CN104375204A - Method and device for analyzing anisotropism of reservoir - Google Patents
Method and device for analyzing anisotropism of reservoir Download PDFInfo
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- CN104375204A CN104375204A CN201410675357.XA CN201410675357A CN104375204A CN 104375204 A CN104375204 A CN 104375204A CN 201410675357 A CN201410675357 A CN 201410675357A CN 104375204 A CN104375204 A CN 104375204A
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Abstract
The invention discloses a method and device for analyzing anisotropism of a reservoir. The method includes the steps that the lithology and the stratification structure of the reservoir are identified according to core scale electric imaging logging information; the macroscopic anisotropism of the reservoir is analyzed according to the lithology and the stratification structure of the reservoir; the microcosmic anisotropism of the reservoir is analyzed according to nuclear magnetic resonance logging information. Through the scheme, the macroscopic anisotropism and the microcosmic anisotropism of the reservoir are analyzed based on the core scale electric imaging logging information and the nuclear magnetic resonance logging information, and the electric imaging logging information and the nuclear magnetic resonance logging information are longitudinally continuous and high in accuracy, so that the accuracy of analyzing the anisotropism of the reservoir is improved.
Description
Technical field
The present invention relates to logging geological field, espespecially a kind of method and apparatus analyzing reservoir heterogeneity.
Background technology
Reservoir heterogeneity refers to the attribute that the various character of reservoir change with its locus.Be mainly manifested in the heterogeneous body of rock substance composition and the heterogeneous body of pore space.
The method of current identification reservoir heterogeneity mainly comprises comprehensive geology analytical approach, reservoir geologic modeling method and laboratory assays etc.
Wherein, comprehensive geology analytical approach utilizes V-factor, permeability extreme difference and individual layer to assault the parameters such as coefficient and comprehensively analyzes reservoir heterogeneity; Reservoir geologic modeling method is by geostatistics method, utilizes given data realization to the sign of oil and gas reservoir nonuniformity and portrays; Comprehensive geology analytical approach and reservoir geologic modeling method are only from macroscopically identifying reservoir heterogeneity, and its porosity and permeability data comes from Using Conventional Logs, and Using Conventional Logs precision is lower.
Laboratory assays mainly utilizes the method identification reservoir heterogeneity such as core wafer or casting body flake qualification, scanning electron microscope and the identification of pressure mercury.Laboratory method of identification, emphasis studies microheterogeneity, again because rock core is few, scattered, cannot carry out system, continuous and comprehensive non-average identification to reservoir.
Summary of the invention
In order to solve the problem, the present invention proposes a kind of method and apparatus analyzing reservoir heterogeneity, can analysis precision be improved.
In order to achieve the above object, the present invention proposes a kind of method analyzing reservoir heterogeneity, comprising:
According to lithology and the bedding structure of drilling core graduation electric imaging logging data identification reservoir;
According to the lithology of reservoir and bedding structure, the macroscopic heterogeneity of reservoir is analyzed;
Analyze according to the microscopic heterogeneity of NMR logging data to reservoir.
Preferably, the described lithology according to reservoir and bedding structure carry out analysis to the macroscopic heterogeneity of reservoir and comprise:
Be different lithology facies units according to the lithology of reservoir and bedding structure by reservoir zonation, the macroscopic heterogeneity according to the relatively described reservoir of the lithology of each lithology facies unit is analyzed.
Preferably, describedly according to NMR logging data, analysis is carried out to the microscopic heterogeneity of reservoir and comprises:
Analyze the pore texture of described reservoir according to NMR logging data, the microscopic heterogeneity of pore texture to described reservoir according to described reservoir is analyzed.
Preferably, the described pore texture according to NMR logging data analysis reservoir comprises:
Obtain the corresponding relation between the T2 of described each lithology facies unit and factor of porosity according to the NMR logging data of described reservoir, analyze the pore texture of described each lithology facies unit according to the corresponding relation obtained.
The invention allows for a kind of device analyzing reservoir heterogeneity, at least comprise:
Identification module, for according to the lithology of drilling core graduation electric imaging logging data identification reservoir and bedding structure;
First analysis module, for analyzing the macroscopic heterogeneity of reservoir according to the lithology of reservoir and bedding structure;
Second analysis module, for analyzing according to the microscopic heterogeneity of NMR logging data to reservoir.
Preferably, described first analysis module specifically for:
Be different lithology facies units according to the lithology of reservoir and bedding structure by reservoir zonation, the macroscopic heterogeneity according to the relatively described reservoir of the lithology of each lithology facies unit is analyzed.
Preferably, described second analysis module specifically for:
Analyze the pore texture of described reservoir according to NMR logging data, the microscopic heterogeneity of pore texture to described reservoir according to described reservoir is analyzed.
Preferably, described second analysis module specifically for:
Obtain the corresponding relation between the T2 of described each lithology facies unit and factor of porosity according to the NMR logging data of described reservoir, analyze the pore texture of described each lithology facies unit according to the corresponding relation obtained.
Compared with prior art, the present invention includes: according to lithology and the bedding structure of drilling core graduation electric imaging logging data identification reservoir; According to the lithology of reservoir and bedding structure, the macroscopic heterogeneity of reservoir is analyzed; Analyze according to the microscopic heterogeneity of NMR logging data to reservoir.Pass through the solution of the present invention, based on drilling core graduation electric imaging logging data and NMR logging data, reservoir is carried out to the analysis of macroscopic heterogeneity and microscopic heterogeneity, because electric imaging logging data and NMR logging data are longitudinally continuous, and precision is high, this improves the precision analyzing reservoir heterogeneity.
Accompanying drawing explanation
Be described the accompanying drawing in the embodiment of the present invention below, the accompanying drawing in embodiment is for a further understanding of the present invention, is used from explanation the present invention, does not form limiting the scope of the invention with instructions one.
Fig. 1 is the process flow diagram that the present invention analyzes the method for reservoir heterogeneity;
Fig. 2 is the schematic diagram of Lithology Discrimination of the present invention;
Fig. 3 is the schematic diagram of bedding conformation identification of the present invention;
Fig. 4 is that lithology of the present invention knows each other other schematic diagram;
Fig. 5 is the schematic diagram of the corresponding relation between the T2 of reservoir of the present invention and factor of porosity;
Fig. 6 is the schematic diagram that the factor of porosity of each porosity type of the present invention accounts for total porosity number percent;
Fig. 7 is the structure composition schematic diagram that the present invention analyzes the device of reservoir heterogeneity.
Embodiment
For the ease of the understanding of those skilled in the art, below in conjunction with accompanying drawing, the invention will be further described, can not be used for limiting the scope of the invention.
See Fig. 1, the present invention proposes a kind of method analyzing reservoir heterogeneity, comprising:
Step 100, according to the lithology of drilling core graduation electric imaging logging data identification reservoir and bedding structure.
In this step, existing method specifically can be adopted to identify lithology and the bedding structure of reservoir, and the protection domain be not intended to limit the present invention, repeats no more here.Such as, application number is " CN201210089632.0 ", the method identifying lithology is described in detail in the Chinese invention patent that denomination of invention is " a kind of petroclastic rock Lithology Identification Methods and system ", application number is CN201210095243.9, and denomination of invention is describe the method identifying bedding structure in the Chinese invention patent of " a kind of bedding conformation identification method and system " in detail.
Fig. 2 is the schematic diagram of Lithology Discrimination, as shown in Figure 2, first is classified as rock core photo, second is classified as large scale deep calibration, 3rd is classified as Electrical imaging still image, 4th is classified as degree of depth small scale deep calibration, and the 5th is classified as gamma ray curve, and the 6th is classified as the lithological profile set up by Lithology Discrimination.In 6th row, the box indicating lithology of dotted line is mud stone, both sides are black circle, centre is the box indicating lithology of soft dot is that both sides are soft dot containing gravel sandstone grit, and the middle box indicating lithology for black circle is glutenite, so, as can be seen from the figure, identify reservoir and include 3 kinds of lithology, be respectively mud stone, containing gravel sandstone grit and glutenite.
Fig. 3 is the schematic diagram of bedding conformation identification, and as shown in Figure 3, first is classified as deep calibration, and second is classified as Electrical imaging dynamic image schematic diagram, and the 3rd is classified as dip vector, and the 4th is classified as rock core photo, and the bedding identifying reservoir is configured to incision type tabular cross-stratification.
Step 101, according to the lithology of reservoir and bedding structure, the macroscopic heterogeneity of reservoir to be analyzed.
In this step, according to the lithology of reservoir and bedding structure, analysis is carried out to the macroscopic heterogeneity of reservoir and comprises:
Be different lithology facies units according to the lithology of reservoir and bedding structure by reservoir zonation, the macroscopic heterogeneity according to the relative reservoir of lithology of each lithology facies unit is analyzed.
Wherein, identifying on the basis that lithology and bedding construct, can be different lithology facies units by reservoir zonation according to different lithology from bedding tectonic association, the corresponding a kind of lithology phase of each lithology facies unit, lithology due to reservoir reflects the sedimentary environment hydrodynamic condition of reservoir mutually, hydrodynamic condition is stronger, and during representative deposition, water energy is higher, and the reservoir properties of formation is better.Therefore, geologic origin or macroscopically see that different its reservoir physicals of lithology facies unit is variant, Fig. 4 is that lithology knows each other other schematic diagram, as shown in Figure 4, first is classified as deep calibration, second is classified as gamma ray curve, 3rd is classified as the lithological profile set up by Lithology Discrimination, 4th is classified as Electrical imaging still image schematic diagram, 5th is classified as Electrical imaging dynamic image schematic diagram, 6th is classified as dip vector, 7th is classified as T2 spectrum, 8th is classified as the lithology phase identified, 9th is classified as factor of porosity, tenth is classified as permeability, in 3rd row, the box indicating lithology of three black circles is sandstone grit, so, the sand body that 3756-3761.5 rice (m) is dark can mark off 3 kinds of lithology phases, be respectively tabular cross-stratification glutenite, trough cross-stratification glutenite and block bedding sandstone grit.
During trough cross-stratification glutenite deposition, water energy is the highest, it is 17.1% that factor of porosity is analyzed in core experiment room, and permeability is 25.5 millidarcies (md), and reservoir physical is best, during tabular cross-stratification glutenite deposition, water energy is slightly low, it is 14.9% that factor of porosity is analyzed in core experiment room, and permeability is 14.2md, and reservoir properties is poor, during block diagonal stratification sandstone grit deposition, water energy is the most weak, it is 13.8% that factor of porosity is analyzed in core experiment room, and permeability is 8.8md, and reservoir properties is the poorest.
The above-mentioned macroscopic heterogeneity analysis result to reservoir and Analytical Laboratory Results match, and illustrate that this analytical approach has higher reliability.
Step 102, to analyze according to the microscopic heterogeneity of NMR logging data to reservoir.
In this step, according to NMR logging data, analysis is carried out to the microscopic heterogeneity of reservoir and comprises:
Analyze the pore texture of reservoir according to NMR logging data, the microscopic heterogeneity of pore texture to reservoir according to reservoir is analyzed.
Wherein, can with the pore texture of default unit (as lithology facies unit) for unit analysis reservoir.
Wherein, T2 (the i.e. T2 of each default unit is obtained according to the NMR logging data of reservoir, it is the time constant describing nuclear magnetization cross stream component rejuvenation) and factor of porosity between corresponding relation, analyze the pore texture of each default unit according to the corresponding relation obtained.
Wherein, can adopt the corresponding relation between the T2 of each default unit of prior art acquisition and factor of porosity, the protection domain be not intended to limit the present invention, repeats no more here.
Wherein, the pore texture presetting unit can refer to the distribution situation of various porosity type in default unit.Particularly, porosity type can be divided into N type according to the T2 of reservoir.Wherein, N be more than or equal to 1 integer.Such as, according to usual method porosity type can be divided into little, in, large three types.Namely be fine porosity when T2 is less than or equal to first threshold, being mesoporosity when T2 is greater than first threshold and is less than or equal to Second Threshold, is macropore when T2 is greater than Second Threshold.
Such as, Fig. 5 is the schematic diagram of the corresponding relation between the T2 of reservoir and factor of porosity.As shown in Figure 5, horizontal ordinate is T2, and ordinate is the factor of porosity after scale.So, according to T2, the porosity type of reservoir can be divided into large, medium and small three types.Namely when T2 is positioned at T2 cutoff 1 (16 milliseconds (ms)) left part, namely being less than 16ms is fine porosity (the left diagonal line hatches part namely in Fig. 5), T2 is positioned at part between T2 cutoff 1 (16ms) and T2 cutoff 2 (128ms), namely 16ms to 128ms is mesoporosity (the horizontal line dash area namely in Fig. 5), T2 is positioned at T2 cutoff 2 (128ms) right part, and being namely greater than 128ms is macropore (the right diagonal line hatches part namely in Fig. 5).T2 corresponding for three kinds of porosity type spectrum is carried out the factor of porosity that integration can obtain each porosity type, and its size can represent by the shaded area corresponding to porosity type each in Fig. 5.
By Fig. 5, the number percent of total porosity shared by each porosity type can be obtained according to each porosity type factor of porosity, be shown as Fig. 6 more intuitively, the i.e. schematic diagram of total porosity number percent shared by each porosity type, horizontal ordinate is three kinds of porosity type dividing according to T2 (T2), and ordinate is the number percent that the factor of porosity of different aperture type accounts for total porosity.The number percent that macroporous factor of porosity accounts for total porosity is larger, and the perviousness of petrofacies unit is better, and the physical property representing petrofacies unit is better; Otherwise it is larger that the factor of porosity of fine porosity accounts for total porosity number percent, then lithology facies unit perviousness is poorer, represent that the physical property of lithology facies unit is poorer.As shown in Figure 6, the number percent that the factor of porosity of fine porosity accounts for total porosity is 42%, the number percent that the factor of porosity of mesoporosity accounts for total porosity is 50%, the number percent that macroporous factor of porosity accounts for total porosity is 8%, illustrate that this petrofacies unit is primarily of mesoporosity and fine porosity composition, the medium deviation of this petrofacies unit physical property.
In method of the present invention, based on drilling core graduation electric imaging logging data and NMR logging data, reservoir is carried out to the analysis of nonuniformity, because electric imaging logging data and NMR logging data are longitudinally continuous, and precision is high, this improves the precision identifying reservoir heterogeneity.In addition, due to the stratification structure formed in layer when bedding is deposits, and pore texture is not only relevant with deposition, and relevant with Diagn, therefore, and the deposition of reservoir and diagenetic impact by method concentrated expression of the present invention.
Obtained the pore texture of each lithology facies unit by method of the present invention after, just can according to the lithology phase of lithology facies unit and the pore texture nonuniformity from both macro and micro two kinds of angle analysis lithology facies units.Such as, analyze according to Fig. 4 the 7th road Nuclear Magnetic Resonance Logging, trough cross-stratification glutenite lithology phase (3759-3760.1m), T2 spectrum is mainly positioned at T2 cutoff 2 (128ms) right side, is namely greater than 128ms, percent profile analysis is composed according to T2, the number percent that macroporous factor of porosity accounts for total porosity is 70%, and the number percent that the factor of porosity of mesoporosity accounts for total porosity is 30%, illustrates to form primarily of macropore, part mesoporosity, reservoir properties is best; Tabular cross-stratification glutenite lithology phase (3756-3759m) T2 spectrum is mainly positioned between T2 cutoff 1 (16ms) to T2 cutoff 2 (128ms), percent profile analysis is composed according to T2, the number percent that macroporous factor of porosity accounts for total porosity is 7%, the number percent that the factor of porosity of mesoporosity accounts for total porosity is 60%, the number percent that the factor of porosity of fine porosity accounts for total porosity is 33%, explanation is mainly mesoporosity, containing part fine porosity and a small amount of macropore, reservoir properties is better; Block bedding sandstone grit lithology phase (3760.1-3761.5m), T2 spectrum is mainly positioned at T2 cutoff 1 (16ms) left side, namely 16ms is less than, compose percent profile analysis according to T2, the number percent that macroporous factor of porosity accounts for total porosity is 5%, and the number percent that the factor of porosity of mesoporosity accounts for total porosity is 15%, the number percent that the factor of porosity of fine porosity accounts for total porosity is 80%, illustrate that containing part mesoporosity and a small amount of macropore, reservoir properties is the poorest primarily of fine porosity composition.
Integrated reservoir both macro and micro heterogeneous body analysis result, trough cross-stratification glutenite lithology phase reservoir quality is best, tabular cross-stratification glutenite lithology phase reservoir properties is better, these two kinds of reservoirs are Favorable Reservoir of taping the latent power, block bedding sandstone grit lithology phase reservoir quality is then poor, substantially without value of taping the latent power.
The present invention makes full use of electric imaging logging data and NMR logging data is analysed in depth reservoir macroscopic heterogeneity and microscopic heterogeneity respectively.Macroscopically passing through Lithology Discrimination, bedding conformation identification based on imaging logging, dividing and setting up high-precision lithology facies unit, and carrying out reservoir elaborate division and geologic origin research with this; On microcosmic based on nuclear magnetic resonance log by reservoir T2 is composed explain and little, in, macropore divides and obtains respective proportion statistics, comes quantitatively characterizing reservoir micropore structure feature and aeolotropic characteristics thereof.Integrated reservoir macroscopic view and micro-analysis result, can realize with lithology be yardstick, the object of longitudinal continuous print, comprehensively reflection reservoir heterogeneity, for finding real Favorable Reservoir or dessert provides reliable basis.
See Fig. 7, the invention allows for a kind of device analyzing reservoir heterogeneity, at least comprise:
Identification module, for according to the lithology of drilling core graduation electric imaging logging data identification reservoir and bedding structure;
First analysis module, for analyzing the macroscopic heterogeneity of reservoir according to the lithology of reservoir and bedding structure;
Second analysis module, for analyzing according to the microscopic heterogeneity of NMR logging data to reservoir.
In device of the present invention, the first analysis module specifically for:
Be different lithology facies units according to the lithology of reservoir and bedding structure by reservoir zonation, the macroscopic heterogeneity according to the relative reservoir of lithology of each lithology facies unit is analyzed.
In device of the present invention, the second analysis module specifically for:
Analyze the pore texture of reservoir according to NMR logging data, the microscopic heterogeneity of pore texture to reservoir according to reservoir is analyzed.
In device of the present invention, the second analysis module specifically for:
Obtain the corresponding relation between the T2 of each lithology facies unit and factor of porosity according to the NMR logging data of reservoir, analyze the pore texture of each lithology facies unit according to the corresponding relation obtained.
It should be noted that; above-described embodiment is only understand for the ease of those skilled in the art; be not limited to protection scope of the present invention; under the prerequisite not departing from inventive concept of the present invention, any apparent replacement and improvement etc. that those skilled in the art make the present invention are all within protection scope of the present invention.
Claims (8)
1. analyze a method for reservoir heterogeneity, it is characterized in that, comprising:
According to lithology and the bedding structure of drilling core graduation electric imaging logging data identification reservoir;
According to the lithology of reservoir and bedding structure, the macroscopic heterogeneity of reservoir is analyzed;
Analyze according to the microscopic heterogeneity of NMR logging data to reservoir.
2. method according to claim 1, is characterized in that, the described lithology according to reservoir and bedding structure carry out analysis to the macroscopic heterogeneity of reservoir and comprise:
Be different lithology facies units according to the lithology of reservoir and bedding structure by reservoir zonation, the macroscopic heterogeneity according to the relatively described reservoir of the lithology of each lithology facies unit is analyzed.
3. method according to claim 1, is characterized in that, describedly carries out analysis according to NMR logging data to the microscopic heterogeneity of reservoir and comprises:
Analyze the pore texture of described reservoir according to NMR logging data, the microscopic heterogeneity of pore texture to described reservoir according to described reservoir is analyzed.
4. method according to claim 3, is characterized in that, the described pore texture according to NMR logging data analysis reservoir comprises:
Obtain the corresponding relation between the T2 of described each lithology facies unit and factor of porosity according to the NMR logging data of described reservoir, analyze the pore texture of described each lithology facies unit according to the corresponding relation obtained.
5. analyze a device for reservoir heterogeneity, it is characterized in that, at least comprise:
Identification module, for according to the lithology of drilling core graduation electric imaging logging data identification reservoir and bedding structure;
First analysis module, for analyzing the macroscopic heterogeneity of reservoir according to the lithology of reservoir and bedding structure;
Second analysis module, for analyzing according to the microscopic heterogeneity of NMR logging data to reservoir.
6. device according to claim 5, is characterized in that, described first analysis module specifically for:
Be different lithology facies units according to the lithology of reservoir and bedding structure by reservoir zonation, the macroscopic heterogeneity according to the relatively described reservoir of the lithology of each lithology facies unit is analyzed.
7. device according to claim 5, is characterized in that, described second analysis module specifically for:
Analyze the pore texture of described reservoir according to NMR logging data, the microscopic heterogeneity of pore texture to described reservoir according to described reservoir is analyzed.
8. device according to claim 7, is characterized in that, described second analysis module specifically for:
Obtain the corresponding relation between the T2 of described each lithology facies unit and factor of porosity according to the NMR logging data of described reservoir, analyze the pore texture of described each lithology facies unit according to the corresponding relation obtained.
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| CN105092820A (en) * | 2015-08-06 | 2015-11-25 | 中国石油集团长城钻探工程有限公司地质研究院 | Bioclastic limestone reservoir heterogeneity research method |
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| CN111950193A (en) * | 2020-07-15 | 2020-11-17 | 中海油田服务股份有限公司 | Modeling method and device of pore network model based on reservoir |
| CN114076991A (en) * | 2020-08-14 | 2022-02-22 | 中国石油化工股份有限公司 | Characterization method of reservoir macroscopic heterogeneity |
| CN114076991B (en) * | 2020-08-14 | 2024-02-23 | 中国石油化工股份有限公司 | Characterization method of macroscopic heterogeneity of reservoir |
| CN114089421A (en) * | 2021-12-06 | 2022-02-25 | 中国矿业大学 | Oil and gas reservoir heterogeneity analysis method |
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