Shale oil reservoir classification method and system based on nuclear magnetic product difference

Abstract

The invention discloses a shale oil reservoir classification method and system based on nuclear magnetic product difference, and belongs to the technical field of well logging. The classification method comprises the steps that firstly, nuclear magnetic resonance logging information and oil testing data are obtained, product difference calculation is conducted on the nuclear magnetic resonance logging information, and the nuclear magnetic product difference of an oil testing layer is obtained; then, the shale oil reservoir classification standard is formed by integrating the nuclear magnetic product error of the oil testing layer, nuclear magnetic resonance logging information and oil testing data; and finally, classifying the target shale oil reservoir by referring to a shale oil reservoir classification standard. According to the method, on the basis of nuclear magnetic resonance logging information, reservoir quality characterization parameters are extracted to serve as nuclear magnetic product errors, point-by-point classification of the shale oil reservoirs is achieved in combination with the porosity curve, the method conforms to the characteristics of the shale oil reservoirs, an existing shale oil reservoir classification method is supplemented, applicability is good, and the types of the shale oil reservoirs can be visually and briefly reflected.

Description

Technical Field

[0001] The present invention belongs to the field of well logging technology, and in particular relates to a shale oil reservoir classification method based on nuclear magnetic product difference and a system thereof. Background Art

[0002] Shale oil logging evaluation is a current research hotspot and also a difficult problem in the industry. The research started late. Shale formations have coexisting sources and reservoirs, strong heterogeneity, rapid changes in lithology and lithofacies, and difficulty in effectiveness evaluation. Unclear understanding of reservoir classification will lead to an increase in invalid test layers, greatly hindering the progress of shale oil exploration in oil fields. It is very meaningful to use logging methods to carry out reservoir classification, accurately evaluate the target strata, and achieve fine characterization of sweet spots and inefficient layers.

[0003] Commonly used reservoir classification methods are mainly divided into two categories. One category is represented by cluster analysis and neural networks, which use mathematical methods to mine information and improve the utilization rate of logging data. Xie Ranhong, Yang Bin, Wang Lichang, Wu Zeyun, Xu Shaohua and others have carried out a lot of work and established a relatively accurate identification model. This type of method relies on the analysis of the main controlling factors of the reservoir to optimize the logging parameters and use appropriate discriminant analysis methods to improve the accuracy; the other category is represented by pore structure evaluation, which strengthens the fine characterization of reservoir quality. Well logging evaluation mainly includes flow unit index and nuclear magnetic resonance logging evaluation. Lu Jiankang (2021) used FZI cumulative frequency to divide reservoirs into 4 categories, and established a fine calculation model for the permeability of various reservoirs, realizing the continuous division of reservoir types; Xu Shiyu (2021) based on the understanding of reservoir geological characteristics and main controlling factors, selected six parameters including porosity, permeability, permeability variation coefficient, mud content, water saturation, and reservoir thickness for quantitative classification and evaluation of reservoirs. Jin Guowen (2022) proposed a classification scheme and production capacity prediction method for sandstone conglomerate reservoirs by extracting the percentage of three pore components based on nuclear magnetic resonance logging. Extracting more information to finely characterize reservoir quality is an important task in reservoir classification evaluation using logging data.

[0004] The existing technology is slightly insufficient in the detailed characterization of shale oil reservoir categories. At the same time, there are many invalid test sections in the oil field. There is an urgent need for a more intuitive and concise classification method to reflect the shale oil reservoir categories. Summary of the invention

[0005] In order to overcome the above-mentioned shortcomings of the prior art, the purpose of the present invention is to provide a shale oil reservoir classification method and system thereof, so as to solve the problem that the existing shale oil reservoir classification is not objective and concise enough.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] The present invention discloses a shale oil reservoir classification method based on nuclear magnetic resonance product difference, which comprises the following steps: obtaining nuclear magnetic resonance logging data and oil test data, performing product difference calculation on the nuclear magnetic resonance logging data, and obtaining nuclear magnetic resonance product difference of the oil test layer; comprehensively analyzing the nuclear magnetic resonance product difference of the oil test layer, the nuclear magnetic resonance logging data and the oil test data to form a shale oil reservoir classification standard; and classifying the target shale oil reservoir with reference to the shale oil reservoir classification standard.

[0008] Preferably, the steps include:

[0009] S1, obtain cumulative porosity, total NMR logging porosity, NMR transverse relaxation time and oil testing data;

[0010] S2, g(x) is obtained from the corresponding relationship between the ratio of cumulative porosity to total porosity of NMR logging and the transverse relaxation time of NMR;

[0011] S3, construct the equation of the line f(x) passing through the two end points of g(x);

[0012] S4, determine the nuclear magnetic product difference of the test oil layer according to the sum of the difference between g(x) and f(x);

[0013] S5, the classification standard of shale oil reservoirs is formed by integrating the nuclear magnetic field difference of the oil test layer, the total porosity of nuclear magnetic logging and the oil test data;

[0014] S6, classify the target shale oil reservoir according to the nuclear magnetic product difference and nuclear magnetic porosity of the target formation and refer to the shale oil reservoir classification standard obtained in S5.

[0015] Preferably, in S2, the cumulative saturation is calculated as follows:

[0016]

[0017] Where: x is the cumulative saturation, POR is the total porosity of nuclear magnetic logging, and f(t) is the T2 spectrum distribution function of the test oil layer.

[0018] Preferably, g(x) is:

[0019] T2=g(x)

[0020] Where: T2 is the transverse relaxation time of NMR.

[0021] Preferably, in S3, the coordinates of the two end points are (0.9, log10(g(x)|x=0.9)) and (0.1, log10(g(x)|x=0.1)) respectively.

[0022] Further preferably, f(x) is:

[0023]

[0024] Where: x is the cumulative saturation; g(x) is the correspondence between the NMR transverse relaxation time and the cumulative saturation.

[0025] Preferably, in S4, the calculation method of the nuclear magnetic product difference of the oil test layer is:

[0026]

[0027] Where: Jc is the nuclear magnetic product difference; g(x) is the correspondence between the nuclear magnetic resonance transverse relaxation time and the cumulative saturation; f(x) is the equation of the straight line passing through the two end points of g(x).

[0028] Preferably, the specific steps of S5 are: classifying the test oil layers in the research area according to their production capacity, establishing a test oil layer-nuclear magnetic product difference-total porosity data intersection diagram based on the total porosity of nuclear magnetic resonance logging and the test oil layer nuclear magnetic product difference obtained in S4; and forming a shale oil reservoir classification standard based on the characteristics of different types of test oil layers in the test oil layer-nuclear magnetic product difference-total porosity data intersection diagram.

[0029] Preferably, the specific steps of S6 are: determining the nuclear magnetic resonance product difference of the target formation based on the nuclear magnetic resonance logging data measured in the target work area, combining the determined nuclear magnetic resonance product difference with the nuclear magnetic resonance porosity, and referring to the shale oil reservoir classification standard obtained in S5 to classify the target shale oil reservoir.

[0030] The present invention also discloses a shale oil reservoir classification system based on nuclear magnetic product difference, comprising:

[0031] Acquisition module, used to obtain cumulative porosity, total NMR logging porosity, NMR transverse relaxation time and oil test data;

[0032] The NMR product difference determination module is used to obtain g(x) from the corresponding relationship between the ratio of cumulative porosity to total NMR logging porosity and NMR transverse relaxation time, and obtain f(x) from the straight line passing through the two end points of g(x); the NMR product difference of the test oil layer is determined according to the sum of the difference between g(x) and f(x);

[0033] The shale oil reservoir classification standard determination module is used to integrate the NMR product difference of the test oil layer, the total porosity of NMR logging and the oil test data to form the shale oil reservoir classification standard;

[0034] The shale oil reservoir classification module is used to classify the target shale oil reservoir according to the nuclear magnetic product difference and nuclear magnetic porosity of the target formation and refer to the shale oil reservoir classification standard.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] The present invention provides a shale oil reservoir classification method based on nuclear magnetic resonance product difference. Based on nuclear magnetic resonance logging data and oil test data, a new reservoir quality characterization parameter is extracted, which is defined as nuclear magnetic resonance product difference. This parameter can reflect the concave-convex relationship between the cumulative saturation and the nuclear magnetic resonance transverse relaxation time intersection curve under the logarithmic scale, and has a strong indicative effect on the reservoir quality. Combining nuclear magnetic resonance product difference with reservoir porosity can realize point-by-point classification of shale oil reservoirs. This method conforms to the characteristics of shale oil reservoirs, can supplement the existing shale oil reservoir classification methods, and has good applicability. The calculation process and ideas of this method have changed compared with previous studies, which are specifically reflected in: the better the physical properties and oil content of the shale oil reservoir, the stronger the back-end signal of the T2 spectrum, and the cumulative saturation and the logarithmic scale crossover curve of the nuclear magnetic resonance transverse relaxation time bulge upward; when the physical properties and oil content of the reservoir deteriorate, the bulge amplitude of the cumulative saturation and the logarithmic scale crossover curve of the T2 relaxation time decreases; when the reservoir is dry and there is bound fluid in the pores, the T2 spectrum is dominated by the front-end signal, and the cumulative saturation and the logarithmic scale crossover curve of the nuclear magnetic resonance transverse relaxation time show a significant concave. In summary, this method can further tap the potential of nuclear magnetic resonance logging, intuitively reflect the type of shale oil reservoirs, help improve the level of reservoir understanding, optimize the test layer, improve the efficiency of oilfield exploration and development, and promote oilfield cost reduction and efficiency improvement. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A flow chart of a shale oil reservoir classification method based on nuclear magnetic product difference provided by the present invention;

[0038] Figure 2 This is the corresponding relationship diagram between the cumulative saturation and T2 relaxation time of the test oil layer in the target work area;

[0039] Figure 3 Schematic diagram for obtaining the nuclear magnetic product difference of the target work area;

[0040] Figure 4 It is the reservoir classification cross-plot of the target work area;

[0041] Figure 5 This is a schematic diagram of the effect of the shale oil reservoir classification method based on nuclear magnetic product difference in the target work area (Type I);

[0042] Figure 6 This is a schematic diagram of the effect of the shale oil reservoir classification method based on nuclear magnetic product difference in the target work area (Type II);

[0043] Figure 7 This is a schematic diagram of the effect of the shale oil reservoir classification method based on nuclear magnetic product difference in the target work area (Type III). DETAILED DESCRIPTION

[0044] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme 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 only 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 should fall within the scope of protection of the present invention.

[0045] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0046] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0047] See also Figure 1 The present invention provides a shale oil reservoir classification method based on nuclear magnetic product difference, and the specific steps are as follows:

[0048] S1, obtain NMR logging data and oil testing data

[0049] The nuclear magnetic resonance logging data and oil test data are obtained, wherein the nuclear magnetic resonance logging data include the cumulative porosity from the relaxation time 0 ms to the given relaxation time, the total porosity of nuclear magnetic logging, and the nuclear magnetic resonance transverse relaxation time (ie, T2 relaxation time).

[0050] S2, obtain the corresponding relationship between T2 relaxation time and cumulative saturation g(x)

[0051] The ratio of the cumulative porosity from the relaxation time 0ms to the given relaxation time to the total porosity of nuclear magnetic logging is defined as the cumulative saturation x, and its mathematical form is:

[0052]

[0053] Where: POR is the total porosity of nuclear magnetic logging, f(t) is the T2 spectrum distribution function of the test oil layer;

[0054] The corresponding relationship between T2 relaxation time and cumulative saturation x is expressed by function g(x), and its mathematical form is:

[0055] T2=g(x)

[0056] Where: T2 is the transverse relaxation time of NMR.

[0057] Taking Changqing Oilfield as an example, the evaluation target is shale oil. There are 36 test layers in the target work area with nuclear magnetic resonance logging data collected, such as Figure 2 As shown in the figure, the concave-convex relationship between the cumulative saturation and the T2 relaxation time intersection curve on a logarithmic scale has an obvious corresponding relationship with the reservoir's liquid production capacity. The pore structure of the reservoir that has reached industrial oil flow is mainly composed of large and medium-sized pores, and the intersection curve is steep at first and then gentle, with a convex shape upward; the reservoir that has not seen oil in the oil test is mainly composed of small and medium-sized pores, and the intersection curve is gentle at first and then steep, with an obvious concave shape.

[0058] S3, construct the equation of the line f(x) passing through the two end points of g(x)

[0059] In order to eliminate the influence of noise and ringing signals, the two endpoints of g(x) are defined as endpoint A and endpoint B. The coordinate of endpoint A is (0.9, log10(g(x)|x=0.9)), and the coordinate of endpoint B is (0.1, log10(g(x)|x=0.1)).

[0060] After derivation, the mathematical expression of f(x) is:

[0061]

[0062] Where: x is the cumulative saturation; g(x) is the correspondence between T2 relaxation time and cumulative saturation.

[0063] S4, determine the nuclear magnetic product difference Jc of the test oil layer

[0064] like Figure 3 As shown, the sum of the differences between g(x) and the linear equation f(x) on a logarithmic scale between cumulative saturation 0.1 and 0.9 is defined as the nuclear magnetic product difference Jc, and its mathematical form is:

[0065]

[0066] Where: g(x) is the correspondence between T2 relaxation time and cumulative saturation; f(x) is the equation of the straight line passing through endpoints A and B.

[0067] S5, based on the nuclear magnetic field difference, total porosity and oil testing results, forms the shale oil reservoir classification standard

[0068] The test oil layers in the study area were classified according to their production capacity, and a data cross-plot of test oil layers-nuclear magnetic product difference-total porosity was established based on the total porosity of nuclear magnetic logging and the nuclear magnetic product difference of the test oil layers obtained by S4. A classification standard for shale oil reservoirs was formed based on the characteristics of different types of test oil layers in the data cross-plot of test oil layers-nuclear magnetic product difference-total porosity.

[0069] Figure 4 As shown, the red dots represent industrial oil flow wells, the green dots represent low oil flow or oil flower wells, and the blue dots represent no oil wells. The classification standards for shale oil reservoirs based on NMR product difference and total porosity are as follows: Class I reservoirs (industrial oil flow) are dominated by large pores, with a measured NMR total porosity greater than 8 and a calculated NMR product difference greater than 1; Class II reservoirs (low oil flow + oil flower) are dominated by medium and large pores, with a measured NMR total porosity between 6.5 and 10, and a calculated NMR product difference greater than -1; Class III reservoirs (no oil in oil test) are dominated by small and medium pores, with a measured NMR total porosity less than 6.5 and a calculated NMR product difference less than 2.

[0070] S6, using NMR data to calculate the formation NMR product difference point by point to achieve shale oil reservoir classification

[0071] According to the measured NMR logging data of the target work area, the NMR product difference of the target formation is determined, and the determined NMR product difference is combined with the NMR porosity, and the shale oil reservoir classification standard obtained by S5 is referred to to realize the classification of the target shale oil reservoir.

[0072] The oil field in the following example is a typical shale oil reservoir in China, and the target well is analyzed by combining the shale oil reservoir classification method based on nuclear magnetic product difference.

[0073] like Figure 5 As shown, the T2 spectrum of Ning xx well at 1736-1738m is at the rear, the pores are mainly large pores, the total porosity is measured to be 15.46%, and the calculated nuclear magnetic product difference is greater than 3, which falls in the Class I area of ​​the shale oil reservoir classification plate. It is comprehensively interpreted as a Class I oil layer. The well was tested by fracturing at 1735-1738m, with a daily oil production of 24.23 tons, which is consistent with the reservoir classification results.

[0074] like Figure 6 As shown, the 1440.55m and 1462.57m point spraying fracturing of the Zhengxx well produced 0.002 tons of oil per day. The T2 spectrum position of the fracturing section reservoir is slightly behind the middle, mainly medium pores, and the measured total porosity is 8.13% and 9.23% respectively. The calculated nuclear magnetic product difference is 0.82 and 0.10 respectively, which falls in the Class II area of ​​the shale oil reservoir classification plate, which is consistent with the oil test results.

[0075] like Figure 7As shown, the T2 spectrum position of 2396-2400m in Baixx well is slightly forward in the middle, mainly small and medium pores, with a measured total porosity of 5.90%. The calculated nuclear magnetic product difference is less than 1, falling into the Class III area of ​​the shale oil reservoir classification plate. It is comprehensively interpreted as a Class III oil layer. No oil was found in this section after fracturing test, which is consistent with the reservoir classification result.

[0076] The above contents are only for explaining the technical idea of ​​the present invention and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.

Claims

1. A shale oil reservoir classification method based on nuclear magnetic product difference, characterized in that: Obtain NMR logging data and oil test data, calculate the product difference of the NMR logging data, and obtain the NMR product difference of the oil test layer; comprehensively consider the NMR product difference of the oil test layer, the NMR logging data and the oil test data to form a shale oil reservoir classification standard; refer to the shale oil reservoir classification standard to classify the target shale oil reservoir.

2. The shale oil reservoir classification method based on nuclear magnetic product difference according to claim 1 is characterized in that: The following steps are involved: S1, obtain cumulative porosity, total NMR logging porosity, NMR transverse relaxation time and oil testing data; S2, g(x) is obtained from the corresponding relationship between the ratio of cumulative porosity to total porosity of NMR logging and the transverse relaxation time of NMR; S3, construct the equation of the line f(x) passing through the two end points of g(x); S4, determine the nuclear magnetic product difference of the test oil layer according to the sum of the difference between g(x) and f(x); S5, the classification standard of shale oil reservoirs is formed by integrating the nuclear magnetic field difference of the oil test layer, the total porosity of nuclear magnetic logging and the oil test data; S6, classify the target shale oil reservoir according to the nuclear magnetic product difference and nuclear magnetic porosity of the target formation and refer to the shale oil reservoir classification standard obtained in S5.

3. The shale oil reservoir classification method based on nuclear magnetic product difference according to claim 2 is characterized in that: In S2, the cumulative saturation is calculated as: Where: x is the cumulative saturation, POR is the total porosity of nuclear magnetic logging, and f(t) is the T2 spectrum distribution function of the test oil layer.

4. The shale oil reservoir classification method based on nuclear magnetic product difference according to claim 2 is characterized in that: g(x) is: T2=g(x) Where: T2 is the transverse relaxation time of NMR.

5. The shale oil reservoir classification method based on nuclear magnetic product difference according to claim 2 is characterized in that: In S3, the coordinates of the two end points are (0.9, log10(g(x)|x=0.9)) and (0.1, log10(g(x)|x=0.1)) respectively.

6. The shale oil reservoir classification method based on nuclear magnetic product difference according to claim 5 is characterized in that: f(x) is: Where: x is the cumulative saturation; g(x) is the correspondence between the NMR transverse relaxation time and the cumulative saturation.

7. The shale oil reservoir classification method based on nuclear magnetic product difference according to claim 2 is characterized in that: In S4, the calculation method of the nuclear magnetic product difference of the test oil layer is: Where: Jc is the nuclear magnetic product difference; g(x) is the correspondence between the nuclear magnetic resonance transverse relaxation time and the cumulative saturation; f(x) is the equation of the straight line passing through the two end points of g(x).

8. The shale oil reservoir classification method based on nuclear magnetic product difference according to claim 2 is characterized in that: The specific steps of S5 are as follows: classify the test oil layers in the research area according to their production capacity, and establish a data cross-plot of test oil layers-nuclear magnetic product difference-total porosity based on the total porosity of nuclear magnetic logging and the nuclear magnetic product difference of the test oil layers obtained in S4; and form a classification standard for shale oil reservoirs based on the characteristics of different types of test oil layers in the data cross-plot of test oil layers-nuclear magnetic product difference-total porosity.

9. The shale oil reservoir classification method based on nuclear magnetic product difference according to claim 2 is characterized in that: The specific steps of S6 are: determine the nuclear magnetic resonance product difference of the target formation based on the nuclear magnetic resonance logging data measured in the target work area, combine the determined nuclear magnetic resonance product difference with the nuclear magnetic resonance porosity, and refer to the shale oil reservoir classification standard obtained in S5 to classify the target shale oil reservoir.

10. A shale oil reservoir classification system based on nuclear magnetic product difference, characterized in that: include: Acquisition module, used to obtain cumulative porosity, total NMR logging porosity, NMR transverse relaxation time and oil test data; The NMR product difference determination module is used to obtain g(x) from the corresponding relationship between the ratio of cumulative porosity to total NMR logging porosity and NMR transverse relaxation time, and obtain f(x) from the straight line passing through the two end points of g(x); the NMR product difference of the test oil layer is determined according to the sum of the difference between g(x) and f(x); The shale oil reservoir classification standard determination module is used to integrate the NMR product difference of the test oil layer, the total porosity of NMR logging and the oil test data to form the shale oil reservoir classification standard; The shale oil reservoir classification module is used to classify the target shale oil reservoir according to the nuclear magnetic product difference and nuclear magnetic porosity of the target formation and refer to the shale oil reservoir classification standard.

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