Method for predicting non-electrical gas saturation of argillaceous sandstone

Abstract

The invention discloses an argillaceous sandstone non-electrical method gas saturation prediction method, and relates to the technical field of petroleum geophysical exploration, and the method comprises the following steps: S1, defining a density neutron separation degree DC; s2, a cross plot analysis method is applied, and a gas-free stratum density neutron separation degree DCw value calculation equation is established; s3, determining the slope c and the intercept d of the gas saturation; and S4, determining a saturation prediction equation based on the density neutron separation degree. The method belongs to a non-electrical saturation evaluation method, and has a better application effect when gas-bearing evaluation is carried out on a well without resistivity logging information. Compared with a traditional non-electrical saturation method, the method has the advantages that reservoir parameters such as porosity and shale content are increased, saturation evaluation is converted into a linear equation based on the density neutron separation degree, and the difference of reservoir types is fully considered; and the method has certain reference significance for evaluating the gas saturation of the argillaceous sandstone with relatively high heterogeneity.

Description

Technical Field

[0001] The invention relates to the technical field of petroleum geophysical exploration, and in particular to a method for predicting gas saturation of argillaceous sandstone using non-electrical method. Background Art

[0002] Saturation is the core parameter of reservoir logging evaluation. Obtaining accurate saturation helps determine the reservoir quality level, optimize mining strategies, and evaluate the production potential of the reservoir. Reliable saturation data provides a guarantee and basis for the formulation and optimization of efficient development plans for oil and gas fields. Among conventional logging methods, electrical logging is still the preferred method for quantitative evaluation of saturation. The Archie model and Indonesian model based on electrical logging have achieved good application results. In non-electrical logging, nuclear magnetic resonance logging, especially two-dimensional nuclear magnetic resonance logging, has achieved fruitful application results in the field of saturation evaluation due to its unique measurement methods and characteristics. However, due to the influence of objective factors such as its high measurement cost, it is difficult to apply and promote the nuclear magnetic resonance logging method on a large scale in the exploration and development of oil and gas fields.

[0003] For gas-bearing reservoirs, combined density and neutron logging is the most commonly used means of traditional non-electrical logging methods in gas-bearing evaluation, but its application is mainly in the qualitative identification of gas-bearing reservoirs, and the research on quantitative evaluation is still restricted by many objective factors. Among them, the invasion of mud filtrate is the most critical factor that makes it difficult to carry out quantitative research on gas saturation. Due to the exchange between mud filtrate and pore primary fluid, the reservoir fluid properties have changed. Neutron and density logging that reflect the detection range of the invasion zone are difficult to reflect the characteristics of the original formation pore fluid. Even the qualitative identification effect of gas depends on the existence of residual gas after invasion, and the difference in invasion degree increases the difficulty of quantitative evaluation of saturation. However, the emergence of LWD logging technology has greatly reduced the degree of influence of invasion on density and neutron logging data obtained while drilling, so that the reliability of quantitative evaluation of saturation based on neutron density can be guaranteed. Saturation is the core parameter of reservoir logging evaluation and an important basis for the formulation of exploration direction and development plan. The Archie model and various saturation models based on it have always been the main means of evaluating saturation by electrical logging. However, due to the influence of differences in reservoir quality, the fixed rock electrical parameters obtained by the rock resistivity enhancement experiment are difficult to characterize the conductive mechanism of all reservoir types, resulting in the saturation prediction results being unable to accurately reflect the actual state of gas in the reservoir.

[0004] Therefore, it is urgent to study a method to predict gas saturation based on density neutron separation. Summary of the invention

[0005] In order to solve the above technical problems, the present invention discloses a non-electrical gas saturation prediction method for mudstone. Based on the comparative analysis of lithology and physical properties of density and neutron curve separation degree, the method shows obvious superiority in predicting gas saturation of mudstone reservoirs with strong heterogeneity.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] A method for predicting gas saturation of argillaceous sandstone by non-electric method comprises the following steps:

[0008] S1. Define density neutron separation DC;

[0009] S2. Use the cross plot analysis method to establish the neutron separation DC of the gas-free formation density w Value calculation equation;

[0010] S3, determine the slope c and intercept d of gas saturation;

[0011] S4. Determine the saturation prediction equation based on density-neutron separation.

[0012] Optionally, in step S1, when defining the density neutron separation DC, the parameter that quantitatively expresses the degree of separation between the two logging curves of density logging DEN and neutron logging CNL is expressed as:

[0013]

[0014] Where DEN is density, g / cm 3 , CNL is the neutron logging value, v / v; DENL and DENR are 1.95 g / cm 3 and 2.95g / cm 3 , that is, the left and right scale boundaries of the density logging curve; similarly, the neutron logging scale boundaries CNLL and CNLR are 0.45 and -0.15 respectively. It should be noted that the density neutron separation DC is the density neutron separation of all formations, and DCw is the density neutron separation of water-producing formations in these formations.

[0015] Optionally, select the density neutron separation data of mudstone and muddy sandstone pure water layers as the X-axis input data of the crossplot, and the corresponding formation mud content V sh As the Y-axis input data, the neutron separation DC of the gas-free formation density is obtained. w Value, the formula is:

[0016] DC w =a×vsh+b (2)

[0017] Where, DC wis the neutron separation of gas-free formation density, decimal; vsh is the mud content, %; a and b are the slope and intercept of the linear regression equation.

[0018] Optionally, in step S3, the step of determining the slope c and intercept d of the gas saturation specifically includes:

[0019] S31. Based on discrete core test data: Closed coring of the reservoir is performed to obtain the water saturation S of the rock sample. w , based on the rock sample water saturation S w Neutron separation DC w Determine the slope and intercept of the corresponding linear equation:

[0020]

[0021] d=S w -c×DC (4)

[0022] Where, 100 is the water saturation of the pure water layer, %; S w Water saturation obtained from experimental analysis, %;

[0023] S32, based on the continuous reservoir parameters por and vsh, combined with the slope and intercept determined in step S31, a continuous slope and intercept function of the formation is obtained, which is expressed as:

[0024] c=EXP e×por+f×vsh+g (5)

[0025] d=h×EXP i×c (6)

[0026] Where por is the reservoir porosity, %; e, f, g are the fitting coefficients of the slope equation, and h and i are the fitting coefficients of the intercept equation.

[0027] Optionally, in step S4, the saturation prediction equation is:

[0028] S w (DC) = c × DC + d (7)

[0029] In the formula, S w (DC) is the reservoir water saturation calculated based on density neutron separation, %; c and d are obtained from formulas (5) and (6).

[0030] The beneficial effects of the present invention are as follows: compared with the application effects of the traditional gas reservoir saturation prediction method, the present invention has the following effects:

[0031] (1) The present invention belongs to a non-electrical saturation evaluation method and has a better applicable effect when conducting gas content evaluation on a well that does not contain resistivity logging data.

[0032] (2) Compared with the traditional non-electrical saturation method, the present invention adds reservoir parameters such as porosity and mud content, and transforms the saturation evaluation into the problem of constructing a linear equation based on density neutron separation. This method fully considers the differences in reservoir types and has certain reference significance for the gas saturation evaluation of mudstone sandstone with strong heterogeneity. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a schematic diagram of the density neutron separation of the DFX1 well in the Dongfang gas field in the Yinggehai Basin;

[0034] Figure 2 This is the relationship between the mud content and density neutron classification of Well DFX1 in Dongfang Gas Field, Yinggehai Basin;

[0035] Figure 3 The numerical simulation results of density neutron separation and equivalent water saturation of shaly sandstone with different reservoir characteristics are shown;

[0036] Figure 4 is the relationship between porosity and slope response;

[0037] Figure 5 is the relationship between mud content and slope response;

[0038] Figure 6 To predict the slope and intercept relationship of the saturation equation based on density neutron separation;

[0039] Figure 7 This is a comparison chart of the water saturation logging interpretation results of Well DFX1. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the invention claimed for protection, but merely represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0041] A method for predicting gas saturation of argillaceous sandstone by non-electric method comprises the following steps:

[0042] S1. Define the density neutron separation DC, which is a parameter that quantitatively expresses the separation degree between the density logging DEN and the neutron logging CNL logging curves. The expression is:

[0043]

[0044] Where DEN is density, g / cm 3 , CNL is the neutron logging value, v / v; DENL and DENR are 1.95 g / cm 3 and 2.95g / cm 3 , that is, the left and right scale boundaries of the density logging curve; similarly, the neutron logging scale boundaries CNLL and CNLR are 0.45 and -0.15 respectively.

[0045] S2. Use the cross plot analysis method to establish the neutron separation DC of the gas-free formation density w Value calculation equation;

[0046] The density neutron separation DC data of mudstone and muddy sandstone pure water layers are selected as the X-axis input data of the crossplot, and the corresponding formation mud content V sh As the Y-axis input data, DC w The value calculation equation is:

[0047] DC w =a×vsh+b (2)

[0048] Where, DC w is the neutron separation of gas-free formation density, decimal; vsh is the mud content, %; a and b are the slope and intercept of the linear regression equation.

[0049] S3, determine the slope c and intercept d of gas saturation;

[0050] Specifically include:

[0051] S31. Based on discrete core test data: Closed coring of the reservoir is performed to obtain the water saturation S of the rock sample. w , based on the rock sample water saturation S w Neutron separation DC w Determine the slope and intercept of the corresponding linear equation:

[0052]

[0053] d=S w -c×DC (4)

[0054] Where, 100 is the water saturation of the pure water layer, %; S w Water saturation obtained from experimental analysis, %;

[0055] S32, based on the continuous reservoir parameters por and vsh, combined with the slope and intercept determined in step S31, a continuous slope and intercept function of the formation is obtained, which is expressed as:

[0056] c=EXP e×por+f×vsh+g (5)

[0057] d=h×EXP i×c (6)

[0058] Where por is the reservoir porosity, %; e, f, g are the fitting coefficients of the slope equation, and h and i are the fitting coefficients of the intercept equation.

[0059] S4. Determine the saturation prediction equation based on density neutron separation. The saturation prediction equation is:

[0060] S w (DC) = c × DC + d (7)

[0061] In the formula, S w (DC) is the reservoir water saturation calculated based on density neutron separation, %; c and d are obtained from formulas (5) and (6).

[0062] Application Examples

[0063] In order to verify the superiority of the invention, the muddy sandstone reservoir of the DFX1 well in the Dongfang gas field in the Yinggehai Basin was selected as the research object to demonstrate the application effect of the invention, and to compare the application effect with the two classic models of traditional electrical logging. Table 1 is a statistical table of high-pressure mercury injection analysis data of the muddy sandstone reservoir of the DFX1 well in the Dongfang gas field in the Yinggehai Basin. Figures 4 to 6 The data for the drawings are all from the experimental analysis data.

[0064] Table 1 Statistics of high-pressure mercury injection analysis of muddy sandstone reservoir in Well DFX1 of Dongfang Gas Field in Yinggehai Basin

[0065]

[0066] like Figure 1 As shown in the figure, the first track is the natural gamma log (GR), the second track is the depth track, the third track is the density (DEN) and neutron log (CNL), and the fourth track is the density neutron separation (DC). When the density curve is on the right side of the neutron curve, the density neutron separation is positive (blue filled area), otherwise it is negative (yellow filled area). This change in the relative position of density and neutron is the most commonly used method for qualitatively identifying gas layers based on the mining effect. The density neutron separation in the fourth track is a parameter that quantitatively characterizes the relative position relationship between the density and neutron curves. Figure 2 DC of non-gas-bearing formations is shown w The trend line response equation is the one where the samples distributed along this trend line do not contain gas. Figure 3 The figure shows the variation of the correlation between density neutron separation and equivalent saturation of shaly sandstone under different reservoir characteristics. Although the situation that the shale content and porosity are both 30% is difficult to occur in reality, the influence of shale content and porosity on the quantitative gas saturation based on density neutron separation still has a certain reference value. Under the same shale content, no matter how the porosity changes, the density neutron separation of the saturated point remains basically unchanged, but the increase in shale content will cause the density neutron separation of the saturated water sample point to increase. When the shale content is 10%, the value of the water-saturated sample data point "A" is less than 0 (DC value is -0.01), and the neutron logging curve is on the right side of the density logging curve, but as the shale content increases further, the water-saturated sample data point moves to "B" (DC value is 0.04), and the neutron logging curve at this time is on the left side of the density curve, showing a positive value. When the shale content is 30%, the water-saturated sample data point moves to "C" and the DC value increases to 0.08. Therefore, judging pure water layers only by the positive and negative values ​​of density neutron separation may lead to misjudgment of fluid properties, especially for low-saturation gas reservoirs formed due to high mud content.

[0067] like Figure 4 and Figure 5 As shown in the figure, two points are used to construct a linear equation. The coordinate data of one point comes from the core analysis saturation and DC value. The core analysis sample comes from the pure gas layer, and the experiment is high-pressure mercury injection analysis. The coordinate data of the other point is from Figure 2 DC calculated by the formula w The actual study area shows that the natural logarithm of the slope is linearly correlated with both porosity and shale content. Figure 6 The intercept and slope of the saturation prediction equation based on separation vary exponentially, and the intercept decreases as the slope increases. Based on the slope and intercept, the saturation can be calculated according to the density neutron separation.

[0068] Figure 7 This is the result of the well logging interpretation of water saturation in the DFX1 well. The first track is the natural gamma (GR), the second track is the depth track (DEPTH), the third track is the neutron (CNL) and density logging (DEN), the fourth track is the density neutron separation (DC,), and the fifth and sixth tracks are the interpretation results of saturation logging and the irreducible water saturation value (CSwi) of high-pressure mercury injection analysis. Since the production results show that the sampling layer is a pure gas layer, the irreducible water saturation at this time is the water saturation (CSw). The saturation models are the Indonesian model Sw (Indonesia), Archie model Sw (Archie), and the density neutron separation model Sw (DC), and the last track is the type of fluid properties interpreted by the well logging.

[0069] According to the prediction accuracy comparison of different models (Table 2), the Archie model predicts water saturation with an absolute error of 9.16% and a relative error of 14.81, with the largest overall error. The Indonesian model takes into account the influence of mud content, and its prediction result is slightly better than that of the Archie model, with an absolute error of -3.48%, which is less than the true water saturation, and a relative error of 5.63%. In the present invention, since the density and neutron logging values ​​of the reservoir become smaller after gasification, the separation degree digitizes this change law, and its relationship with gas saturation is closely related to reservoir characteristics, and the gas correction index related to mud content and porosity can just reflect the difference in reservoir characteristics. Therefore, whether it is the top formation with poor physical properties or the bottom gas layer with better gas content, the separation degree method can be used to quantitatively evaluate the gas content of the reservoir, and the prediction accuracy is the best (Table 2), with an absolute error of -0.72 and a relative error of 1.17%, which shows the feasibility and superiority of this method in dealing with the saturation of argillaceous sandstone reservoirs with strong heterogeneity.

[0070] Table 2 Prediction accuracy statistics of different saturation models

[0071] DEPTH CSwi,% Sw(Archie),% Sw(Indonesia), % Sw(DC),% 2909.7 95.00 100.00 70.28 94.07 2941.4 83.11 84.11 60.77 80.66 2948.5 74.37 80.10 60.93 75.13 2960 57.57 67.36 55.62 70.69 2977.5 47.12 58.92 52.69 47.41 2984 58.08 75.87 61.23 56.26 2988.4 48.84 61.69 55.19 45.66 2991 46.07 54.59 49.43 37.41 3000 53.65 55.07 51.83 46.68 3006 54.44 72.08 65.51 57.01 average value 61.83 70.98 58.35 61.10 Absolute error / 9.16 -3.48 -0.72 Relative error / 14.81 5.63 1.17

[0072] Of course, the above description is not a limitation of the present invention, and the present invention is not limited to the above examples. Changes, modifications, additions or substitutions made by technicians in this technical field within the essential scope of the present invention should also fall within the protection scope of the present invention.

Claims

1. A method for predicting gas saturation of argillaceous sandstone by non-electrical method, characterized in that: The steps include: S1. Define density neutron separation DC; S2. Use the cross plot analysis method to establish the neutron separation DC of the gas-free formation density w Value calculation equation; S3, determine the slope c and intercept d of gas saturation; S4. Determine the saturation prediction equation based on density-neutron separation.

2. The method for predicting gas saturation of argillaceous sandstone by non-electric method according to claim 1, characterized in that: In step S1, when defining the density neutron separation DC, the parameter that quantitatively expresses the separation degree between the density logging DEN and the neutron logging CNL two logging curves is expressed as: Where DEN is density, g / cm 3 , CNL is the neutron logging value, v / v; DENL and DENR are 1.95 g / cm 3 and 2.95g / cm 3 , that is, the left and right scale boundaries of the density logging curve; similarly, the neutron logging scale boundaries CNLL and CNLR are 0.45 and -0.15 respectively.

3. The method for predicting gas saturation of argillaceous sandstone by non-electric method according to claim 2, characterized in that: In step S2, the density neutron separation data of mudstone and muddy sandstone pure water layers are selected as the X-axis input data of the crossplot, and the corresponding formation mud content V sh As the Y-axis input data, the neutron separation DC of the gas-free formation density is obtained. w Value, the formula is: DC w =a×vsh+b (2) Where, DC w is the neutron separation of gas-free formation density, decimal; vsh is the mud content, %; a and b are the slope and intercept of the linear regression equation.

4. The method for predicting gas saturation of argillaceous sandstone by non-electric method according to claim 3, characterized in that: In step S3, the step of determining the slope c and intercept d of the gas saturation specifically includes: S31. Based on discrete core test data: Closed coring of the reservoir is performed to obtain the water saturation S of the rock sample. w , based on the rock sample water saturation S w Neutron separation DC w Determine the slope and intercept of the corresponding linear equation: d=S w -c×DC (4) Where, 100 is the water saturation of the pure water layer, %; S w Water saturation obtained from experimental analysis, %; S32, based on the continuous reservoir parameters por and vsh, combined with the slope and intercept determined in step S31, a continuous slope and intercept function of the formation is obtained, which is expressed as: c=EXP e×por+f×vsh+g (5) d=h×EXP i×c (6) Where por is the reservoir porosity, %; e, f, g are the fitting coefficients of the slope equation, and h and i are the fitting coefficients of the intercept equation.

5. The method for predicting gas saturation of argillaceous sandstone by non-electric method according to claim 4, characterized in that: In step S4, the saturation prediction equation is: S w (DC)=c×DC+d (7) In the formula, S w (DC) is the reservoir water saturation calculated based on density neutron separation, %; c and d are obtained from formulas (5) and (6).

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