CN110688781A - Well logging interpretation method for low-permeability heterogeneous gas reservoir - Google Patents
Well logging interpretation method for low-permeability heterogeneous gas reservoir Download PDFInfo
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Abstract
The invention discloses a logging interpretation method for a low-permeability heterogeneous gas reservoir, which is used for determining the lower physical limit and the lower electrical limit of the low-permeability heterogeneous gas reservoir by processing and analyzing logging data of a research block on the basis of recognizing relevant geological data of the research block. And then the logging interpretation method of the reservoir parameters is summarized, and the stability of the current logging interpretation of the low-permeability heterogeneous gas reservoir can be improved by the method.
Description
Technical Field
The invention belongs to the technical field of unconventional reservoir logging interpretation and evaluation, and relates to a hypotonic heterogeneous gas reservoir logging interpretation method.
Background
The well logging data interpretation and reservoir evaluation of low-porosity and low-permeability reservoirs are always difficult problems in various oil fields at home and abroad. The differences of the sedimentary environment, sedimentary facies zones and diagenetic actions lead to low porosity, various pore types of low permeability reservoirs, complex pore structures and strong reservoir heterogeneity. The extremely strong heterogeneity and the complex pore structure control the fluid percolation capacity and the electric conduction capacity of low-pore and low-permeability reservoirs, and directly influence the physical parameters of the reservoirs and the electrical response characteristics of oil, gas and water layers.
Theoretically, the gas and water layers can be identified by using the combination of acoustic time difference and resistivity logging. For the gas layer, both apparent resistivity and acoustic time difference show high values; for the water layer, the apparent resistivity and the difference in acoustic wave time are low relative to those for the gas layer. However, for a reservoir with low formation water mineralization, the low formation water mineralization causes the apparent resistivity difference between an air layer and a water layer on a logging curve to be not obvious, and the apparent resistivity of the water layer of a certain interval is larger than that of the air layer. The acoustic wave time difference can be in a loose gas-containing sandstone layer section, and the phenomenon of cycle jump exists, so that the defect of poor stability of acoustic logging in gas and water layer identification exists.
Disclosure of Invention
The invention aims to provide a low-permeability heterogeneous gas reservoir logging interpretation method with high stability.
The invention is realized by the following technical scheme:
a well logging interpretation method for a hypotonic heterogeneous gas reservoir comprises the following steps:
step 1: selecting logging data of a target oil field block, and optimally selecting the logging data in the logging data; the method comprises the steps of homing a core of a core well, testing and testing the core to obtain analysis porosity, permeability, gas saturation and shale content data of the core and determine lithology characteristics and sedimentation characteristics of the core;
and step 3: dividing the stratum into small layers by the lithology characteristics and the sedimentation characteristics of the rock core and the logging curve characteristics of lithology series logging data of a plurality of wells, and performing depth division on the logging data of the small layers;
and 4, step 4: distinguishing analysis porosity, permeability, gas saturation and shale content data of different small rock cores of a target oil field block, lithological characteristics of the rock cores, and oil testing data of different small rock cores after deep division; determining logging interpretation models and physical property lower limits of different small-layer reservoir parameters by combining logging data;
and 5: counting the test gas data of different small layers, distinguishing a gas layer, a gas-difference layer, a gas-water layer and a water layer, and making quantitative identification charts of different types of reservoirs by combining with a logging data chart; according to the qualitative judgment of the reservoir fluid properties in the step 2, determining the lower electrical limits of various reservoirs of different small layers by combining with a quantitative identification chart;
step 6: and (5) logging and secondarily explaining various reservoirs of different stratums through the lower electrical limit and the lower physical limit obtained in the step (4) and the step (5).
Further, optimizing and selecting lithology series, porosity series and resistivity series logging data from the logging data in the step 1; lithology series including natural potential, natural gamma, caliper log and natural gamma energy spectrum; porosity series includes density logs, sonic moveout, and neutron logs; the resistivity series included lateral logs, induction logs, microresistivity logs, and the R025, R045, R2.5, and R4 series apparent resistivity logs.
Further, in the step 1, the core homing adopts the acoustic time difference curve as a reference to carry out depth correction on the core analysis porosity; and performing depth correction on the shale content of the core analysis by taking a natural gamma curve as a reference.
Further, the well logging interpretation model of the reservoir parameters in the step 4 comprises an interpretation model of the shale content, an interpretation model of the porosity, an interpretation model of the permeability and an interpretation model of the gas saturation.
Further, the calculation method of the interpretation model of the argillaceous content is as follows:
wherein, VshIs the volume content of the argillaceous substance; GCUR is Hilbert index, 3.7 is taken as a new stratum, and 2.0 is taken as an old stratum; i isGRIs a natural gamma relative value; GR, GRmin、GRmaxThe natural gamma values of the target layer, the pure sandstone layer and the pure shale layer are respectively.
Further, the porosity explanation model is preferably obtained from the correlation between the core analysis porosity and the porosity series logging data; the correlation between the porosity of the core analysis and the series of the porosity logging data comprises a core analysis porosity-acoustic wave time difference cross plot, a core analysis porosity-density cross plot and a core analysis porosity-neutron porosity cross plot.
Further, the explained model of the permeability is to make porosity and permeability distribution charts of different small-layer core analyses to determine the explained model of the permeability and the porosity, and the explained model of the permeability is obtained based on the explained model of the porosity.
Further, the explanation model of the gas saturation is an explanation model of the gas saturation determined by the explanation model of the permeability through the relation chart of the water saturation and the permeability of the closed core data of different stratums.
Further, in the step 4, the lower physical property limit is the lower physical property limit of the reservoir stratum of different layers determined by a relation curve of porosity to gas production per unit thickness, a relation curve of permeability to gas production per unit thickness and a porosity to reservoir capacity loss chart in the test gas data.
Further, in the step 5, the test gas data of different layers are counted, and a gas layer, a gas difference layer, a gas-water layer and a water layer are distinguished, and the quantitative identification charts of different types of reservoirs are made by combining the logging data charts; the logging data chart comprises a natural potential relative value and neutron porosity intersection chart, a sound wave time difference and density intersection chart, a microelectrode amplitude difference ratio value and lateral resistivity amplitude difference ratio chart, an RL3S/RL3D and density intersection chart, a water saturation and R025/Rm intersection chart, a sound wave time difference and RL3S/RL3D intersection chart, an RL3S and RL3D intersection chart, a natural potential relative value and well diameter reduction coefficient intersection chart, and an R0.25/Rm and RL3S/RL3D intersection chart.
Compared with the prior art, the invention has the following beneficial technical effects:
the invention provides a well logging interpretation method for a hypotonic heterogeneous gas reservoir, which introduces △ phi ═ phiD-φN△ phi is larger than zero and can qualitatively judge that the reservoir fluid is natural gas, △ phi is smaller than zero and can qualitatively judge that the reservoir fluid is stratum water, thereby being capable of qualitatively judging stratum fluid properties, in addition, by making a distribution chart of porosity, shale content data and gas saturation and logging data of a core and combining test oil data and closed coring data of different stratums, an explanation model of stratum physical property parameters is obtained, further, the physical property lower limit of the stratum is determined, then, the preferred result of the correlation between the porosity and porosity series logging data is analyzed through the core, the electrical lower limits of various reservoirs of different stratums are determined, secondary explanation is carried out on the stratum through the physical property lower limit and the electrical lower limit of the stratum, the stability of gas reservoir explanation is improved through multi-standard logging explanation of the stratum, the layered evaluation is carried out on the reservoir, refined explanation models of different stratums are established, the accuracy of logging explanation is also improved, meanwhile, the matching between the logging data and the test oil data is better, the more the core data is tested, the more the gas series is established, the more the stability of the reservoir is improved through the method of the invention, the stability of the reservoir stratum is improved through the method of logging interpretation of the present invention, the method of reservoir stability of reservoir is carried out on the reservoir by the methodThe model further determines the physical property lower limit and the electrical property lower limit of the reservoir, can realize qualitative and quantitative evaluation and description of the gas-water layer, realizes fine description of the heterogeneous gas reservoir, can be applied to secondary explanation of the reservoir and primary explanation of the reservoir, and improves the application range of the method.
Furthermore, an interpretation model of the shale content is established through the good correlation between the natural gamma value and the shale content, and the interpretation precision of the stratum is improved.
Drawings
FIG. 1 is a qualitative identification chart of reservoir gas-water layer;
FIG. 2 is a cross plot of core analysis porosity-acoustic time difference logging data;
FIG. 3 is a cross plot of core analysis porosity-density log data;
FIG. 4 is a cross-plot of core analysis porosity-neutron logging data;
FIG. 5 is a chart of core analysis porosity-permeability;
FIG. 6 is a chart of water saturation vs. permeability for core analysis;
FIG. 7 is a porosity versus reservoir capacity loss chart;
FIG. 8 is a graph showing the relationship between permeability and gas production per unit thickness;
FIG. 9 is a graph showing the relationship between porosity and gas production per unit thickness;
FIG. 10 is a plot of natural potential versus neutron porosity;
FIG. 11 is a cross plot of the relative value of the natural potential and the reduction coefficient of the borehole diameter;
FIG. 12 is a plot of microelectrode amplitude difference ratio vs. lateral resistivity amplitude difference ratio;
FIG. 13 is a plot of acoustic time difference versus density;
FIG. 14 is a plot of water saturation versus R025/Rm;
FIG. 15 is a diagram of the intersection of RL3S and RL 3D;
FIG. 16 is a graph of RL3S/RL3D intersecting density;
FIG. 17 is a graph of the sonic time difference intersecting RL3S/RL 3D;
FIG. 18 is a graph of the intersection of R0.25/Rm with RL3S/RL 3D.
Detailed Description
Specific examples are given below, which illustrate the method using a certain oilfield block as an example.
A well logging interpretation method for a hypotonic heterogeneous gas reservoir comprises the following steps:
step 1: selecting logging data of a target oil field block, and optimizing and selecting the logging data in the logging data by lithology series, porosity series and resistivity series; the lithology series comprises natural potential, natural gamma, borehole diameter and natural gamma logging data; the porosity series includes density, acoustic moveout, and neutron log data; the resistivity series comprises lateral logging, induction logging, micro-resistivity and R0.25, R0.45, R2.5 and R4 logging data;
the core of the core well is reset, and the depth correction is carried out on the core analysis porosity by taking the acoustic time difference curve as a reference; performing depth correction on the shale content of the core analysis by taking a natural gamma curve as a reference; the method comprises the steps of selecting 31 coring wells to carry out core homing, wherein the depth of a core is 1700-2100 m, the homing correction value is up to 2.6m at most, and the homing correction error analysis rule and the homing correction error correction range are met;
testing and testing the core of the core well to obtain the data of the analysis porosity, permeability, water saturation and shale content of the core and determine the lithology characteristic and sedimentation characteristic of the core;
and step 3: dividing a stable mud rock stratum by combining the lithological characteristics and the sedimentation characteristics of the rock core and the logging curve characteristics of lithological series logging data of a plurality of wells, subdividing the stratum by the mud rock stratum to obtain small layers, and performing depth division on the logging data of each well by the small layers;
and step 3: distinguishing rock core analysis porosity, permeability, gas saturation, shale content data and lithology characteristics of different small layers of a target oil field block; determining logging interpretation models of different small-layer reservoir parameters by combining logging data;
the well logging interpretation models of different stratum parameters comprise an interpretation model of the shale content, an interpretation model of the porosity, an interpretation model of the permeability and an interpretation model of the gas saturation;
the calculation method of the interpretation model of the argillaceous content comprises the following steps:
wherein, VshIs the volume content of the argillaceous substance; GCUR is Hilbert index, 3.7 is taken as a new stratum, and 2.0 is taken as an old stratum; i isGRIs a natural gamma relative value; GR, GRmin、GRmaxRespectively for the purposeNatural gamma values for layers, pure sandstone formations, and pure shale formations.
The porosity explanation model is preferably obtained through correlation between core analysis porosity and porosity series logging data, and specifically, as shown in fig. 2 to 4, the porosity explanation model is preferably obtained from a core analysis porosity-acoustic wave time difference intersection graph, a core analysis porosity-density intersection graph and a core analysis porosity-neutron porosity intersection graph;
and (3) making distribution charts of the porosity and the permeability of different small layers according to the data of the core analysis, obtaining an explanation model of the permeability-porosity as shown in figure 5, and obtaining the explanation model of the permeability based on the porosity explanation model.
Making an explanation model of water saturation and permeability according to the relation between the water saturation and the permeability of the closed core data of different stratums as shown in figure 6, and further obtaining an explanation model of gas saturation through the explanation model of water saturation; gas saturation of 100% to water saturation in oil-free formations;
as shown in fig. 7 to 9, the graph of porosity to gas production per unit thickness, the graph of permeability to gas production per unit thickness, and the graph of porosity to gas storage capacity loss are then used to obtain the gas data; determining physical property lower limits of various reservoirs of different stratums;
and 5: according to the qualitative judgment of the reservoir fluid properties in the step 2, determining the electrical lower limits of various reservoirs of different small layers by combining with a quantitative identification chart; counting the test gas data of different small layers, distinguishing a gas layer, a gas-difference layer, a gas-water layer and a water layer, and making quantitative identification charts of different types of reservoirs by combining with a logging data chart; as shown in fig. 10 to 18, the log data plate includes a graph of natural potential relative values and neutron porosity, a graph of sonic time difference and density, a graph of microelectrode amplitude difference ratio and lateral resistivity amplitude difference ratio, a graph of RL3S/RL3D and density, a graph of water saturation and R025/Rm, a graph of sonic time difference and RL3S/RL3D, a graph of RL3S and RL3D, a graph of natural potential relative values and well diameter reduction factor, and a graph of R025/Rm and RL3S/RL 3D;
step 6: and (5) logging and secondarily explaining various reservoirs of different stratums through the lower electrical limit and the lower physical limit obtained in the step (4) and the step (5).
Claims (10)
1. A well logging interpretation method for a hypotonic heterogeneous gas reservoir is characterized by comprising the following steps:
step 1: selecting logging data of a target oil field block, and optimally selecting the logging data in the logging data; the method comprises the steps of homing a core of a core well, testing and testing the core to obtain analysis porosity, permeability, gas saturation and shale content data of the core and determine lithology characteristics and sedimentation characteristics of the core;
step 2, introducing a dual-porosity difference method △ phi to phiD-φNWherein phiDPorosity, phi, calculated for density values obtained from density logsNThe method comprises the steps of calculating the porosity by using apparent neutron porosity obtained by compensated neutron logging, and qualitatively analyzing a reservoir by using comprehensive test gas data so as to analyze the △ phi numerical characteristics corresponding to a gas layer, a gas-water layer and a water layer and qualitatively distinguish response characteristics of different fluids △ phi in the reservoir of the stratum;
and step 3: dividing the stratum into small layers by the lithology characteristics and the sedimentation characteristics of the rock core and the logging curve characteristics of lithology series logging data of a plurality of wells, and performing depth division on the logging data of the small layers;
and 4, step 4: distinguishing analysis porosity, permeability, gas saturation and shale content data of different small rock cores of a target oil field block, lithological characteristics of the rock cores, and oil testing data of different small rock cores after deep division; determining logging interpretation models and physical property lower limits of different small-layer reservoir parameters by combining logging data;
and 5: counting the test gas data of different small layers, distinguishing a gas layer, a gas-difference layer, a gas-water layer and a water layer, and making quantitative identification charts of different types of reservoirs by combining with a logging data chart; according to the qualitative judgment of the reservoir fluid properties in the step 2, determining the lower electrical limits of various reservoirs of different small layers by combining with a quantitative identification chart;
step 6: and (5) logging and secondarily explaining various reservoirs of different stratums through the lower electrical limit and the lower physical limit obtained in the step (4) and the step (5).
2. The well logging interpretation method for the hypotonic heterogeneous gas reservoir according to claim 1, wherein the well logging data in the step 1 is optimized and selected from well logging data of lithology series, porosity series and resistivity series; lithology series including natural potential, natural gamma, caliper log and natural gamma energy spectrum; porosity series includes density logs, sonic moveout, and neutron logs; the resistivity series included lateral logs, induction logs, microresistivity logs, and the R025, R045, R2.5, and R4 series apparent resistivity logs.
3. The well logging interpretation method for the low permeability heterogeneous gas reservoir according to claim 1, wherein the core homing in the step 1 is performed with depth correction on the core analysis porosity by using a sonic time difference curve as a reference; and performing depth correction on the shale content of the core analysis by taking a natural gamma curve as a reference.
4. The method for well logging interpretation of a hypotonic heterogeneous gas reservoir of claim 1, wherein the well logging interpretation model of reservoir parameters in step 4 comprises an interpretation model of shale content, an interpretation model of porosity, an interpretation model of permeability and an interpretation model of gas saturation.
5. The method for well logging interpretation of a hypotonic heterogeneous gas reservoir as defined in claim 1, wherein the model for interpretation of shale content is calculated as follows:
wherein the content of the first and second substances,Vshis the volume content of the argillaceous substance; GCUR is Hilbert index, 3.7 is taken as a new stratum, and 2.0 is taken as an old stratum; i isGRIs a natural gamma relative value; GR, GRmin、GRmaxThe natural gamma values of the target layer, the pure sandstone layer and the pure shale layer are respectively.
6. The well logging interpretation method for the hypotonic heterogeneous gas reservoir as claimed in claim 4, wherein the porosity interpretation model is preferably obtained from correlation between core analysis porosity and porosity series logging data; the correlation between the porosity of the core analysis and the series of the porosity logging data comprises a core analysis porosity-acoustic wave time difference cross plot, a core analysis porosity-density cross plot and a core analysis porosity-neutron porosity cross plot.
7. The method as claimed in claim 4, wherein the explained model of permeability is a porosity and permeability distribution chart for making different small-bed core analysis, and the explained model of permeability is obtained based on the porosity explained model.
8. The well logging interpretation method for the hypotonic heterogeneous gas reservoir as recited in claim 4, wherein the interpretation model of the gas saturation is a water saturation and permeability relationship chart based on closed core data of different strata, and the interpretation model of the gas saturation is determined based on the interpretation model of the permeability.
9. The logging interpretation method for the low permeability heterogeneous gas reservoir according to claim 1, wherein the lower physical property limit in the step 4 is the lower physical property limit of the reservoir of different small layers determined by a porosity-gas production rate per unit thickness relation curve, a permeability-gas production rate per unit thickness relation curve and a porosity-gas storage capacity loss chart in the gas test data.
10. The method for explaining well logging in the low-permeability heterogeneous gas reservoir according to claim 1, wherein in the step 5, the test gas data of different small layers are counted, the gas layer, the poor gas layer, the gas-water layer and the water layer are distinguished, and the quantitative identification charts of different types of reservoirs are made by combining the logging data charts; the logging data chart comprises a natural potential relative value and neutron porosity intersection chart, a sound wave time difference and density intersection chart, a microelectrode amplitude difference ratio value and lateral resistivity amplitude difference ratio chart, an RL3S/RL3D and density intersection chart, a water saturation and R025/Rm intersection chart, a sound wave time difference and RL3S/RL3D intersection chart, an RL3S and RL3D intersection chart, a natural potential relative value and well diameter reduction coefficient intersection chart, and an R0.25/Rm and RL3S/RL3D intersection chart.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112526107A (en) * | 2020-11-27 | 2021-03-19 | 中国地质大学（北京） | Method for recognizing and quantitatively characterizing desserts in fractured compact sandstone reservoir |
| CN116291415A (en) * | 2023-04-12 | 2023-06-23 | 西南石油大学 | Method and system for calculating porosity of gas-bearing stratum |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101937108A (en) * | 2009-07-03 | 2011-01-05 | 中国石油天然气股份有限公司 | Determining method for surveying reserves of hypotonic clastic rock oil-gas reservoir |
| CN104712330A (en) * | 2015-01-30 | 2015-06-17 | 中国地质大学（武汉） | Well logging permeability interpretation method |
| WO2016161914A1 (en) * | 2015-04-07 | 2016-10-13 | 四川行之智汇知识产权运营有限公司 | Method for predicting reservoir lithogenous phase using geology and logging information |
| CN106468172A (en) * | 2016-09-30 | 2017-03-01 | 西安石油大学 | A kind of Oil in Super-low Permeability sandstone oil reservoir low-resistance reservoir log interpretation method |
| CN106951660A (en) * | 2017-04-05 | 2017-07-14 | 中国石油天然气股份有限公司 | A kind of marine clastics horizontal well reservoir log interpretation method and device |
-
2019
- 2019-10-31 CN CN201911052326.8A patent/CN110688781B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101937108A (en) * | 2009-07-03 | 2011-01-05 | 中国石油天然气股份有限公司 | Determining method for surveying reserves of hypotonic clastic rock oil-gas reservoir |
| CN104712330A (en) * | 2015-01-30 | 2015-06-17 | 中国地质大学（武汉） | Well logging permeability interpretation method |
| WO2016161914A1 (en) * | 2015-04-07 | 2016-10-13 | 四川行之智汇知识产权运营有限公司 | Method for predicting reservoir lithogenous phase using geology and logging information |
| CN106468172A (en) * | 2016-09-30 | 2017-03-01 | 西安石油大学 | A kind of Oil in Super-low Permeability sandstone oil reservoir low-resistance reservoir log interpretation method |
| CN106951660A (en) * | 2017-04-05 | 2017-07-14 | 中国石油天然气股份有限公司 | A kind of marine clastics horizontal well reservoir log interpretation method and device |
Non-Patent Citations (2)
| Title |
|---|
| 刘传平等: "汪家屯气田气、水层划分标准及孔隙度、饱和度测井解释方法研究", 《大庆石油地质与开发》 * |
| 张彬等: "李家岔地区长2油藏测井二次解释及应用", 《内蒙古石油化工》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112526107A (en) * | 2020-11-27 | 2021-03-19 | 中国地质大学（北京） | Method for recognizing and quantitatively characterizing desserts in fractured compact sandstone reservoir |
| CN112526107B (en) * | 2020-11-27 | 2021-11-16 | 中国地质大学（北京） | Method for recognizing and quantitatively characterizing desserts in fractured compact sandstone reservoir |
| CN116291415A (en) * | 2023-04-12 | 2023-06-23 | 西南石油大学 | Method and system for calculating porosity of gas-bearing stratum |
| CN116291415B (en) * | 2023-04-12 | 2023-11-24 | 西南石油大学 | Method and system for calculating porosity of gas-bearing stratum |
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