Tight sandstone reservoir helium enrichment evaluation method
By conducting multi-parameter analysis of tight sandstone reservoirs, a helium enrichment evaluation standard was established, which solved the accuracy problem of helium exploration and development, enabled the optimal selection of helium exploration target areas, and improved the efficiency of helium resource exploration.
Patent Information
- Application Number
- CN202411173036.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-26
- Publication Date
- 2026-03-03
AI Technical Summary
Existing technologies cannot effectively guide the enrichment evaluation and exploration of helium resources, and the lack of systematic and in-depth research on helium enrichment sweet spots makes it difficult to conduct helium exploration and development accurately.
By collecting and analyzing physical property data, pore-hound combination type data, pore structure data, and gas composition data of tight sandstone reservoirs, correlation analysis was conducted to classify helium enrichment evaluation criteria and select the best exploration target areas.
It has enabled accurate evaluation of helium-rich reservoirs in tight sandstone, promoted helium exploration and development, alleviated the tight helium supply situation in my country, and achieved independent control of the supply chain.
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Abstract
Description
Technical Field
[0001] This invention belongs to the field of helium exploration technology, specifically relating to a method for evaluating helium enrichment in tight sandstone reservoirs. Background Technology
[0002] Helium is a non-renewable and crucial strategic resource. China heavily relies on imports for helium, with demand growing at an annual rate exceeding 10%. Therefore, conducting geological theory and technological research on helium resources to guide and support China's helium exploration and development has become one of the most urgent tasks in China's resource geology research field. Currently, the enrichment control factors and sweet spot prediction of helium remain significant challenges. While helium and hydrocarbons in natural gas reservoirs share the same reservoir but have different origins, their formation and sources are entirely different. Hydrocarbons originate from sedimentary organic matter, making them organically formed, while helium primarily originates from the radioactive decay of uranium and thorium in bedrock such as granites in the Earth's crust and mantle, making it inorganically formed. Existing oil and gas resource evaluation and prediction technologies are not applicable to helium resource evaluation and prediction, and existing theories of oil and gas genesis and reservoir formation cannot effectively guide helium resource exploration and development. Therefore, continuously strengthening research on helium geological theory and focusing on resolving fundamental geological issues related to helium generation, migration, accumulation, and enrichment mechanisms is currently a primary task and key research direction.
[0003] Previous researchers have systematically analyzed the influencing factors of helium-rich natural gas anomalies in the Weihe River Basin of Shaanxi Province, addressing these critical scientific questions that urgently need to be solved. They concluded that the well-developed fault system not only provides connecting channels for helium migration but also releases helium during activity, creating favorable spaces for local helium accumulation. Other scholars have clarified that helium in oil and gas basins in central and western my country is primarily of crustal radiogenic origin, with its enrichment controlled by the distribution of U and Th-rich acidic rocks or basements, anticline traps, and faults, leading to the discovery of my country's first super-large helium-rich field. For areas with low helium exploration levels, some researchers have focused on helium sources, calculating helium generation rates and quantities, mantle-derived helium input ratios, and regional average mantle-derived helium input ratios to determine the helium exploration range. Others have addressed low-exploration areas by unitizing helium source quantities, calculating the helium production based on experimental data of uranium and thorium abundance in certain units, and comprehensively considering helium discharge and transport distance coefficients, using geological analogy to effectively evaluate helium resources in low-exploration areas.
[0004] Currently reviewed patents include those by scholars focusing on helium exploration in low-exploration areas and regions where helium reserves are unknown and cannot be assessed, primarily using single-factor analysis of helium production from basement metamorphic rocks. However, comprehensive research on the generation, transport, and storage of helium-enriched sweet spots is lacking. Other studies have explored global helium reservoir types and distribution, summarizing three different types of helium-rich natural gas reservoirs in basin margins and internal uplift areas: helium-rich hydrocarbon reservoirs, helium-rich carbon dioxide reservoirs, and helium-rich nitrogen reservoirs. These studies analyze the formation models of helium-rich natural gas reservoirs and predict favorable exploration areas based on the basement, faults, and caprocks. However, there is a lack of predictions for helium exploration sweet spots in mature exploration areas and a systematic, in-depth study of helium reservoirs. Summary of the Invention
[0005] The purpose of this invention is to provide a method for evaluating helium enrichment in tight sandstone reservoirs, and to classify the helium enrichment in tight sandstone reservoirs according to the classification criteria, providing an important basis for accurate evaluation of helium reservoirs and selection of favorable areas.
[0006] The technical solution adopted in this invention is a method for evaluating helium enrichment in tight sandstone reservoirs, comprising the following steps:
[0007] S1. Collect physical property data, pore structure data, and gas composition data of the helium-bearing strata in the study area that affect the percentage of helium content; collect the percentage of helium content in the helium-bearing strata in the study area.
[0008] S2. Perform correlation analysis between physical property data and helium percentage content, and classify the reservoir based on physical property data; perform correlation analysis between pore structure data and helium percentage content, and classify the reservoir based on pore structure data; perform correlation analysis between gas composition data and helium percentage content, and classify the reservoir based on gas composition data.
[0009] S3. Based on the classification results, a helium enrichment evaluation table for tight sandstone reservoirs is obtained.
[0010] S4. Select areas based on the evaluation form, and prioritize the "sweet spot" helium reservoirs for exploration and development.
[0011] The invention is further characterized by:
[0012] The physical property data in S1 includes porosity and permeability.
[0013] The specific process of performing correlation analysis between physical property data and helium percentage content and classifying reservoirs in S2 is as follows: Correlation analysis is performed between porosity and permeability and helium percentage content, respectively, and the correlation coefficient R is calculated. 2Under conditions of >80%, the helium content is divided into four categories: Category I (0%–25%), Category II (25%–50%), Category III (50%–75%), and Category IV (75%–100%). Based on the correlation between the four categories of helium content and porosity and permeability, porosity and permeability are also divided into four categories.
[0014] The pore type data in S1 includes porosity, pore type, and main seepage channel type.
[0015] The specific process of performing correlation analysis between pore size combination type data and helium percentage content and classifying reservoirs based on pore size combination type data in S2 is as follows: Correlation analysis is performed between porosity, pore type, and main flow channel type and helium percentage content, respectively, and the correlation coefficient R is calculated. 2 Under conditions of >80%, the helium content is divided into four categories: Category I (0%–25%), Category II (25%–50%), Category III (50%–75%), and Category IV (75%–100%). Based on the correlation between the four categories of helium content and porosity, pore type, and main seepage channel type, porosity, pore type, and main seepage channel type are also divided into four categories.
[0016] The pore structure data in S1 includes the displacement pressure, pore radius, and main flow throat radius.
[0017] The specific process of performing correlation analysis between pore structure data and helium percentage content and classifying reservoirs based on pore structure data in S2 is as follows: Correlation analysis is performed on the displacement pressure, pore radius, and main channel throat radius with helium percentage content, respectively, and the correlation coefficient R is calculated. 2 Under conditions of >80%, the helium content is divided into four categories: Category I (0%–25%), Category II (25%–50%), Category III (50%–75%), and Category IV (75%–100%). Based on the correlation between the four categories of helium content and the displacement pressure, pore radius, and mainstream throat radius, the displacement pressure, pore radius, and mainstream throat radius are also divided into four categories.
[0018] Gas composition data in S1 includes 20 Ne gas content and N2 content.
[0019] The specific process of performing correlation analysis between gas component data and helium percentage content and classifying gas component data reservoirs in S2 is as follows: ... 20 Correlation analysis was performed between Ne gas content, N2 content and helium percentage content, with correlation coefficient R0.2 Under conditions of >80%, helium content is divided into four categories: Category I (0%–25%), Category II (25%–50%), Category III (50%–75%), and Category IV (75%–100%). Based on these four categories of helium content... 20 The correlation between Ne gas content and N2 content will 20 Both Ne gas content and N2 content are divided into four categories.
[0020] The beneficial effects of this invention are:
[0021] The method for evaluating helium enrichment in tight sandstone reservoirs provided by this invention analyzes the correlation between reservoir properties, pore-hound combination type, pore microstructure, gas composition parameters, and helium content—the main controlling factors of tight sandstone helium reservoirs—and the helium content. This enables a multi-parameter comprehensive evaluation of helium-enriched tight sandstone reservoirs, thereby more accurately determining the evaluation criteria for helium-enriched reservoirs. The classification and evaluation results are accurate and reasonable, which can promote the exploration and development of the helium industry. Furthermore, using the method of this application to conduct technical evaluation of helium reservoir selection and optimize exploration target areas can effectively alleviate the tight helium supply situation in my country and achieve independent control over the core links of my country's supply chain. Attached Figure Description
[0022] Figure 1 The percentage of helium in Example 4 and 20 Ne content relationship diagram;
[0023] Figure 2 This is a graph showing the relationship between the percentage of helium and the amount of N2 in Example 4. Detailed Implementation
[0024] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.
[0025] Example 1
[0026] The method for evaluating helium enrichment in tight sandstone reservoirs proposed in this embodiment includes the following steps:
[0027] S1. Collect physical property data, pore structure data, and gas composition data of the helium-bearing strata in the study area that affect the percentage of helium content; collect the percentage of helium content in the helium-bearing strata in the study area.
[0028] S2. Perform correlation analysis between physical property data and helium percentage content, and classify the reservoir based on physical property data; perform correlation analysis between pore structure data and helium percentage content, and classify the reservoir based on pore structure data; perform correlation analysis between gas composition data and helium percentage content, and classify the reservoir based on gas composition data.
[0029] S3. Based on the classification results, a helium enrichment evaluation table for tight sandstone reservoirs is obtained.
[0030] S4. Select areas based on the evaluation form, and prioritize the "sweet spot" helium reservoirs for exploration and development.
[0031] Example 2
[0032] The method for evaluating helium enrichment in tight sandstone reservoirs proposed in this embodiment includes the following steps:
[0033] S1. Collect physical property data, pore structure data, and gas composition data of the helium-bearing strata in the study area that affect the percentage of helium content; collect the percentage of helium content in the helium-bearing strata in the study area.
[0034] Physical property data include porosity and permeability;
[0035] The pore type data includes porosity, pore type, and main seepage channel type;
[0036] Pore structure data includes displacement pressure, pore radius, and mains throat radius;
[0037] Gas composition data includes 20 Ne gas content and N2 content;
[0038] S2. Perform correlation analysis between physical property data and helium percentage content, and classify the reservoir based on physical property data; perform correlation analysis between pore structure data and helium percentage content, and classify the reservoir based on pore structure data; perform correlation analysis between gas composition data and helium percentage content, and classify the reservoir based on gas composition data.
[0039] S3. Based on the classification results, a helium enrichment evaluation table for tight sandstone reservoirs is obtained.
[0040] S4. Select areas based on the evaluation form, and prioritize the "sweet spot" helium reservoirs for exploration and development.
[0041] Example 3
[0042] The method for evaluating helium enrichment in tight sandstone reservoirs proposed in this embodiment includes the following steps:
[0043] S1. Collect physical property data, pore structure data, and gas composition data of the helium-bearing strata in the study area that affect the percentage of helium content; collect the percentage of helium content in the helium-bearing strata in the study area.
[0044] Physical property data include porosity and permeability;
[0045] The pore type data includes porosity, pore type, and main seepage channel type;
[0046] Pore structure data includes displacement pressure, pore radius, and mains throat radius;
[0047] Gas composition data includes 20 Ne gas content and N2 content;
[0048] S2. Perform correlation analysis between physical property data and helium percentage content, and classify the reservoir based on physical property data; perform correlation analysis between pore structure data and helium percentage content, and classify the reservoir based on pore structure data; perform correlation analysis between gas composition data and helium percentage content, and classify the reservoir based on gas composition data.
[0049] The specific process of performing correlation analysis between physical property data and helium percentage content and classifying the reservoir based on physical property data is as follows: Correlation analysis is performed between porosity and permeability and helium percentage content, respectively, and the correlation coefficient R is calculated. 2 Under conditions of >80%, the helium content is divided into four categories: Category I (0%–25%), Category II (25%–50%), Category III (50%–75%), and Category IV (75%–100%). Based on the correlation between the four categories of helium content and porosity and permeability, porosity and permeability are also divided into four categories.
[0050] The specific process of performing correlation analysis between pore size combination type data and helium percentage content and classifying reservoirs based on pore size combination type data is as follows: Correlation analysis is performed between porosity, pore type, and main flow channel type and helium percentage content, respectively. The correlation coefficient R0 is then used to determine the reservoir type. 2 Under conditions of >80%, the helium content is divided into four categories: Category I (0%–25%), Category II (25%–50%), Category III (50%–75%), and Category IV (75%–100%). Based on the correlation between the four categories of helium content and porosity, pore type, and main seepage channel type, porosity, pore type, and main seepage channel type are also divided into four categories.
[0051] The specific process of performing correlation analysis between pore structure data and helium percentage content and classifying reservoirs based on pore structure data is as follows: Correlation analysis is performed on the displacement pressure, pore radius, and main channel throat radius with the helium percentage content, respectively, and the correlation coefficient R is calculated. 2 Under conditions of >80%, the helium content is divided into four categories: Category I (0%–25%), Category II (25%–50%), Category III (50%–75%), and Category IV (75%–100%). Based on the correlation between the four categories of helium content and the displacement pressure, pore radius, and mainstream throat radius, the displacement pressure, pore radius, and mainstream throat radius are also divided into four categories.
[0052] The specific process of performing correlation analysis between gas composition data and helium percentage content, and classifying gas composition data into reservoirs, is as follows: 20 Correlation analysis was performed between Ne gas content, N2 content and helium percentage content, with correlation coefficient R0. 2 Under conditions of >80%, helium content is divided into four categories: Category I (0%–25%), Category II (25%–50%), Category III (50%–75%), and Category IV (75%–100%). Based on these four categories of helium content... 20 The correlation between Ne gas content and N2 content will 20 Both Ne gas content and N2 content are divided into four categories;
[0053] S3. Based on the classification results, a helium enrichment evaluation table for tight sandstone reservoirs is obtained.
[0054] S4. Select areas based on the evaluation form, and prioritize the "sweet spot" helium reservoirs for exploration and development.
[0055] Example 4
[0056] This embodiment describes a method for evaluating helium enrichment in tight sandstone reservoirs in a specific area of a basin, including the following steps:
[0057] S1. Collect physical property data, pore structure data, and gas composition data of the helium-bearing strata in the study area that affect the percentage of helium content; collect the percentage of helium content in the helium-bearing strata in the study area.
[0058] Physical property data include porosity and permeability;
[0059] The pore type data includes porosity, pore type, and main seepage channel type;
[0060] Pore structure data includes displacement pressure, pore radius, and mains throat radius;
[0061] Gas composition data includes 20 Ne gas content and N2 content;
[0062] S2. Perform correlation analysis between physical property data and helium percentage content, and classify the reservoir based on physical property data; perform correlation analysis between pore structure data and helium percentage content, and classify the reservoir based on pore structure data; perform correlation analysis between gas composition data and helium percentage content, and classify the reservoir based on gas composition data.
[0063] The specific process of performing correlation analysis between physical property data and helium percentage content and classifying the reservoir based on physical property data is as follows: Correlation analysis is performed between porosity and permeability and helium percentage content, respectively, and the correlation coefficient R is calculated. 2 Under conditions of >80%, the helium content is divided into four categories: Category I (0%–25%), Category II (25%–50%), Category III (50%–75%), and Category IV (75%–100%). Based on the correlation between the four categories of helium content and porosity and permeability, porosity and permeability are also divided into four categories.
[0064] The specific process of performing correlation analysis between pore size combination type data and helium percentage content and classifying reservoirs based on pore size combination type data is as follows: Correlation analysis is performed between porosity, pore type, and main flow channel type and helium percentage content, respectively. The correlation coefficient R0 is then used to determine the reservoir type. 2 Under conditions of >80%, the helium content is divided into four categories: Category I (0%–25%), Category II (25%–50%), Category III (50%–75%), and Category IV (75%–100%). Based on the correlation between the four categories of helium content and porosity, pore type, and main seepage channel type, porosity, pore type, and main seepage channel type are also divided into four categories.
[0065] The specific process of performing correlation analysis between pore structure data and helium percentage content and classifying reservoirs based on pore structure data is as follows: Correlation analysis is performed on the displacement pressure, pore radius, and main channel throat radius with the helium percentage content, respectively, and the correlation coefficient R is calculated. 2Under conditions of >80%, the helium content is divided into four categories: Category I (0%–25%), Category II (25%–50%), Category III (50%–75%), and Category IV (75%–100%). Based on the correlation between the four categories of helium content and the displacement pressure, pore radius, and mainstream throat radius, the displacement pressure, pore radius, and mainstream throat radius are also divided into four categories.
[0066] The specific process of performing correlation analysis between gas composition data and helium percentage content, and classifying gas composition data into reservoirs, is as follows: 20 Correlation analysis was performed between Ne gas content, N2 content and helium percentage content, as follows: Figure 1 , 2 As shown, in the correlation coefficient R 2 Under conditions of >80%, helium content is divided into four categories: Category I (0%–25%), Category II (25%–50%), Category III (50%–75%), and Category IV (75%–100%). Based on these four categories of helium content... 20 The correlation between Ne gas content and N2 content will 20 Both Ne gas content and N2 content are divided into four categories;
[0067] S3. Based on the classification results, the evaluation table of helium enrichment in tight sandstone reservoirs is obtained, as shown in Table 1.
[0068] Table 1. Evaluation Criteria for Helium Enrichment in Tight Sandstone Reservoirs at a Certain Stratum in a Certain Area of a Basin
[0069]
[0070] S4. Select areas based on the evaluation form, and prioritize the "sweet spot" helium reservoirs for exploration and development.
Claims
1. A method for evaluating helium enrichment in tight sandstone reservoirs, characterized in that, Includes the following steps: S1. Collect physical property data, pore structure data, and gas composition data of the helium-bearing strata in the study area that affect the percentage of helium content; collect the percentage of helium content in the helium-bearing strata in the study area. S2. Perform correlation analysis between physical property data and helium percentage content, and classify the reservoir based on physical property data; perform correlation analysis between pore structure data and helium percentage content, and classify the reservoir based on pore structure data; perform correlation analysis between gas composition data and helium percentage content, and classify the reservoir based on gas composition data. S3. Based on the classification results, a helium enrichment evaluation table for tight sandstone reservoirs is obtained. S4. Select areas based on the evaluation form, and prioritize the exploration and development of "sweet spot" helium reservoirs.
2. The method for evaluating helium enrichment in tight sandstone reservoirs according to claim 1, characterized in that, The physical property data mentioned in S1 include porosity and permeability.
3. The method for evaluating helium enrichment in tight sandstone reservoirs according to claim 2, characterized in that, The specific process described in S2 for performing correlation analysis between physical property data and helium percentage content and classifying the reservoir based on physical property data is as follows: Correlation analysis is performed between porosity and permeability and helium percentage content, respectively, and the correlation coefficient R... 2 Under conditions of >80%, the helium content is divided into four categories: Category I (0%–25%), Category II (25%–50%), Category III (50%–75%), and Category IV (75%–100%). Based on the correlation between the four categories of helium content and porosity and permeability, porosity and permeability are also divided into four categories.
4. The method for evaluating helium enrichment in tight sandstone reservoirs according to claim 1, characterized in that, The pore combination type data described in S1 includes porosity, pore type, and main seepage channel type.
5. The method for evaluating helium enrichment in tight sandstone reservoirs according to claim 4, characterized in that, The specific process described in S2 for performing correlation analysis between pore size combination type data and helium percentage content and classifying reservoirs based on pore size combination type data is as follows: Correlation analysis is performed between porosity, pore type, and main flow channel type and helium percentage content, respectively, and the correlation coefficient R is calculated. 2 Under conditions of >80%, the helium content is divided into four categories: Category I (0%–25%), Category II (25%–50%), Category III (50%–75%), and Category IV (75%–100%). Based on the correlation between the four categories of helium content and porosity, pore type, and main seepage channel type, porosity, pore type, and main seepage channel type are also divided into four categories.
6. The method for evaluating helium enrichment in tight sandstone reservoirs according to claim 1, characterized in that, The pore structure data described in S1 includes the displacement pressure, pore radius, and main flow throat radius.
7. The method for evaluating helium enrichment in tight sandstone reservoirs according to claim 6, characterized in that, The specific process described in S2 for performing correlation analysis between pore structure data and helium percentage content and classifying reservoirs based on pore structure data is as follows: Correlation analysis is performed between displacement pressure, pore radius, and main channel throat radius and helium percentage content, respectively, and the correlation coefficient R... 2 Under conditions of >80%, the helium content is divided into four categories: Category I (0%–25%), Category II (25%–50%), Category III (50%–75%), and Category IV (75%–100%). Based on the correlation between the four categories of helium content and the displacement pressure, pore radius, and mainstream throat radius, the displacement pressure, pore radius, and mainstream throat radius are also divided into four categories.
8. The method for evaluating helium enrichment in tight sandstone reservoirs according to claim 1, characterized in that, The gas composition data mentioned in S1 includes 20 Ne gas content and N2 content.
9. The method for evaluating helium enrichment in tight sandstone reservoirs according to claim 8, characterized in that, The specific process described in S2 for performing correlation analysis between gas component data and helium percentage content and classifying gas component data reservoirs is as follows: ... 20 Correlation analysis was performed between Ne gas content, N2 content and helium percentage content, with correlation coefficient R0. 2 Under conditions of >80%, helium content is divided into four categories: Category I (0%–25%), Category II (25%–50%), Category III (50%–75%), and Category IV (75%–100%). Based on these four categories of helium content... 20 The correlation between Ne gas content and N2 content will 20 Both Ne gas content and N2 content are divided into four categories.