A method and system for determining and quantitatively analyzing the main development zones of shale oil.
By classifying and similaring the dynamic production curves of pure shale oil, and combining artificial intelligence algorithms and mathematical models, the uncertainty of target selection in the development of continental shale oil was solved, and efficient pure shale oil development was achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- PETROCHINA CO LTD
- Filing Date
- 2022-07-01
- Publication Date
- 2026-06-30
AI Technical Summary
Existing technologies are insufficient to comprehensively and accurately select the best development targets and evaluate the sweet spots for different pure shale oils. In particular, in the development of continental shale oils, the development engineering factors and geological differences have not been effectively considered, resulting in poor development results.
Artificial intelligence algorithms are used to classify and analyze the dynamic production curves of pure shale oil. Combined with the production curves and key parameter mathematical models, curves are screened using Eulerian distance and MAPE-relative error percentage. Production capacity characteristics and development effect evaluation standards are established to determine the main geological development zones for continental shale oil.
Accurately identify favorable development zones for pure shale oil, optimize well pattern design, improve the development efficiency of shale oil, and achieve efficient development of continental shale oil.
Smart Images
Figure CN117365459B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of unconventional oil and gas exploration and development technology, and in particular to a method and system for determining and quantitatively analyzing the main development zones for shale oil. Background Technology
[0002] In the field of oil and gas development technology, unconventional oil and gas is gradually becoming a new area of global oil and gas exploration, especially shale oil, which has become a hot spot in global oil and gas exploration and development. In my country, the Ordos Chang 7... 1+2 Shale oil reserves are found in several large-scale shale oil-bearing areas, including the Jimsar Lucaogou Formation in the Junggar Basin. According to resource assessments by the Ministry of Land and Resources, interbedded and laminated shale oil resources could reach 20.1 billion tons, while pure shale oil resources in the Qingshankou Formation in the northern Songliao Basin alone are estimated at 9.8 billion tons, indicating even greater potential. Currently, domestic and international shale oil exploration and evaluation studies typically use geological parameters such as shale free hydrocarbon content (S1), TOC, porosity, oil saturation, and effective thickness to assess shale oil potential and identify sweet spots. Emphasis is placed on the content of retained hydrocarbons and reservoir performance in shale, focusing on the evaluation and selection of sweet spots. For example, Chinese patent applications 201710097281.0 and 201810763086.1 determine favorable shale formations based on maturity, organic carbon content, hydrogen index, and shale density. In the Chinese patent application with application number 202110056218.9, various parameters obtained from rock pyrolysis analysis were used to calculate the amount of hydrocarbon expulsion, evaluate the oil-bearing properties of shale, and further clarify the favorable exploration intervals for shale oil.
[0003] Compared to marine shale formations abroad, domestic lacustrine (continental) shale formations exhibit greater heterogeneity. During development, it is crucial to consider the mobility and compressibility of shale oil, emphasizing the productivity of pure shale oil. Therefore, establishing a comprehensive and sound evaluation system for shale oil reservoir development intervals to identify favorable development intervals is of paramount importance. Summary of the Invention
[0004] The purpose of this invention is to provide a method and system for determining and quantitatively analyzing the main development zones of shale oil. Combining production patterns and considering development engineering factors, it uses artificial intelligence algorithms to determine the weights of each parameter, which can accurately identify the favorable zones in the development stage of pure shale oil, establish a sweet spot evaluation technology and method for pure shale oil development, and provide a basis for realizing the profitable development of pure shale oil.
[0005] To achieve the above objectives, the present invention provides the following technical solution:
[0006] A method for determining and quantitatively analyzing the main development zones of shale oil, the method comprising:
[0007] Based on the dynamic production curve of pure shale oil, the characteristics of pure shale oil production capacity are revealed;
[0008] Based on the different pure shale oil production capacity characteristics, extract the standards and parameters for shale oil development effect analysis;
[0009] Based on the standards and parameters for analyzing the effectiveness of shale oil development, the main geological development zones for shale oil should be determined.
[0010] Based on the development results of shale oil and the main geological development zones, the main drilling targets for shale oil were determined.
[0011] Preferably, the step of revealing the pure shale oil production capacity characteristics based on the pure shale oil dynamic production curve includes,
[0012] Obtain the dynamic production curve of pure shale oil;
[0013] Classify the dynamic production curves of pure shale oil;
[0014] A similarity analysis was performed on the dynamic production curves of pure shale oil after classification.
[0015] The analysis results reveal the production capacity characteristics of pure shale oil.
[0016] Preferably, the classification of dynamic production curves for pure shale oil is as follows:
[0017] This includes classifying the dynamic production curves of pure shale oil by category, unsupervised clustering, or supervised classification;
[0018] It also includes similarity comparison and classification of curves of fixed or variable length, and trend prediction of single-channel and multi-channel curves.
[0019] Preferably, the similarity analysis of the dynamic production curves of the classified pure shale oil includes,
[0020] Artificial intelligence algorithms for trend prediction are used to filter the distance errors between two or more similar curves; among them,
[0021] The artificial intelligence algorithm for trend prediction includes Eulerian distance and MAPE (Most Percentage of Relative Error).
[0022] Preferably, the standards and parameters for analyzing the development effect of extracted shale oil include:
[0023] Based on the different pure shale oil production capacity characteristics, establish a mathematical model of production curves and key parameters;
[0024] Based on the production curve and key parameter mathematical model, the evaluation criteria and parameters for shale oil development effectiveness are extracted.
[0025] Preferably, the establishment of the production curve and key parameter mathematical model includes the following steps:
[0026] Based on the different production capacity characteristics of pure shale oil, a mathematical model of production curves and key parameters is established using an artificial intelligence recurrent neural network algorithm.
[0027] Preferably, the pure shale oil production capacity characteristics include, but are not limited to, one or more of the following: initial production capacity, cumulative production capacity in the first two years, or average daily production during the high-production period.
[0028] Preferably, the shale oil development effect analysis standards and parameters include the amount of retained hydrocarbons, crude oil mobility, and compressibility.
[0029] A system for determining and quantitatively analyzing the main development zones of shale oil, the system comprising:
[0030] The revealing unit is used to reveal the production capacity characteristics of pure shale oil based on the dynamic production curve of pure shale oil.
[0031] The extraction unit is used to extract shale oil development effect analysis standards and parameters based on the different pure shale oil production capacity characteristics;
[0032] The first determining unit is used to determine the main geological development zone for shale oil based on the shale oil development effect analysis standards and parameters;
[0033] The second determination unit, combining the shale oil development effect with the main geological development zone, determines the main drilling target for shale oil.
[0034] Preferably, the step of revealing the pure shale oil production capacity characteristics based on the pure shale oil dynamic production curve includes,
[0035] The unit reveals the dynamic production curve of pure shale oil;
[0036] Classify the dynamic production curves of pure shale oil;
[0037] A similarity analysis was performed on the dynamic production curves of pure shale oil after classification.
[0038] Based on the analysis results, the unit reveals the characteristics of pure shale oil production capacity.
[0039] Preferably, the standards and parameters for analyzing the development effect of extracted shale oil include:
[0040] Based on the different pure shale oil production capacity characteristics, establish a mathematical model of production curves and key parameters;
[0041] Based on the production curve and key parameter mathematical model, the extraction unit extracts the evaluation criteria and parameters for shale oil development effectiveness.
[0042] The technical effects and advantages of this invention are as follows:
[0043] 1. By analyzing and evaluating the dynamic production curves of pure shale oil, and using artificial intelligence algorithms for curve classification, similarity matching, and trend prediction, the production capacity characteristics of pure shale oil can be accurately revealed.
[0044] 2. Based on the different pure shale oil production capacity characteristics, use artificial intelligence recurrent neural network algorithms to establish a mathematical model of production curves and key parameters, and extract evaluation standards and parameters for shale oil development effects;
[0045] 3. Based on the three aspects of residual hydrocarbon content, crude oil mobility, and compressibility, the main geological development zones for shale oil are determined;
[0046] 4. By combining the development results of shale oil with the main geological development zones, the main development targets for continental shale oil will be determined to achieve profitable development of pure shale oil; this will provide a basis for the rational optimization of shale oil well network spacing and profitable development.
[0047] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description
[0048] Figure 1 This is a schematic diagram of the process for determining and quantitatively evaluating the main development zones of continental shale oil in an embodiment of the present invention;
[0049] Figure 2a This is the first type of production capacity characteristic curve for pure shale oil in this embodiment of the invention;
[0050] Figure 2b This is the second type of production capacity characteristic curve for pure shale oil in this embodiment of the invention;
[0051] Figure 2c This is the third type of production capacity characteristic curve for pure shale oil in this embodiment of the invention;
[0052] Figure 3 This is a schematic diagram of the Long Short-Term Memory Neural Network algorithm mode in an embodiment of the present invention;
[0053] Figure 4 This is a schematic diagram of the core parameters for geological evaluation of pure shale oil in the Qingshankou Formation of the Songliao Basin in this invention. Detailed Implementation
[0054] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0055] To address the shortcomings of existing technologies, this invention discloses a method for determining and quantitatively analyzing the main development zones for shale oil, combined with... Figure 1 It is understood that the method includes: revealing the production capacity characteristics of pure shale oil based on the dynamic production curve of pure shale oil; extracting shale oil development effect analysis standards and parameters based on different pure shale oil production capacity characteristics; determining the main geological development zone of shale oil based on the shale oil development effect analysis standards and parameters; and determining the main drilling development target of shale oil by combining the shale oil development effect and the main geological development zone.
[0056] Furthermore, the step of revealing the production capacity characteristics of pure shale oil based on the dynamic production curve of pure shale oil includes: obtaining the dynamic production curve of pure shale oil; classifying the dynamic production curve of pure shale oil; performing similarity analysis on the classified dynamic production curve of pure shale oil; and revealing the production capacity characteristics of pure shale oil based on the analysis results.
[0057] The classification of dynamic production curves for pure shale oil includes categorizing them based on their dynamic production curves. This can involve unsupervised clustering or supervised classification, including comparison and classification of similarity between fixed-length and variable-length curves, and trend prediction for single-channel or multi-channel curves. Simultaneously, dynamic production curve similarity analysis is performed using artificial intelligence algorithms for trend prediction. For example, Eulerian distance and MAPE (Modal-Absolute Error Percentage) are used to filter the distance error between two curves, thereby accurately revealing the production capacity characteristics of pure shale oil.
[0058] Furthermore, based on the different pure shale oil production capacity characteristics, emphasizing indicators such as initial production capacity, cumulative production capacity in the first two years, and average daily production during the high-production period, an artificial intelligence recurrent neural network algorithm is used to establish a mathematical model of production curves and key parameters; based on the production curves and key parameter mathematical model, evaluation standards and parameters for shale oil development effectiveness are extracted.
[0059] Furthermore, based on the geological differences of different pure shale oils, and combined with the core geological evaluation parameters such as oil content (retained hydrocarbon content), mobility and compressibility, and lateral scale, the main geological development zones for shale oil are determined from three aspects: retained hydrocarbon content, crude oil mobility, and compressibility.
[0060] Furthermore, by combining the development results of shale oil with the main geological development strata, the main development target for continental shale oil was finally determined, so as to achieve the profitable development of pure shale oil.
[0061] This invention provides a technical method for evaluating and predicting the sweet spot in the development of continental pure shale oil, addressing the problem that existing technologies struggle to comprehensively and accurately select the optimal development targets for different pure shale oils and accurately define evaluation parameters and standards for the sweet spot. By analyzing and determining the dynamic production curves of pure shale oil, and utilizing artificial intelligence algorithms for curve classification, similarity matching, and trend prediction, the method accurately reveals the production capacity characteristics of pure shale oil. Based on the production capacity characteristics of different pure shale oils, an artificial intelligence recurrent neural network algorithm is used to establish a mathematical model of the production curves and key parameters, extracting evaluation standards and parameters for shale oil development effectiveness. The method identifies the main geological development zones for shale oil based on three aspects: residual hydrocarbon content, crude oil mobility, and compressibility. Finally, by combining the shale oil development effectiveness with the main geological development zones, the main development targets for continental shale oil are determined, achieving profitable development of pure shale oil.
[0062] This invention also discloses a system for determining and quantitatively analyzing the main development zones of shale oil, the system comprising:
[0063] The revealing unit is used to reveal the production capacity characteristics of pure shale oil based on the dynamic production curve of pure shale oil.
[0064] The extraction unit is used to extract shale oil development effect analysis standards and parameters based on the different pure shale oil production capacity characteristics;
[0065] The first determining unit is used to determine the main geological development zone for shale oil based on the shale oil development effect analysis standards and parameters;
[0066] The second determination unit, combining the shale oil development effect with the main geological development zone, determines the main drilling target for shale oil.
[0067] Furthermore, the step of revealing the production capacity characteristics of pure shale oil based on the dynamic production curve of pure shale oil includes: the revealing unit acquiring the dynamic production curve of pure shale oil; classifying the dynamic production curve of pure shale oil; performing similarity analysis on the classified dynamic production curve of pure shale oil; and revealing the production capacity characteristics of pure shale oil based on the analysis results.
[0068] Furthermore, the extraction of shale oil development effect analysis standards and parameters includes: establishing a production curve and key parameter mathematical model based on the different pure shale oil production capacity characteristics; and extracting shale oil development effect evaluation standards and parameters based on the production curve and key parameter mathematical model.
[0069] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.
[0070] The technical solutions of the present invention will be further described below with reference to specific embodiments. To more clearly illustrate the technical solutions in the embodiments of this disclosure or in the conventional art, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0071] Breakthroughs in North American shale gas exploration and development have addressed US energy security. Shale oil, as a key area of unconventional oil and gas development, has become a bright spot in global unconventional oil development. my country has a wide distribution of onshore shale, offering broad exploration prospects. National resource assessments indicate that the geological resources of interbedded and laminated shale oil in continental facies amount to 20.1 billion tons, distributed across the Ordos, Songliao, Bohai Bay, and Junggar basins. However, the potential for pure shale oil resources far exceeds these two types; the pure shale oil resources in the Qingshankou Formation in the northern Songliao Basin alone have reached 9.8 billion tons. Accurate quantitative evaluation and prediction of the main development strata are crucial for efficient development.
[0072] Shale oil in the Qingshankou Formation in the northern Songliao Basin is widely distributed, with a resource volume of approximately 98 × 10⁸ t. Breakthroughs have been achieved in the exploration of Gulong Shale Oil. The overall lithology of the Qingshankou Formation is dominated by shale, so the Qingshankou Formation in the Songliao Basin is taken as an example.
[0073] A. Based on the dynamic production curves of pure shale oil in the Songliao Basin, a similarity analysis of the dynamic production curves is conducted. The Euclidean distance formula and MAPE-relative error percentage are used to filter the distance error between the two curves. The following formula is the two-dimensional calculation process of Euclidean distance:
[0074]
[0075]
[0076]
[0077] In the formula, x, y, and z represent points in a dimension, n represents the number of dimensions, and a and b are constants.
[0078] The first line is the standard distance formula between two points in two dimensions. The second line generalizes to a distance formula in three dimensions, and the third line generalizes to a distance formula in multiple dimensions, where the dimensions are the features. Therefore, the distance formula in multiple dimensions can be expressed as:
[0079]
[0080] In the formula, X i Let represent the i-th dimension, n represent the total number of dimensions, and a and b be constants.
[0081] Based on parameters such as daily shale oil production and initial cumulative production, the production capacity characteristics of pure shale oil are divided into three categories ( Figures 2a-2c ):
[0082] like Figure 2a As shown, this illustrates the production characteristics of Type I pure shale oil. Production begins after 100 days, and by 200 days, production has increased dramatically, reaching 40 cubic meters per day. 3 After that, daily oil production began to decline, but after 250 days, daily oil production remained at around 20m³. 3 above.
[0083] like Figure 2b As shown, this illustrates the production characteristics of the second type of pure shale oil. Production begins after 100 days, and by 200 days, production has increased dramatically, reaching 40 cubic meters per day. 3 After that, daily oil production began to decline, continuing until it reached zero after about 225 days.
[0084] like Figure 2c As shown, this illustrates the production characteristics of Type III pure shale oil. Production begins after 150 days of cumulative production, and around 160-170 days, production increases linearly to reach 40 cubic meters per day. 3 After that, daily oil production began to decline, but by the time it reached 2000 days, daily oil production remained at around 20m³. 3 the following.
[0085] Based on the different pure shale oil production characteristics, emphasizing production capacity indicators, and utilizing artificial intelligence recurrent neural network algorithms, such as... Figure 3 As shown, Figure 3 In this context, Xt represents the t-th memory, A represents the information, and ht represents the module output. The previous information A is memorized and applied to the calculation of the current output. That is, the nodes between the hidden layers are connected, and the input of the hidden layer includes not only the output of the input layer but also the output of the hidden layer at the previous time step. A mathematical model of the production curve and key parameters is established, and the evaluation criteria and parameters for shale oil development effect are extracted.
[0086] Therefore, screening initial capacity, cumulative capacity in the first two years, and average daily output during the high-production period are key parameters to reflect pure shale oil production capacity. Figure 4 This paper presents the core parameters for geological evaluation of pure shale oil in the Qingshankou Formation of the Songliao Basin. Based on the geological differences of different pure shale oils and combined with the core geological evaluation parameter of oil content (retained hydrocarbon content), the following parameters are used: Figure 4Based on the evaluation of mobility, compressibility, and lateral scale, considering factors such as retained hydrocarbon content, crude oil mobility, and compressibility, the organic-rich clayey shale is a high-TOC (total organic carbon) shale (4.27%), with an S1 of 2.05% and chloroform A reaching 4.6 mg / g, exhibiting the best oil-bearing properties. The felsic shale is a medium-TOC (2.24%) shale, with an S1 of approximately 1.42% and chloroform A of 3.6 mg / g. Overall, its retained hydrocarbon content is slightly lower than that of the high-TOC shale, but its shale oil has better fluidity. Meanwhile, the high-TOC shale is characterized by organic matter pores, intragranular pores of clay minerals, and intragranular dissolution pores, with small pore sizes and poor pore throat connectivity. NMR analysis of the high-TOC felsic shale shows that the median pore throat radius is less than 0.1 micrometers, and the average effective porosity is 3.2%. The medium-TOC shale exhibits diverse pore types, including intergranular microcracks, dissolution pores, and intragranular pores, with relatively large pores. NMR analysis reveals that the TOC shale has large pore throats, slightly higher effective porosity, a median radius of 4 micrometers for the largest pore throat, and an average effective porosity of 4.8%. It also shows densely developed effective bedding fractures and good permeability. Therefore, the medium-TOC shale (2%–3.5%) (felsic shale) was ultimately determined to be the primary geological development zone for pure shale oil.
[0087] Based on the development effects of initial shale oil production capacity, cumulative production capacity in the first two years, and average daily output during the high-production period, and the favorable sections identified in the geological evaluation results of the main geological development strata, the main development target for continental shale oil was determined to be medium-TOC shale. The goal is to make full use of the upper geological sweet spots with high TOC and high residual hydrocarbon content to achieve profitable development of pure shale oil.
[0088] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
Claims
1. A method for determining and quantitatively analyzing the main development zones of shale oil, characterized in that, The method includes: Based on the dynamic production curve of pure shale oil, the characteristics of pure shale oil production capacity are revealed; Based on the different pure shale oil production capacity characteristics, extract the standards and parameters for shale oil development effect analysis; Based on the shale oil development effect analysis standards and parameters, the main geological development zones for shale oil are determined. The shale oil development effect analysis standards and parameters include the amount of retained hydrocarbons, crude oil mobility, and compressibility. Based on the development results of shale oil and the main geological development zones, the main drilling targets for shale oil were determined; among them, The method of revealing the production capacity characteristics of pure shale oil based on the dynamic production curve of pure shale oil includes, Obtain the dynamic production curve of pure shale oil; The classification of dynamic production curves for pure shale oil includes category classification, unsupervised clustering, or supervised classification; it also includes similarity comparison and classification of curves of fixed or variable length, and trend prediction of single-channel and multi-channel curves. A similarity analysis is performed on the classified pure shale oil dynamic production curves, including using an artificial intelligence algorithm for trend prediction to filter the distance error of two or more similar curves; wherein, the artificial intelligence algorithm for trend prediction includes Eulerian distance and MAPE relative error percentage; The analysis results reveal the characteristics of pure shale oil production capacity; The standards and parameters for analyzing the development effect of extracted shale oil include, Based on the different pure shale oil production capacity characteristics, establish a mathematical model of production curves and key parameters; Based on the production curve and key parameter mathematical model, the evaluation criteria and parameters for shale oil development effectiveness are extracted.
2. The method for determining and quantitatively analyzing the main development zones of shale oil according to claim 1, characterized in that, The establishment of the production curve and key parameter mathematical model includes the following steps. Based on the different production capacity characteristics of pure shale oil, a mathematical model of production curves and key parameters is established using an artificial intelligence recurrent neural network algorithm.
3. The method for determining and quantitatively analyzing the main development zones of shale oil according to claim 2, characterized in that, The characteristics of pure shale oil production capacity include, but are not limited to, one or more of the following: initial production capacity, cumulative production capacity in the first two years, or average daily production during the high-production period.
4. A system for determining and quantitatively analyzing the main development zones of shale oil, characterized in that, The system for implementing the method according to any one of claims 1-3, the system comprising: The revealing unit is used to reveal the production capacity characteristics of pure shale oil based on the dynamic production curve of pure shale oil. The extraction unit is used to extract shale oil development effect analysis standards and parameters based on the different pure shale oil production capacity characteristics; The first determining unit is used to determine the main geological development zone for shale oil based on the shale oil development effect analysis standards and parameters; The second determination unit, combining the shale oil development effect with the main geological development zone, determines the main drilling target for shale oil.
5. The shale oil main development zone determination and quantitative analysis system according to claim 4, characterized in that, The method of revealing the production capacity characteristics of pure shale oil based on the dynamic production curve of pure shale oil includes, The unit reveals the dynamic production curve of pure shale oil; Classify the dynamic production curves of pure shale oil; A similarity analysis was performed on the dynamic production curves of pure shale oil after classification. Based on the analysis results, the unit reveals the characteristics of pure shale oil production capacity.
6. The shale oil main development zone determination and quantitative analysis system according to claim 4, characterized in that, The standards and parameters for analyzing the development effect of extracted shale oil include, Based on the different pure shale oil production capacity characteristics, establish a mathematical model of production curves and key parameters; Based on the production curve and key parameter mathematical model, the extraction unit extracts the evaluation criteria and parameters for shale oil development effectiveness.