CN110688781B - Well logging interpretation method for low-permeability heterogeneous gas reservoir - Google Patents
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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 conductivity 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 reservoirs with low formation water mineralization, the low formation water mineralization causes the apparent resistivity difference of an air layer and a water layer on a logging curve to be not obvious, and the apparent resistivity of the water layer of an individual 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 skip 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 2, step: introducing a dual-porosity difference method delta phi = phi D -φ N Wherein phi D Porosity, phi, calculated for density values obtained from density logs N Porosity calculated for apparent neutron porosity obtained with compensated neutron logging; qualitatively analyzing the reservoir by integrating the test gas data, and further analyzing the numerical characteristics of the fluid delta phi corresponding to the gas layer, the gas-water layer and the water layer to qualitatively distinguish the response characteristics of different fluids delta phi in the reservoir of the stratum;
and 3, 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 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 includes 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, V sh Is 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 is GR Is a natural gamma relative value; GR, GR min 、GR max The 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.
Furthermore, the explanation model of the permeability is an explanation model for determining the permeability and the porosity by making distribution charts of the porosity and the permeability of different small-layer core analyses, and the explanation model of the permeability is obtained based on the explanation 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, an acoustic time difference and density intersection chart, a microelectrode amplitude difference ratio and lateral resistivity amplitude difference ratio intersection chart, an RL3S/RL3D and density intersection chart, a water saturation and R025/Rm intersection chart, an acoustic 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 low-permeability heterogeneous gas reservoir, which introduces delta phi = phi D -φ N When the delta phi is larger than zero, the reservoir fluid can be qualitatively judged to be natural gas, and when the delta phi is smaller than zero, the reservoir fluid can be qualitatively judged to be formation water, so that the property of the formation fluid can be qualitatively judged; in addition, an explanation model of formation physical property parameters is obtained by making a distribution chart of the porosity, shale content data, gas saturation and logging data of the rock core and combining oil testing data and closed coring data of different formations, and then the lower physical property limit of the formations is determined; then, determining the electrical lower limits of various reservoirs of different stratums by analyzing the optimal results of the correlation relationship between the porosity and the porosity series logging data through the rock core; the stratum is explained for the second time through the lower physical property limit and the lower electrical property limit of the stratum, and the stratum is explained by logging through multiple standards, so that the stability of the gas reservoir interpretation is improved; the reservoir stratum is evaluated in a layered mode, a refined explanation model of different strata is built, the well logging explanation precision is improved, and meanwhile the matching performance between the well logging data and the oil testing data is better; in the standard establishing process, the more oil testing data and the more core testing data, the more series of logging data, the more accurate the reservoir interpretation model is, and the higher the interpretation stability of the gas reservoir is; on the basis of the existing stratum knowledge, a logging interpretation model of the reservoir is established by the method, so that the physical property lower limit and the electrical property lower limit of the reservoir are determined, qualitative and quantitative evaluation and description of a gas-water layer can be realized, and refined description of a heterogeneous gas reservoir is realized.
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 an RL3S and RL3D intersection;
FIG. 16 is a graph of RL3S/RL3D vs. density;
FIG. 17 is a graph of the acoustic time difference versus RL3S/RL3D intersection;
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 process with certain oils Tian Oukuai 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 for core homing, enabling the depth of a core to be 1700-2100 m, enabling the homing correction value to reach 2.6m at most, and conforming to the homing correction error analysis rule and the correction range;
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;
step 2: introducing a dual-porosity difference method delta phi = phi D -φ N Wherein phi D Porosity, phi, calculated for use with density log data N Porosity calculated using neutron log data; when delta phi is larger than 0, the main fluid property of the reservoir can be qualitatively obtained as natural gas, and when delta phi is smaller than 0, the main fluid property of the reservoir can be qualitatively obtained as formation water; comprehensively analyzing the numerical characteristics of delta phi corresponding to the gas layer, the gas-water layer and the water layer, and qualitatively distinguishing the response characteristics of the delta phi of different fluid reservoirs; specifically, the method comprises the steps of counting test gas data of a research area, distinguishing a gas layer, a gas-water layer and a water layer, calculating density porosity and neutron porosity calculated by test gas stratum layer section density logging and neutron logging data by using the formula, counting corresponding delta phi values of the gas layer, the gas-water layer and the water layer, making a delta phi value and reservoir fluid property chart, and further qualitatively identifying the property of a formation fluid, wherein the delta phi values are shown in figure 1; in this embodiment, the logging data of 10 production wells with neutron logging and density logging are selected, then the density porosity and the neutron porosity of the production formation interval are respectively calculated, and then the curve characteristics of delta phi on the production well depth are passedQualitatively judging the fluid property of the stratum, wherein the total interpreted layer number is 137 layers, the layer number which accords with the actual production is 123 layers, and the coincidence rate is 89.78%;
and step 3: dividing stable shale layers by combining the lithologic characteristics and the sedimentation characteristics of the rock core and the logging curve characteristics of lithologic series logging data of a plurality of wells, subdividing the strata by the shale layers to obtain small layers, and deeply dividing the logging data of each well by the depth of 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, V sh Is 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 is GR Is a natural gamma relative value; GR, GR min 、GR max The natural gamma values of the target layer, the pure sandstone layer and the pure shale layer are respectively.
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 =100% -water saturation in an oil-free formation;
as shown in fig. 7 to fig. 9, the porosity-gas production capacity loss chart is obtained by using the relationship curve of porosity-gas production per unit thickness, the relationship curve of permeability-gas production per unit thickness and the porosity-gas storage capacity loss chart in the gas test 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 natural potential relative value and neutron porosity cross-plot, an acoustic time difference and density cross-plot, a microelectrode amplitude difference ratio and lateral resistivity amplitude difference ratio cross-plot, an RL3S/RL3D and density cross-plot, a water saturation and R025/Rm cross-plot, an acoustic time difference and RL3S/RL3D cross-plot, an RL3S and RL3D cross-plot, a natural potential relative value and well diameter reduction coefficient cross-plot, and an R025/Rm and RL3S/RL3D cross-plot;
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 delta phi = phi D -φ N Wherein phi D Porosity, phi, calculated for density values obtained from density logs N Porosity calculated for apparent neutron porosity obtained with compensated neutron logging; qualitatively analyzing the reservoir by integrating the gas testing data, and further analyzing the numerical characteristics of the fluid delta phi corresponding to the gas layer, the gas-water layer and the water layer to qualitatively distinguish the response characteristics of different fluids delta 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 well logging interpretation method for the hypotonic heterogeneous gas reservoir as claimed in claim 1, wherein the well logging interpretation model for the reservoir parameters in step 4 comprises an interpretation model for shale content, an interpretation model for porosity, an interpretation model for permeability and an interpretation model for 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, V sh Is 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 is GR Is a natural gamma relative value; GR, GR min 、GR max The 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 well logging data chart comprises a natural potential relative value and neutron porosity intersection chart, an acoustic time difference and density intersection chart, a microelectrode amplitude difference ratio and lateral resistivity amplitude difference ratio intersection chart, an RL3S/RL3D and density intersection chart, a water saturation and R025/Rm intersection chart, an acoustic 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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