Evaluation and optimization method for continental shale oil dessert interval

Abstract

The invention relates to an evaluation and optimization method for continental shale oil dessert intervals, which comprises the following steps: calculating an oil production evaluation coefficient of each sample according to the organic carbon content and petroleum potential parameters; calculating a reservoir evaluation coefficient of each sample according to the shale porosity; calculating an oiliness evaluation coefficient of each sample according to the free oil quantity; calculating a compressibility evaluation coefficient of each sample according to the quartz content, the carbonate mineral content and the clay mineral content; calculating the shale oil dessert layer segment coefficient of each sample according to the oil-generating property evaluation coefficient of each sample, the storage property evaluation coefficient of each sample, the oiliness evaluation coefficient of each sample and the compressibility evaluation coefficient of each sample, and performing data distribution proportion analysis on the shale oil dessert layer segment coefficients of all the samples in the plurality of samples to obtain the shale oil dessert layer segment coefficient of each sample. And determining an evaluation grading standard to complete well drilling shale oil dessert interval evaluation optimization, so that technical support can be provided for realizing high yield and stable yield of a shale oil well.

Description

Technical Field

[0001] The present invention relates to the technical field of shale oil exploration, and in particular to a method for evaluating and optimizing a continental shale oil sweet spot layer. Background Art

[0002] The TOC content of marine shale in North America is generally greater than 2%, with an average of 3%. The organic matter type is mainly mixed kerogen, with a high pressure coefficient, sufficient formation energy, good oil content, and high mobile hydrocarbon content. However, the organic carbon content of continental shale in my country varies, with an average value of less than 2% in most basins. Therefore, it is difficult to apply the technical methods and cognitive achievements of marine shale oil in North America to the research on the geological conditions for the formation and enrichment mechanism of continental shale oil.

[0003] The results of literature survey show that the current research on continental shale oil in my country is mainly focused on lithofacies, reservoirs, shale oil enrichment characteristics and laws. For the key areas of shale oil breakthroughs such as the Gulong area of ​​the Songliao Basin, the Jiyang sag of the Bohai Bay Basin, the Qintong and Gaoyou sags of the Subei Basin, and the Fuxing area of ​​the Sichuan Basin, some geological understandings have been proposed in the understanding of enrichment characteristics and geological laws, such as favorable lithofacies are the basis, high-quality inorganic pores are the key, and abnormally high pressure provides the necessary conditions for high shale oil production. However, for the optimization of the sweet spot layer of continental shale oil and the determination of the traversing layer of shale oil horizontal wells in production, it is still mainly based on single factor analysis and comparison of lithofacies, reservoirs, oil generation, oil content, mobility, etc., and the optimization is mainly based on experience judgment. It is urgent to establish a corresponding scientific quantitative evaluation method. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the above-mentioned shortcomings and deficiencies of the prior art, the present invention provides a method for evaluating and optimizing sweet spot layers of continental shale oil, so as to select the best horizontal well penetration layer section to achieve high and stable production of continental shale oil wells.

[0006] (II) Technical solution

[0007] In order to achieve the above object, the main technical solutions adopted by the present invention include:

[0008] In a first aspect, an embodiment of the present invention provides a method for evaluating and optimizing a terrestrial shale oil sweet spot layer, comprising: identifying shale lithofacies to obtain lithofacies identification results, dividing layers based on conventional logging curve characteristics and lithofacies identification results to obtain layer division results; sampling based on the lithofacies identification results and the layer division results to obtain multiple samples, and determining target parameters corresponding to each of the multiple samples; wherein the target parameters include organic carbon content, oil potential parameters, shale porosity, free oil content, quartz content, carbonate mineral content, and clay mineral content; according to the organic carbon content and the oil potential parameters, calculating the oil generation evaluation of each sample coefficient; calculate the reservoir evaluation coefficient of each sample according to the shale porosity; calculate the oil content evaluation coefficient of each sample according to the free oil content; calculate the compressibility evaluation coefficient of each sample according to the quartz content, carbonate mineral content and clay mineral content; calculate the shale oil sweet spot layer coefficient of each sample according to the oil generation evaluation coefficient of each sample, the reservoir evaluation coefficient of each sample, the oil content evaluation coefficient of each sample and the compressibility evaluation coefficient of each sample, and perform data distribution ratio analysis on the shale oil sweet spot layer coefficients of all samples in multiple samples to determine the evaluation grading standard, so as to complete the evaluation and optimization of shale oil sweet spot layer in drilling.

[0009] In one possible embodiment, the oil generation evaluation coefficient of each sample is calculated according to the organic carbon content and the oil potential parameter, including: calculating the TOC coefficient of each sample according to the organic carbon content; calculating the hydrogen index ratio of each sample according to the organic carbon content and the oil potential parameter; and taking the product of the TOC coefficient of each sample and its hydrogen index ratio as the oil generation evaluation coefficient of the corresponding sample.

[0010] In a possible embodiment, the TOC coefficient of each sample is calculated according to the organic carbon content, including: calculating a first average value of the organic carbon content of all samples; and taking the ratio of the organic carbon content of each sample to the first average value as the TOC coefficient of the corresponding sample.

[0011] In one possible embodiment, the hydrogen index ratio of each sample is calculated based on the organic carbon content and the oil potential parameter, including: calculating the hydrogen index of each sample based on the oil potential parameter of each sample and its corresponding organic carbon content; calculating the second average value of the hydrogen index of all samples; and taking the ratio of the hydrogen index of each sample to the second average value as the hydrogen index ratio of the corresponding sample.

[0012] In one possible embodiment, the calculation expression of the hydrogen index is as follows:

[0013]

[0014] In the formula, I i represents the hydrogen index of the i-th sample; S2 iA represents the oil potential parameter of the i-th sample; i represents the organic carbon content of the ith sample.

[0015] In a possible embodiment, the reservoir evaluation coefficient of each sample is calculated based on the shale porosity, including: calculating the third average value of the shale porosity of all samples; and taking the ratio of the shale porosity of each sample to the third average value as the reservoir evaluation coefficient of the corresponding sample.

[0016] In a possible embodiment, the oil content evaluation coefficient of each sample is calculated based on the free oil content, including: calculating the fourth average value of the free oil content of all samples; and taking the ratio of the free oil content of each sample to the fourth average value as the oil content evaluation coefficient of the corresponding sample.

[0017] In a possible embodiment, the compressibility evaluation coefficient of each sample is calculated based on the quartz content, the carbonate mineral content and the clay mineral content, including: calculating the compressibility index of each sample based on the quartz content of each sample, the carbonate mineral content of each sample and the clay mineral content of each sample; calculating the fifth average value of the compressibility index of all samples; and taking the ratio of the compressibility index of each sample to the fifth average value as the compressibility evaluation coefficient of the corresponding sample.

[0018] In a possible embodiment, the calculation expression of the compressibility index is as follows:

[0019]

[0020] In the formula, E i represents the compressibility index of the i-th sample; Q i represents the quartz content of the i-th sample; T i represents the carbonate mineral content of the i-th sample; N i represents the clay mineral content of the ith sample.

[0021] In a possible embodiment, the calculation expression of the shale oil sweet spot interval coefficient is as follows:

[0022] F i =Y i ×C i ×H i ×K i ;

[0023] In the formula, F i represents the shale oil sweet spot coefficient of the i-th sample; Y i represents the oil generation evaluation coefficient of the i-th sample; C i represents the reservoir evaluation coefficient of the i-th sample; H i represents the oil content evaluation coefficient of the i-th sample; Ki Represents the compressibility evaluation coefficient of the i-th sample.

[0024] In a second aspect, an embodiment of the present application provides a storage medium having a computer program stored thereon, and the computer program is executed by a processor to execute the method described in the first aspect or any optional implementation of the first aspect.

[0025] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the method described in the first aspect or any optional implementation method of the first aspect is performed.

[0026] In a fourth aspect, the present application provides a computer program product, which, when running on a computer, enables the computer to execute the method in the first aspect or any possible implementation of the first aspect.

[0027] (III) Beneficial effects

[0028] The beneficial effects of the present invention are:

[0029] The embodiment of the present invention proposes a method for evaluating and optimizing sweet spot layers of continental shale oil, which fully considers the differences in oil generation, reservoir, oil content and compressibility of the target shale oil layers in the vertical direction, and establishes a quantitative evaluation method for shale oil sweet spot layers including the key parameters of "four properties", so as to provide technical support for accurately determining the horizontal well penetration layers in continental shale oil drilling and achieving high and stable production of shale oil wells.

[0030] In order to make the above-mentioned objectives, features and advantages to be achieved by the embodiments of the present application more obvious and understandable, the following specifically cites preferred embodiments and describes them in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0032] Figure 1 A flow chart showing a method for evaluating and optimizing a continental shale oil sweet spot layer provided in an embodiment of the present application is shown;

[0033] Figure 2A schematic diagram showing the relationship between a data cumulative proportion and a sweet layer coefficient provided in an embodiment of the present application is shown;

[0034] Figure 3 A schematic diagram of sweet layer evaluation provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0035] In order to better explain the present invention and facilitate understanding, the present invention is described in detail below through specific implementation modes in conjunction with the accompanying drawings.

[0036] Continental shales have diverse lithofacies types and organic microscopic component types. Different layers have different oil generation, reservoir properties, oil content and compressibility. It is difficult to optimize shale oil sweet spot layers, which has become a bottleneck problem restricting the high and stable production of continental shale oil wells in my country.

[0037] Therefore, in order to select the best horizontal well penetration layer section to achieve high and stable production of continental shale oil wells, the embodiment of the present invention proposes an evaluation and optimization method for continental shale oil sweet spot layer sections, which fully considers the differences in oil generation, reservoir, oil content and compressibility of shale oil target layers in the vertical direction, and establishes a quantitative evaluation method for shale oil sweet spot layer sections including the key parameters of "four properties", which provides technical support for accurately determining the horizontal well penetration layer sections for continental shale oil drilling and achieving high and stable production of shale oil wells.

[0038] In order to better understand the above technical solution, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to enable a clearer and more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0039] See also Figure 1 , Figure 1 The flowchart of a method for evaluating and optimizing a continental shale oil sweet spot layer provided by an embodiment of the present application is shown. It should be understood that the evaluation and optimization method can be performed by an evaluation and optimization device for a continental shale oil sweet spot layer, and the specific device of the evaluation and optimization device can be set according to actual needs, and the embodiment of the present application is not limited thereto. For example, the evaluation and optimization device can be a computer, etc. Specifically, the evaluation and optimization method includes:

[0040] Step S110, identifying the shale lithofacies to obtain a lithofacies identification result, and performing layer segmentation based on conventional logging curve characteristics and the lithofacies identification result to obtain a layer segmentation result.

[0041] Specifically, drilling core observation and description can be carried out, vertical lithofacies identification and division can be performed, and layer division can be carried out in combination with conventional logging curve characteristics.

[0042] Step S120, sampling is performed based on the lithofacies identification results and the layer segmentation results to obtain multiple samples, and the target parameters corresponding to each of the multiple samples are determined. The target parameters include organic carbon content, oil potential parameters, shale porosity, free oil content, quartz content, carbonate mineral content, and clay mineral content.

[0043] Specifically, n samples are collected according to lithofacies and layers, and parameters such as organic carbon content (TOC), rock pyrolysis, porosity (Φ) and whole-rock X-ray diffraction are tested and analyzed on the n samples to obtain target parameters including organic carbon content, oil potential parameters, shale porosity, free oil content, quartz content, carbonate mineral content and clay mineral content.

[0044] Step S130, calculating the oil generation evaluation coefficient of each sample according to the organic carbon content and the oil potential parameter.

[0045] It should be understood that the specific process of calculating the oil generation evaluation coefficient of each sample according to the organic carbon content and the oil potential parameter can be set according to actual needs, and the embodiments of the present application are not limited thereto.

[0046] Optionally, the TOC coefficient of each sample is calculated based on the organic carbon content; the hydrogen index ratio of each sample is calculated based on the organic carbon content and the oil potential parameter; and the product of the TOC coefficient of each sample and its hydrogen index ratio is used as the oil generation evaluation coefficient of the corresponding sample.

[0047] The TOC coefficient of each sample is calculated according to the organic carbon content, including: calculating a first average value of the organic carbon content of all samples; taking the ratio of the organic carbon content of each sample to the first average value as the TOC coefficient of the corresponding sample;

[0048] And, calculating the hydrogen index ratio of each sample according to the organic carbon content and the oil potential parameter, including: calculating the hydrogen index of each sample according to the oil potential parameter of each sample and its corresponding organic carbon content; calculating the second average value of the hydrogen index of all samples; and taking the ratio of the hydrogen index of each sample to the second average value as the hydrogen index ratio of the corresponding sample.

[0049] To facilitate understanding of step S130, a specific embodiment is used to describe it below.

[0050] Specifically, the TOC data of organic carbon content obtained from all sample tests were used to establish a calculation formula for the TOC coefficient (T) to reveal the differences in TOC content of different samples and layers. Specifically:

[0051] A 平 =(A1+A2+A3+…+A n) / n (1);

[0052] T i =A i / A 平 (2);

[0053] In the formula, A1 to A n Respectively represent the TOC data of the first sample to the TOC data of the nth sample; n represents the number of samples; A 平 represents the first average value of TOC data of all drilling samples; i is a positive integer greater than 1 and less than or equal to n; T i Represents the TOC coefficient of the ith sample.

[0054] And, using the rock pyrolysis experimental test data, the hydrogen index (I) of the shale sample is calculated using the following formula (3), and the second average value (I) of the hydrogen index of all shale samples is calculated using the following formula (4): 平 ), and the hydrogen index ratio (J) calculation formula (5) is established to reveal the differences in hydrocarbon generation potential caused by differences in shale organic parent material types, specifically:

[0055]

[0056] I 平 =(I1+I2+I3+…+I n ) / n (4);

[0057] J i =I i / I 平 (5);

[0058] In the formula, I i represents the hydrogen index of the i-th sample; S2 i A represents the oil potential parameter of the i-th sample; i represents the organic carbon content of the i-th sample; 平 Represents the second average value of the hydrogen index of all shale samples; I1 to I n represents the hydrogen index of the first sample to the hydrogen index of the nth sample; n represents the total number of all samples; J i represents the hydrogen index ratio of the ith sample.

[0059] And, using the TOC coefficient (T) and the hydrogen index ratio (J), the calculation formula of the oil generation evaluation coefficient (Y) is established to comprehensively reflect the differences in the oil generation capacity of different samples. Specifically:

[0060] Y i =T i ×J i (6);

[0061] Where Y i Represents the oil generation evaluation coefficient of the i-th sample.

[0062] Step S140: Calculate the reservoir evaluation coefficient of each sample according to the shale porosity.

[0063] It should be understood that the specific process of calculating the reservoir evaluation coefficient of each sample according to the shale porosity can be set according to actual needs, and the embodiments of the present application are not limited thereto.

[0064] Optionally, a third average value of the shale porosity of all samples is calculated; and the ratio of the shale porosity of each sample to the third average value is used as the reservoir evaluation coefficient of the corresponding sample.

[0065] For example, using the measured data of shale porosity (Φ), the third average value of shale porosity (Φ) is calculated using the following formula (7): 平 ), and the calculation formula (8) of reservoir evaluation coefficient (C) is established to reflect the difference in reservoir capacity of different samples, specifically:

[0066] Φ 平 =(Φ1+Φ2+Φ3+…+Φ n ) / n (7);

[0067] C i =Φ i / Φ 平 (8);

[0068] In the formula, Φ 平 represents the third average value of shale porosity of all samples; Φ1 to Φ n represent the shale porosity from the first sample to the nth sample respectively; C i represents the reservoir evaluation coefficient of the i-th sample; Φ i represents the shale porosity of the i-th sample.

[0069] Step S150, calculating the oil content evaluation coefficient of each sample according to the free oil content.

[0070] It should be understood that the specific process of calculating the oil content evaluation coefficient of each sample according to the free oil content can be set according to actual needs, and the embodiments of the present application are not limited to this.

[0071] Optionally, a fourth average value of the free oil content of all samples is calculated; and the ratio of the free oil content of each sample to the fourth average value is used as the oil content evaluation coefficient of the corresponding sample.

[0072] For example, using the rock pyrolysis experimental test data, the fourth average value (S1) of the free oil content of all samples is calculated using the following formula (9): 平 ), and the calculation formula (10) of the oil content evaluation coefficient (H) was established to reflect the difference in oil content of different samples, specifically:

[0073] S1 平 =(S11+S12+S13+…+S1 n ) / n (9);

[0074] H i =S1 i / S1 平 (10);

[0075] Where S1 平 The fourth average value of the free oil content of all samples; S11 to S1 n Respectively represent the free oil content of the first sample to the free oil content of the nth sample; H i Represents the oil content evaluation coefficient of the i-th sample.

[0076] Step S160, calculating the compressibility evaluation coefficient of each sample according to the quartz content, the carbonate mineral content and the clay mineral content.

[0077] It should be understood that the specific process of calculating the compressibility evaluation coefficient of each sample according to the quartz content, carbonate mineral content and clay mineral content can be set according to actual needs, and the embodiments of the present application are not limited to this.

[0078] Optionally, the compressibility index of each sample is calculated based on the quartz content of each sample, the carbonate mineral content of each sample and the clay mineral content of each sample; the fifth average value of the compressibility index of all samples is calculated; and the ratio of the compressibility index of each sample to the fifth average value is used as the compressibility evaluation coefficient of the corresponding sample.

[0079] For example, using the measured data of shale whole rock X-ray diffraction, the shale compressibility index (E) is calculated using the following formula (11), and the fifth average value of the compressibility index of all samples (E) is calculated using the following formula (12): 平 ), and the calculation formula (13) of the compressibility evaluation coefficient (K) is established to reflect the compressibility differences of different samples, specifically:

[0080]

[0081] E 平 =(E1+E2+E3+…+E n ) / n(12);

[0082] K i=E i / E 平 (13);

[0083] In the formula, E i represents the compressibility index of the i-th sample; Q i represents the quartz content of the i-th sample; T i represents the carbonate mineral content of the i-th sample; N i represents the clay mineral content of the i-th sample; E 平 The fifth average value of the compressibility index of all samples; E1 to E n Respectively represent the compressibility index of the first sample to the compressibility index of the nth sample; K i Represents the compressibility evaluation coefficient of the i-th sample.

[0084] Step S170, calculate the shale oil sweet layer coefficient of each sample according to the oil generation evaluation coefficient of each sample, the reservoir evaluation coefficient of each sample, the oil content evaluation coefficient of each sample and the compressibility evaluation coefficient of each sample, and perform data distribution ratio analysis on the shale oil sweet layer coefficients of all samples in multiple samples to determine the evaluation grading standard to complete the evaluation and optimization of drilling shale oil sweet layer.

[0085] Optionally, a shale oil sweet spot layer coefficient calculation formula (14) is established. According to the data sample of the target layer of drilling, the data distribution proportion of the shale oil sweet spot layer coefficient is statistically analyzed. The evaluation and classification standard can be determined according to the actual data distribution interval and the proportion of each interval. Specifically:

[0086] F i =Y i ×C i ×H i ×K i (14);

[0087] In the formula, F i represents the shale oil sweet spot coefficient of the i-th sample; Y i represents the oil generation evaluation coefficient of the i-th sample; C i represents the reservoir evaluation coefficient of the i-th sample; H i represents the oil content evaluation coefficient of the i-th sample; K i Represents the compressibility evaluation coefficient of the i-th sample.

[0088] In addition, the evaluation and optimization of shale oil sweet spot layers in drilling can be carried out according to the actual data conditions: when the core sampling of the target layer in drilling is relatively complete, the evaluation of the shale oil sweet spot layer in drilling can be completed according to the measured data of the samples, using the above-mentioned shale oil sweet spot layer coefficient calculation formula and evaluation standards; when the core sampling of the target layer in drilling is relatively small, the measured data of various parameters of the samples are used as the calibration basis, and the logging data are used to calculate the logging interpretation data of various parameters of the entire well section, and the above-mentioned shale oil sweet spot layer coefficient calculation formula and evaluation standards are used to complete the evaluation and optimization of the shale oil sweet spot layer in drilling.

[0089] Therefore, with the help of the above-mentioned technical scheme, the embodiment of the present application realizes the quantitative evaluation and optimization of the sweet spot layer of shale oil in a single well based on the key parameters of the "four properties" of shale oil, and provides a technical method for scientifically and accurately determining the penetration layer and target window of horizontal wells in continental shale oil drilling, which has important practical application value for achieving high and stable production of shale oil wells.

[0090] In order to facilitate understanding of the embodiments of the present application, a description is given below using specific embodiments.

[0091] Specifically, practical applications have been carried out in the Funing Formation in the Subei Basin, the Shahejie Formation in the Bohai Bay Basin, and the Jurassic in the Sichuan Basin. The evaluation of the sweet spot layer of the Funing Formation in the Fuer 2 shale oil well in the HQ1 well in the Subei Basin is now preferred as an example. Figure 2 and Figure 3 , the details are as follows:

[0092] First, we carried out core observation and description of Well HQ1, carried out vertical lithofacies identification and division, and combined with the characteristics of conventional logging curves, divided the Fu 2nd Member from bottom to top into three sub-segments: the lower sub-segment, the middle sub-segment, and the upper sub-segment. We established a core profile, such as Figure 3 As shown;

[0093] In addition, samples were collected according to lithofacies and intervals, and parameters such as TOC, rock pyrolysis, porosity (Φ) and whole-rock X-ray diffraction were tested;

[0094] And, using the TOC data obtained from the test, the TOC average value was calculated to be 1.95%, and the TOC coefficient (T) of all samples in the vertical direction was obtained according to the TOC coefficient calculation formula;

[0095] And, using the rock pyrolysis experimental test data, the hydrogen index (I) and the average hydrogen index (I 平 =248 mg·g-1), and the hydrogen index ratio (J) of all samples in the longitudinal direction is obtained according to the hydrogen index ratio calculation formula;

[0096] And, using the TOC coefficient (T) and the hydrogen index ratio (J), the oil generation evaluation coefficient calculation formula was used to obtain the oil generation evaluation coefficient (Y) of all samples in the three subsections in the longitudinal direction;

[0097] And, using the measured data of shale porosity (Φ), the average shale porosity (Φ 平 =5.4%), and the reservoir evaluation coefficient (C) of all samples in the vertical direction is obtained according to the reservoir evaluation coefficient calculation formula;

[0098] And, using the rock pyrolysis experimental test data, the average free oil content of shale (S1 平 =2.21 mg·g-1), and the oil content evaluation coefficient (H) of all samples in the longitudinal direction is obtained according to the oil content evaluation coefficient calculation formula;

[0099] Furthermore, the compressibility index (E) and the average compressibility index (E) were obtained by using the whole-rock X-ray diffraction measured data of shale and the compressibility index calculation formula. 平 =0.76), and the compressibility evaluation coefficient (K) of all samples in the longitudinal direction is obtained according to the compressibility evaluation coefficient (K) calculation formula;

[0100] In addition, the shale oil sweet layer coefficient calculation formula was used to obtain the shale oil sweet layer coefficient (F) of all samples in the vertical direction; the data distribution ratio of the F value of all samples was analyzed to determine the three-level classification evaluation standard of the sweet layer, that is, the sweet layer coefficient (F) ≥ 2 (accounting for 20%) is Class I, > 1-2 (accounting for 20%) is Class II, and ≤ 1 (accounting for 60%) is Class III. The HQ1 well was evaluated. Figure 2 and Figure 3 As shown;

[0101] Finally, based on the evaluation results of the shale oil sweet spot layer of the Fu 2nd member of well HQ1, the upper part of the middle sub-section 3675.98m-3686.64m and the upper part of the lower sub-section 3693.34m-3699.30m are selected as the development sections of Class I and Class II shale oil sweet spot layers, and it is recommended to implement horizontal well drilling in the upper part of the middle sub-section with relatively large thickness.

[0102] It should be understood that the above-mentioned preferred method for evaluating the sweet spot layer of continental shale oil is only exemplary, and those skilled in the art can make various modifications based on the above-mentioned method, and the modified scheme also falls within the protection scope of the present application.

[0103] The present application provides a storage medium having a computer program stored thereon. The computer program is executed by a processor to execute the method described in the embodiment.

[0104] The present application also provides a computer program product, which, when executed on a computer, enables the computer to execute the method described in the method embodiment.

[0105] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0106] The present invention is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present invention. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions.

[0107] It should be noted that in the claims, any reference numerals placed between brackets shall not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention may be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In the claims enumerating several means, several of these means may be embodied by the same hardware. The use of the words first, second, third, etc., is for convenience of expression only and does not indicate any order. These words may be understood as part of the component name.

[0108] In addition, it should be noted that, in the description of this specification, the description of the terms "one embodiment", "some embodiments", "embodiment", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0109] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments after knowing the basic creative concept. Therefore, the claims should be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present invention.

[0110] Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention should also include these modifications and variations.

Claims

1. A method for evaluating and optimizing sweet spot layers of continental shale oil, characterized in that: include: Identify shale lithofacies to obtain lithofacies identification results, and divide layers based on conventional logging curve characteristics and the lithofacies identification results to obtain layer division results; Sampling is performed based on the lithofacies identification result and the layer segment division result to obtain multiple samples, and target parameters corresponding to each of the multiple samples are determined; wherein the target parameters include organic carbon content, oil potential parameter, shale porosity, free oil content, quartz content, carbonate mineral content and clay mineral content; Calculating the oil generation evaluation coefficient of each sample according to the organic carbon content and the oil potential parameter; Calculating the reservoir evaluation coefficient of each sample according to the shale porosity; Calculating the oil content evaluation coefficient of each sample according to the free oil content; Calculating the compressibility evaluation coefficient of each sample according to the quartz content, the carbonate mineral content and the clay mineral content; The shale oil sweet spot layer coefficient of each sample is calculated according to the oil generation evaluation coefficient of each sample, the reservoir evaluation coefficient of each sample, the oil content evaluation coefficient of each sample and the compressibility evaluation coefficient of each sample, and the shale oil sweet spot layer coefficients of all samples in the multiple samples are analyzed for data distribution and proportion, and the evaluation grading standards are determined to complete the evaluation and optimization of the shale oil sweet spot layer in drilling.

2. The evaluation and optimization method according to claim 1, characterized in that: The step of calculating the oil generation evaluation coefficient of each sample according to the organic carbon content and the oil potential parameter comprises: Calculating the TOC coefficient of each sample according to the organic carbon content; Calculating the hydrogen index ratio of each sample according to the organic carbon content and the oil potential parameter; The product of the TOC coefficient of each sample and its hydrogen index ratio is used as the oil generation evaluation coefficient of the corresponding sample.

3. The evaluation and optimization method according to claim 2, characterized in that: Calculating the TOC coefficient of each sample according to the organic carbon content includes: Calculating a first average value of the organic carbon content of all the samples; The ratio of the organic carbon content of each sample to the first average value is taken as the TOC coefficient of the corresponding sample.

4. The evaluation and optimization method according to claim 2, characterized in that: Calculating the hydrogen index ratio of each sample according to the organic carbon content and the oil potential parameter comprises: Calculating the hydrogen index of each sample according to the oil potential parameter of each sample and its corresponding organic carbon content; Calculating a second average of the hydrogen indices of all the samples; The ratio of the hydrogen index of each sample to the second average value is taken as the hydrogen index ratio of the corresponding sample.

5. The evaluation and optimization method according to claim 4, characterized in that: The calculation expression of the hydrogen index is as follows: In the formula, I i represents the hydrogen index of the i-th sample; S2 i A represents the oil potential parameter of the i-th sample; i represents the organic carbon content of the ith sample.

6. The evaluation and optimization method according to claim 1, characterized in that: Calculating the reservoir evaluation coefficient of each sample according to the shale porosity includes: Calculating a third average value of the shale porosity of all the samples; The ratio of the shale porosity of each sample to the third average value is used as the reservoir evaluation coefficient of the corresponding sample.

7. The evaluation and optimization method according to claim 1, characterized in that: Calculating the oil content evaluation coefficient of each sample according to the free oil content includes: Calculating a fourth average of the free oil amounts of all the samples; The ratio of the free oil content of each sample to the fourth average value is used as the oil content evaluation coefficient of the corresponding sample.

8. The evaluation and optimization method according to claim 1, characterized in that: Calculating the compressibility evaluation coefficient of each sample according to the quartz content, the carbonate mineral content and the clay mineral content, including: Calculating the compressibility index of each sample according to the quartz content of each sample, the carbonate mineral content of each sample and the clay mineral content of each sample; Calculating a fifth average of the compressibility indexes of all the samples; The ratio of the compressibility index of each sample to the fifth average value is used as the compressibility evaluation coefficient of the corresponding sample.

9. The evaluation and optimization method according to claim 8, characterized in that: The calculation expression of the compressibility index is as follows: In the formula, E i represents the compressibility index of the i-th sample; Q i represents the quartz content of the i-th sample; T i represents the carbonate mineral content of the i-th sample; N i represents the clay mineral content of the i-th sample.

10. The evaluation and optimization method according to claim 1, characterized in that: The calculation expression of the shale oil sweet spot layer coefficient is as follows: F i =Y i ×C i ×H i ×K i ; In the formula, F i represents the shale oil sweet spot coefficient of the i-th sample; Y i represents the oil generation evaluation coefficient of the i-th sample; C i represents the reservoir evaluation coefficient of the i-th sample; H i K represents the oil content evaluation coefficient of the i-th sample; i represents the compressibility evaluation coefficient of the i-th sample.

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