A method for identifying gas and water layers in tight sandstone gas reservoirs
By conducting depth relocation and optimization correction of core data of tight sandstone gas reservoirs, combining porosity interpretation model and quadratic relationship profile diagram to identify gas-water layers, the problem of insufficient regularity of water production during the development of tight sandstone gas reservoirs is solved, and the accuracy of fluid recognition is improved.
Patent Information
- Application Number
- CN202411733875.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-29
- Publication Date
- 2025-04-08
AI Technical Summary
During the development process of tight sandstone gas reservoirs, there are high gas barrier water layers and low gas barrier water layers, resulting in less regularity of water production, and it is difficult to choose the opening section, which affects the later production capacity construction and efficient development.
By performing depth relocation and optimization correction on the core data of drilling centering, a logging curve identification pattern was drawn, a porosity interpretation model with acoustic time difference as independent variables was constructed, and a gas-water layer was identified by combining the four-ethnic relationship profile diagram and electrical parameters intersection diagram.
It improves the accuracy of fluid identification and reduces the difficulty of opening the layer segment selection during the development process, which is of great significance to solve the development problem of tight sandstone gas reservoirs.
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Figure CN119784881A_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the technical field of petroleum exploration and development, and relates to a method for identifying gas and water layers in a tight sandstone gas reservoir. Background Art
[0002] In the actual gas testing and production process, tight sandstone gas reservoirs will have high-resistance gas-water layers and low-resistance gas-water layers, and the regularity of their water production is not obvious, which makes it difficult to select the layers to be opened during the development process, and affects the later production capacity construction and efficient development. The identification of gas-water layer types is an important basis for studying the distribution relationship of gas and water in tight sandstone gas reservoirs. In the development process of gas reservoirs, using conventional logging curves to identify fluids is a common logging method in petroleum exploration. At present, conventional gas layer identification technologies include the longitudinal and transverse wave velocity ratio method, the neutron-density intersection method, and the resistivity-porosity comprehensive identification method. However, these methods in the existing technology have a strong risk of failure in some work areas. Summary of the invention
[0003] In order to solve the above problems, the present invention provides a method for identifying tight sandstone gas and water layers with high stability.
[0004] The technical solution of the present invention is: A method for identifying gas and water layers in tight sandstone gas reservoirs is as follows: Step 1: Depth homing of the core data obtained from drilling according to the well logging curve of the target block; Step 2: Draw the well logging curve identification plate of the gas layer, gas-water layer, water layer and dry layer in the low-porosity and low-permeability reservoir; conduct secondary interpretation on the optimized and corrected well logging curve, and draw the four-property relationship profile of the target layer's lithology, physical property, electrical property and gas-bearing property; Step 3: construct a porosity interpretation model with acoustic time difference as the independent variable and reservoir porosity as the dependent variable; the relative error between the porosity interpretation model and the measured porosity does not exceed ±8%; Step 4: Based on the four-property relationship profile and porosity interpretation model, combined with the reservoir characteristics of the target block and the distribution characteristics of the daily production of a single well, draw an electrical parameter intersection diagram to obtain the lower limit value of the logging parameters of the gas and water layers in the target block, thereby effectively identifying the gas and water layers.
[0005] When the core data obtained by drilling is depth-relocated, the target block logging curve is first optimized and corrected, and then the lithology curve, porosity curve and resistivity curve are selected from the optimized and corrected target block logging curve; wherein the lithology curve includes the wellbore logging curve, the natural potential curve, the natural gamma ray spectrum curve and the natural gamma ray curve; the porosity curve includes the sonic time difference curve, the density curve and the neutron logging curve; the resistivity curve includes the deep lateral resistivity curve and the shallow lateral resistivity curve.
[0006] The specific process of depth homing of the core data obtained by drilling is: comparing the measured quartz content with the lithology curve, comparing the measured porosity and measured density with the porosity curve, comparing the measured permeability with the permeability curve, and correcting the core depth to the logging depth. The optimization correction is achieved by the core calibration method.
[0007] The specific process of the secondary interpretation is: correcting the porosity curve with the measured porosity, correcting the permeability curve with the measured permeability, forming a secondary interpretation logging curve, combining the secondary interpretation logging curve with the natural gamma curve, natural potential curve, resistivity curve, lithology profile, and gas test results to draw a cross-sectional diagram of the relationship between the lithology, physical properties, electrical properties, and gas content of the target layer. The permeability curve is obtained through the porosity-permeability relationship curve.
[0008] The porosity interpretation model is established by the method of intersecting the average value of the acoustic wave curve with the corresponding measured porosity.
[0009] The electrical parameter cross-plot is a resistivity-acoustic time difference cross-plot.
[0010] The technical effects of the present invention are: (1) The method for identifying gas and water layers in tight sandstone gas reservoirs provided by the present invention is easy to implement and has strong operability; (2) The present invention greatly improves the accuracy of fluid identification while saving costs; (3) The present invention is of great significance in solving the problems of unclear regularity of water production in actual gas testing and production processes and difficulty in selecting layers to be opened during development. BRIEF DESCRIPTION OF THE DRAWINGS
[0011] Figure 1 This is the core return diagram.
[0012] Figure 2 Well logging curve identification plate for gas layer.
[0013] Figure 3 This is the well logging curve identification plate for the gas and water layers.
[0014] Figure 4 Well logging curve identification plate for dry layer.
[0015] Figure 5 This is a cross-sectional diagram showing the relationship between the target layer’s lithology, physical properties, electrical properties and gas content.
[0016] Figure 6 Explanatory model for porosity.
[0017] Figure 7 This is the error analysis diagram between the reservoir porosity calculated by the porosity interpretation model and the measured porosity.
[0018] Figure 8 This is the resistivity-acoustic time difference cross-plot. DETAILED DESCRIPTION
[0019] A method for identifying gas and water layers in tight sandstone gas reservoirs is as follows: Step 1, obtaining the target block logging curve; and optimizing and correcting the target block logging curve by core calibration method, and selecting lithology curve, porosity curve and resistivity curve from the optimized and corrected target block logging curve; wherein the lithology curve includes wellbore logging curve, natural potential curve, natural gamma spectrum curve and natural gamma curve; the porosity curve includes acoustic wave time difference curve, density curve and neutron logging curve; the resistivity curve includes deep lateral resistivity curve and shallow lateral resistivity curve; Compare the measured quartz content with the lithology curve, compare the measured porosity and density with the porosity curve, compare the measured permeability with the permeability curve, and correct the core depth to the logging depth. Figure 1 shown.
[0020] Step 2: Combine the natural gamma curve and the natural potential curve to identify the reservoir lithology; the natural potential curve of the sandstone layer shows a medium-to-high amplitude negative anomaly; the natural gamma curve value is low and the acoustic time difference value is high; the mudstone layer uses the natural potential curve as the baseline, and the natural gamma curve is a jagged high value; Interpret reservoir properties through acoustic time difference curves, density curves and neutron logging curves; Interpret the gas content of the reservoir through deep lateral resistivity curves and shallow lateral resistivity curves; Combined with production testing, the well logging curve identification charts of low-porosity and low-permeability reservoir gas layers, gas-water layers, water layers and dry layers are drawn; the well logging curve identification charts of gas layers are as follows: Figure 2 , the well logging curve identification chart of gas and water layers is as follows Figure 3 , the well logging curve identification chart of the dry layer is as follows Figure 4 ; The identification basis is as follows: (1) Gas layer: relatively pure lithology, gas-bearing display in logging, good physical properties, low gamma, high acoustic time difference, relatively high resistivity, positive difference or overlap between deep and shallow resistivity, and the compensated neutron and acoustic time difference curves (under the same direction scale), resistivity curve and acoustic time difference curve (under the reverse scale) show "mirror change" characteristics. (2) Water layer: medium to high negative abnormal amplitude natural potential, low natural gamma, low resistivity, high acoustic wave, high neutron. (3) Gas-water layer: high and medium resistivity is usually a high gas-bearing layer, low resistivity is a water layer, and gas-water layers usually show alternation of high resistivity and low resistivity. The gamma value, neutron and density values of the gas-water layer may show certain irregularities, and the gamma ray value may be high while the gas layer resistivity remains high. (4) Dry layer: no display or poor display in logging, high mud content, and poor physical properties. Low resistivity, the resistivity curve and the porosity curve show the characteristic of "changing in the same direction"; The porosity curve is corrected with the measured porosity, and the permeability curve is corrected with the measured permeability to form a secondary interpretation logging curve. Combining the secondary interpretation logging curve with the natural gamma curve, natural potential curve, resistivity curve, lithology profile, and gas test results, a profile diagram of the relationship between the lithology, physical properties, electrical properties, and gas content of the target layer is drawn, such as Figure 5 The reservoir lithology is mainly fine sandstone, with a maximum mud content of 36.65%, a minimum of 4.84%, and an average of 14.23%. The reservoir lithology is relatively pure.
[0021] The first logging interpretation showed that the He 8 reservoir (2542.7-2551.5m) is a gas-water layer, and the Shan 1 reservoir (2560.8-2567.3m) is a gas-water layer.
[0022] Combined with the well logging curve identification plate of the gas layer, the well logging curve identification plate of the gas-water layer and the well logging curve identification plate of the dry layer, the secondary interpretation was carried out. The test gas well section 2544-2548m, 2562-2566m, the daily gas production is 16,540 cubic meters, and almost no water is produced. The natural potential has a certain negative anomaly, the natural gamma value is 40.0-81.2API, and the acoustic wave time difference is 215.7μs / m, which is a low value, indicating that the reservoir permeability is general, and the lateral resistivity of the electrical depth measurement is 126.2Ω·m. Its calculated effective porosity is 5.76%, and the calculated permeability is 0.50×10-3μm 2 , the measured porosity is 5.66%, the measured permeability is 0.43×10-3μm 2 It is a typical gas layer, medium-low porosity, ultra-low permeability, and high resistivity reservoir.
[0023] Step 3: Construct a porosity interpretation model with acoustic time difference as the independent variable and reservoir porosity as the dependent variable, such as Figure 6 As shown; A total of 566 layer points from 26 wells were selected to establish the relationship between the reservoir porosity and acoustic wave time difference of the He 8 member. The formula is as follows: Φ=0.1619Δt-28.394 (R=0.9345, N=566); where Φ is the reservoir porosity, %; Δt is the acoustic wave time difference, μs / m.
[0024] Using the above relationship, the reservoir porosity is calculated by acoustic time difference and compared with the measured porosity. The average absolute error is 0.48% and the average relative error is 3.15%. Figure 7 As shown, the relative error is in line with the regulatory requirement of no more than ±8%, indicating that the above porosity interpretation model can be used for porosity interpretation of effective reservoirs in uncored wells.
[0025] Step 4: Determine the type of gas-water layer based on the four-property relationship profile and porosity interpretation model; draw the resistivity-acoustic time difference crosstalk diagram based on the logging parameter characteristics of the industrial gas flow well and non-industrial gas flow well in the target layer, such as Figure 8 Combining the single-layer gas test or production test data and some interpretation data in the study area, the lower limit values of the well logging parameters of the He 8 gas-water layer are obtained as shown in Table 1.
[0026] As can be seen from Table 1, the resistivity of the gas layer in the He 8 section is greater than 39Ω·m, and the resistivity of the water layer is below 39Ω·m; that is, the lower limit of the resistivity of the gas-water layer is determined to be 39Ω·m. For the He 8 section of the unknown gas reservoir in the same block, when the resistivity is greater than 39Ω·m, it is a gas layer, and when the resistivity is less than 39Ω·m, it is a water layer. Therefore, when selecting the opening layer during the development process, the reservoir with a resistivity below 39Ω·m should be avoided as much as possible.
[0027] The above technical solution is only one implementation of the present invention, and the method is also applicable to different layers in the same research block, as shown in Table 1.
Claims
1. A method for identifying gas and water layers in tight sandstone gas reservoirs, characterized in that: Here’s how: Step 1: Depth homing of the core data obtained from drilling according to the well logging curve of the target block; Step 2: Draw the well logging curve identification plate of the gas layer, gas-water layer, water layer and dry layer in the low-porosity and low-permeability reservoir; conduct secondary interpretation on the optimized and corrected well logging curve, and draw the four-property relationship profile of the target layer's lithology, physical property, electrical property and gas-bearing property; Step 3: construct a porosity interpretation model with acoustic time difference as the independent variable and reservoir porosity as the dependent variable; the relative error between the porosity interpretation model and the measured porosity does not exceed ±8%; Step 4: Based on the four-property relationship profile and porosity interpretation model, combined with the reservoir characteristics of the target block and the distribution characteristics of the daily production of a single well, draw an electrical parameter intersection diagram to obtain the lower limit value of the logging parameters of the gas and water layers in the target block, thereby effectively identifying the gas and water layers.
2. The method for identifying gas and water layers in tight sandstone gas reservoirs according to claim 1, characterized in that: When the core data obtained by drilling is depth-relocated, the target block logging curve is first optimized and corrected, and then the lithology curve, porosity curve and resistivity curve are selected from the optimized and corrected target block logging curve; wherein the lithology curve includes the wellbore logging curve, the natural potential curve, the natural gamma ray spectrum curve and the natural gamma ray curve; the porosity curve includes the sonic time difference curve, the density curve and the neutron logging curve; the resistivity curve includes the deep lateral resistivity curve and the shallow lateral resistivity curve.
3. The method for identifying gas and water layers in tight sandstone gas reservoirs according to claim 2, characterized in that: The specific process of depth tracing of the core data obtained by drilling is as follows: comparing the measured quartz content with the lithology curve, comparing the measured porosity and density with the porosity curve, comparing the measured permeability with the permeability curve, and correcting the core depth to the logging depth according to the maximum similarity.
4. The method for identifying gas and water layers in tight sandstone gas reservoirs according to claim 2, characterized in that: The optimization correction is achieved by core calibration method.
5. The method for identifying gas and water layers in tight sandstone gas reservoirs according to claim 2, characterized in that: The specific process of the secondary interpretation is: correcting the porosity curve with the measured porosity, correcting the permeability curve with the measured permeability, forming a secondary interpretation logging curve, combining the secondary interpretation logging curve with the natural gamma curve, natural potential curve, resistivity curve, lithology profile, and gas testing results to draw a profile diagram of the relationship between the lithology, physical properties, electrical properties, and gas content of the target layer.
6. The method for identifying gas and water layers in tight sandstone gas reservoirs according to claim 5, characterized in that: The permeability curve is obtained through the porosity-permeability relationship curve.
7. The method for identifying gas and water layers in tight sandstone gas reservoirs according to claim 1, characterized in that: The porosity interpretation model is established by the intersection method of the average value of the acoustic wave curve and the corresponding measured porosity.
8. The method for identifying gas and water layers in tight sandstone gas reservoirs according to claim 1, characterized in that: The electrical parameter cross-plot is a resistivity-acoustic time difference cross-plot.