of quartz rock components, and a good correlation between the photoelectric absorption cross section index and the total content of quartz rock components. Therefore, the total content of quartz rock components can be calculated by establishing a statistical relationship between natural gamma, photoelectric absorption cross section index and the total content of quartz rock components.

[0036] Furthermore, among the various rock components, quartz has a high content and a low photoelectric absorption cross section index, while clay components (ferroic calcite, ferroic dolomite, and siderite) have a high photoelectric absorption cross section index. Therefore, ferroic calcite, ferroic dolomite, and siderite have the greatest impact on logging response. Thus, ferroic calcite, ferroic dolomite, and siderite are separated from the interstitial material and classified separately.

[0037] Furthermore, the total content of interstitial rock components excluding heavy minerals and illite is highly correlated with thorium. A statistical relationship between the two was established, and the total content of interstitial rock components excluding heavy minerals and illite was calculated using this relationship. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 A flowchart illustrating a method for quantitatively evaluating the composition of complex sandstone using conventional well logging curves, provided as an embodiment of the present invention;

[0040] Figure 2 This is a comparison chart of the calculated rock composition of complex sandstone described in the embodiments of the present invention and its analysis with core analysis. Detailed Implementation

[0041] To further understand the present invention, the present invention will be described below with reference to embodiments. These descriptions are only for further explaining the features and advantages of the present invention and are not intended to limit the claims of the present invention.

[0042] To quantitatively evaluate the rock composition of complex sandstone, this invention establishes a method for evaluating the rock composition of complex sandstone using conventional logging curves. This method first classifies the rock composition, and then establishes the relationship between conventional logging characteristic curves and rock composition categories, thereby achieving quantitative evaluation of the rock composition of complex sandstone.

[0043] The technical principle adopted in this invention is:

[0044] The rock components in the study area of ​​this invention are divided into five categories: quartz (including quartz, flint and quartzite fragments), potassium-bearing minerals, heavy minerals (ferro-calcite, ferro-dolomite, siderite), other interstitial materials without heavy minerals and illite, and rock fragments without quartzite.

[0045] The conventional logging curves were calibrated using thin section analysis data.

[0046] Natural gamma ray content and the total quartzite component content of rocks show a good correlation. Some sand bodies have high-uranium sandstone interlayers, and the photoelectric absorption cross section index shows a good correlation with the total quartzite component content. Statistical relationships between natural gamma ray content, photoelectric absorption cross section index, and the total quartzite component content are established. For general sandstone strata, the relevant formula for natural gamma ray content is selected, and for high-uranium strata, the relevant formula for photoelectric absorption cross section index is selected to calculate the total quartzite component content.

[0047] Among the various rock components, quartz has a high content and a low photoelectric absorption cross section index (PAC). Clay components (ferroic calcite, ferroic dolomite, and siderite) have higher PAC values. Ferroic calcite, ferroic dolomite, and siderite have the greatest impact on well logging response. Therefore, ferroic calcite, ferroic dolomite, and siderite are separated from the interstitial material and classified separately. A statistical relationship between the natural gamma curve and the PAC curve is established to characterize the influence of clay on the PAC. The calculated PAC, characterizing the clay influence, is obtained using natural gamma. Then, the difference between the well logging PAC and the calculated PAC is used to identify heavy minerals. A statistical relationship is established between this difference and the total content of heavy mineral rock components, and this relationship is used to calculate the total content of heavy mineral rock components.

[0048] Radioactivity content is highly correlated with thorium. The total content of interstitial rock components that do not contain heavy minerals or illite is also highly correlated with thorium. A statistical relationship between the two was established, and the total content of interstitial rock components that do not contain heavy minerals or illite was calculated using this relationship.

[0049] In the interstitial material, the altered tuffaceous slurry mica exhibits low native gamma characteristics. Slurry mica itself contains potassium, as does feldspar, and the slurry mica and feldspar together constitute potassium-bearing minerals. A statistical relationship was established between the K-curve in the gamma spectrum and the total content of potassium-bearing mineral rock components, and this relationship was used to calculate the total content of potassium-bearing mineral rock components.

[0050] The relative content of rock components is 100%, while the total content of rock fragment components is the remaining volume. Specific Implementation

[0052] like Figure 1 The specific implementation steps of this invention are divided into the following six steps:

[0053] Step 1: Based on thin section data, analyze and classify the reservoir rock composition in the study area;

[0054] The rock composition of the study area can be divided into five categories: quartz, potassium-bearing minerals, heavy minerals, other interstitial materials without heavy minerals and illite, and rock fragments without quartzite.

[0055] Step 2: Establish a method for calculating the total content of quartz rock components.

[0056] Natural gamma and uranium-depleted gamma curves show a good correlation with the total content of quartz components in the rocks. Some sand bodies have high-gamma sandstone interlayers. The photoelectric absorption cross section index shows a good correlation with the total content of quartz components. Statistical relationships between natural gamma, uranium-depleted gamma, photoelectric absorption cross section index and the total content of quartz components were established based on historical data. Then, based on these relationships, appropriate formulas were selected for each stratigraphic layer to calculate the total content of quartz components.

[0057] In the study area of ​​this invention, the relationships between the total content of quartz rock components and natural gamma and photoelectric absorption cross-section index are as follows:

[0058] V Quartz =93.174-0.4684GR (1)

[0059] V Quartz =83.202-3.8136PE (2)

[0060] V Quartz 1 represents the total content of quartz rock components, %; GR represents the natural gamma ray logging value, API; PE represents the logging photoelectric absorption cross section index, Ba / E.

[0061] The formula (1) is generally used to select sandstone strata, and the formula (2) is used to select photoelectric absorption cross section index related strata to calculate the total content of quartz rock components.

[0062] Step 3: Establish a method for calculating the total content of heavy mineral rock components.

[0063] Based on historical data, a statistical relationship between the natural gamma curve and the photoelectric absorption section index curve is established. The natural gamma curve is used to calculate the photoelectric absorption section index, which characterizes the influence of clay. Then, the difference between the calculated photoelectric absorption section index and the well logging photoelectric absorption section index is used to identify heavy minerals, and a statistical relationship between the two is established. This relationship is then used to calculate the total content of heavy mineral rock components.

[0064] In the study area of ​​this invention, the statistical relationship between the natural gamma curve and the photoelectric absorption cross-section exponential curve is as follows:

[0065] PE C =2.2171+0.0063GR

[0066] Among them, PE C The photoelectric absorption cross section index is calculated to characterize the effect of clay, where GR is the natural gamma and API is the standard value.

[0067] Adjust the display scale of the calculated photoelectric absorption cross section index in formations without heavy minerals so that it basically coincides with the well logging photoelectric absorption cross section index on the well logging chart. The difference between the well logging photoelectric absorption cross section index and the calculated photoelectric absorption cross section index on the well logging chart is then calculated as follows:

[0068]

[0069] Where D PE To calculate the difference between the photoelectric absorption cross section index and the logging photoelectric absorption cross section index. PE is the logging photoelectric absorption cross section index, Ba / E.

[0070] The total content of heavy mineral rock components is

[0071] V HM =1.0439 + 9.6367D PE

[0072] Where V HM The percentage represents the total content of heavy mineral rock components.

[0073] Step 4: Establish a method for calculating the total content of interstitial rock components.

[0074] Radioactivity content is highly correlated with the thorium curve. The total content of interstitial rock components (excluding heavy minerals and illite) also shows a high correlation with the thorium curve. A statistical relationship between the two was established based on historical data, and this relationship was used to calculate the total content of interstitial rock components. In the study area, the statistical relationship between the thorium curve and the total content of interstitial rock components is as follows:

[0075] V interm =3.0573 + 1.4057TH

[0076] Among them, Vinterm The percentage represents the total content of interstitial rock components excluding heavy minerals and illite; TH represents the thorium logging value in PPM.

[0077] Step 5: Establish a method for calculating the total content of potassium-containing mineral rock components.

[0078] In the interstitial material, the tuffaceous altered slurry mica exhibits low native gamma characteristics. Slurry mica itself contains potassium, as does feldspar; thus, slurry mica and feldspar constitute potassium-bearing minerals. Based on historical data, a statistical relationship was established between the K-curve in the gamma spectrum and potassium-bearing minerals, and this relationship was used to calculate the total content of potassium-bearing rock components. In the study area, the statistical relationship between the potassium curve and the total content of potassium-bearing rock components is as follows:

[0079] V K =14.792×K-0.7492

[0080] Among them, V K The total content of potassium-bearing mineral rock components is expressed as %, and K is the potassium logging value, expressed as %.

[0081] Step 6: Calculate the rock component content of complex sandstone.

[0082] The relative content of rock components is 100%, while the content of rock fragments is the remaining volume. By incorporating the above calculation method into a calculation program and inputting conventional well logging curves, rock component calculation can be achieved.

[0083] The technical implementation steps involved in this invention are completed in independent software. After the above steps, the rock composition calculation results are obtained, as shown in the appendix. Figure 2 From the appendix Figure 2 It can be seen that the mineral composition calculated by well logging is basically consistent with the mineral content of thin section analysis, realizing a method for quantitatively evaluating the composition of complex sandstone using conventional well logging curves.

[0084] The above description is merely an illustration and explanation of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for quantitatively evaluating the rock composition of complex sandstone using conventional well logging curves, characterized in that, Rock components are classified based on thin section analysis data. Statistical relationships between conventional logging characteristic curves and the total content of each rock component category are established based on historical data of the total content of each rock component category. The total content of each rock component category is calculated based on the obtained statistical relationships and the current conventional logging characteristic curves. The rock components are divided into five categories: quartz, potassium-bearing minerals, heavy minerals, interstitial materials without heavy minerals and illite, and rock fragments without quartzite; The method for calculating the total content of heavy mineral rock components is as follows: Establish a statistical relationship between natural gamma logging values ​​and photoelectric absorption cross section index in conventional well logging characteristic curves. Based on this statistical relationship, calculate the photoelectric absorption cross section index characterizing the influence of clay using natural gamma logging values. Calculate the difference between the calculated photoelectric absorption cross section index characterizing the influence of clay and the logging photoelectric absorption cross section index. Establish a statistical relationship between this difference and the total content of heavy mineral rock components. Calculate the total content of heavy mineral rock components based on the statistical relationship between natural gamma logging values ​​and photoelectric absorption cross section index, the statistical relationship between the difference and the total content of heavy mineral rock components, and the natural gamma curve and photoelectric absorption cross section index curve in current conventional well logging characteristic curves. The statistical relationship between natural gamma logging values ​​and photoelectric absorption cross section index is as follows: The difference between the calculated photoelectric absorption section index, which characterizes the effect of clay, and the well logging photoelectric absorption section index is calculated as follows: The statistical relationship between the difference and the total content of heavy mineral rock components is as follows: in, The photoelectric absorption cross section index, which characterizes the influence of clay, is calculated based on natural gamma logging values. Natural gamma logging value, API; The difference between the photoelectric absorption section index and the well logging photoelectric absorption section index is calculated to characterize the influence of clay. Ba / E is the photoelectric absorption cross-sectional index for well logging. The total content of heavy mineral rock components, %.

2. The method for quantitatively evaluating the composition of complex sandstone using conventional well logging curves according to claim 1, characterized in that, Quartz-type rock components include at least one of quartz, flint, and quartzite fragments; heavy mineral-type rock components include at least one of ferrocalcite, ferrodolithite, and siderite.

3. The method for quantitatively evaluating the composition of complex sandstone using conventional well logging curves according to claim 1, characterized in that, The method for calculating the total content of quartz rock components is as follows: Establish a statistical relationship between the natural gamma logging value and the total content of quartz components in the conventional well logging characteristic curve, and then calculate the total content of quartz components based on this statistical relationship and the natural gamma curve in the current conventional well logging characteristic curve; Alternatively, establish a statistical relationship between the photoelectric absorption cross section index in conventional well logging characteristic curves and the total content of quartz rock components, and then calculate the total content of quartz rock components based on this statistical relationship and the photoelectric absorption cross section index curve in the current conventional well logging characteristic curves.

4. The method for quantitatively evaluating the composition of complex sandstone using conventional well logging curves according to claim 3, characterized in that, The statistical relationship between natural gamma logging values ​​and the total content of quartz components is as follows: The statistical relationship between the photoelectric absorption cross-section index of well logging and the total content of quartz components is as follows: in, % represents the total content of quartz rock components; GR represents the natural gamma ray logging value (API); PE represents the logging photoelectric absorption cross section index (Ba / E).

5. The method for quantitatively evaluating the composition of complex sandstone using conventional well logging curves according to claim 1, characterized in that, The method for calculating the total content of interstitial rock components is as follows: Establish a statistical relationship between the total content of interstitial rock components excluding heavy minerals and illite and the thorium logging values ​​in conventional well logging characteristic curves. Calculate the total content of interstitial rock components excluding heavy minerals and illite based on this statistical relationship and the thorium logging values ​​in current conventional well logging characteristic curves.

6. The method for quantitatively evaluating the composition of complex sandstone using conventional well logging curves according to claim 5, characterized in that, The statistical relationship between the total content of interstitial rock components excluding heavy minerals and illite and thorium logging values ​​is as follows: in, The percentage represents the total content of interstitial rock components excluding heavy minerals and illite, in %; TH represents the thorium logging value, in PPM.

7. The method for quantitatively evaluating the composition of complex sandstone using conventional well logging curves according to claim 1, characterized in that, The method for calculating the total content of potassium-bearing rock components is as follows: Establish a statistical relationship between the potassium curve in conventional well logging characteristic curves and the total content of potassium-bearing mineral rock components. Use this statistical relationship and the potassium curve in current conventional well logging characteristic curves to calculate the total content of potassium-bearing mineral rock components.

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