CN116010789B - Carbonate reservoir type identification method, device, equipment and application - Google Patents
Carbonate reservoir type identification method, device, equipment and application Download PDFInfo
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- BVKZGUZCCUSVTD-UHFFFAOYSA-L Carbonate Chemical compound [O-]C([O-])=O BVKZGUZCCUSVTD-UHFFFAOYSA-L 0.000 title claims abstract description 108
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- 206010017076 Fracture Diseases 0.000 claims abstract description 149
- 208000010392 Bone Fractures Diseases 0.000 claims abstract description 136
- 238000011161 development Methods 0.000 claims abstract description 83
- 238000003384 imaging method Methods 0.000 claims abstract description 21
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- 239000011435 rock Substances 0.000 description 7
- 230000006870 function Effects 0.000 description 4
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- 235000019738 Limestone Nutrition 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 239000010459 dolomite Substances 0.000 description 2
- 229910000514 dolomite Inorganic materials 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
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- 239000006028 limestone Substances 0.000 description 2
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- 238000012360 testing method Methods 0.000 description 2
- 239000004215 Carbon black (E152) Substances 0.000 description 1
- 235000006040 Prunus persica var persica Nutrition 0.000 description 1
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- 229930195733 hydrocarbon Natural products 0.000 description 1
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Abstract
The invention discloses a carbonate reservoir type identification method, a carbonate reservoir type identification device, carbonate reservoir type identification equipment and carbonate reservoir type identification application, wherein the carbonate reservoir type identification method comprises the following steps: determining a fracture linear density of the carbonate reservoir based on the core observations and/or the electrical imaging logging data; determining a fracture development section of the carbonate reservoir based on the log and the fracture line density; the fracture porosity of the fracture development stage is calculated to identify the type of carbonate reservoir based on the fracture porosity. The method comprises the steps of processing a conventional logging curve, amplifying response characteristics of a record carrier to a reservoir, and constructing a crack identification probability model of a carbonate reservoir so as to determine a crack development section of the reservoir; and then under the constraint of a fracture identification probability model, judging the fracture occurrence and determining the fracture porosity of the corresponding occurrence so as to accurately identify the quantitative data of the carbonate reservoir. The method can effectively divide the reservoir types under the condition of no imaging logging, nuclear magnetic logging and other data, is convenient to apply, has high accuracy, and has great practical value and popularization significance.
Description
Technical Field
The invention relates to the technical field of oil and gas reservoir exploration and development, in particular to a carbonate reservoir type identification method, a carbonate reservoir type identification device, carbonate reservoir type identification equipment and carbonate reservoir type identification application.
Background
Carbonate reservoirs are always important exploration targets for finding oil and gas resources as important carriers for oil and gas. Thus, identification of carbonate reservoirs has an important role in determining hydrocarbon resource potential. Compared with the conventional pore type reservoir, the carbonate fracture-cavity type reservoir has a complex pore structure and extremely strong anisotropy, and the logging identification and evaluation difficulty is far greater than that of the conventional pore type reservoir, so that the carbonate fracture-cavity type reservoir has been a difficulty and a hot spot of logging analysis for many years.
The method for identifying the carbonate fracture-cavity reservoir in the prior art can be summarized into the following categories:
(1) Performing fracture and hole identification by utilizing core observation, namely observing the core taken out from the well by naked eyes or under a lens to form visual knowledge of development degree, distribution and the like of reservoir cracks so as to identify reservoir types;
(2) And identifying the fracture and hole by using a conventional logging curve. A large number of core data, imaging logging data and conventional logging data show that the response degree difference of different logging curves to a carbonate fracture-cavity is obvious, and the carbonate fracture-cavity reservoir is comprehensively identified by adopting a plurality of logging curves;
(3) The new logging technique identifies fractures. For example, modern logging technologies represented by FMI logging, dipole shear imaging logging and the like are mature in recent years, a more accurate technical method is provided for identifying carbonate fracture-cavity reservoirs, researchers can directly observe pore structures of cracks, solution holes, solution cavities and the like of the reservoirs according to various imaging log diagrams, and identification of the cracks and the holes and explanation of various geological structures can be intuitively and accurately completed.
Disclosure of Invention
The inventor finds that when the rock core observation method is used for identifying the fracture and hole, the development characteristics and rules of a large number of cracks in the uncorrupted wells are difficult to describe only by virtue of the coring data due to the limited number of the coring wells; when the conventional logging curve method is used for identifying the fracture and hole, the quantitative data identification degree is not high; the identification method of the new logging technology is expensive and difficult to popularize on a large scale. In view of the complexity of the carbonate fracture-cavity reservoir, a set of system and a perfect carbonate fracture-cavity reservoir logging evaluation method are not formed so far, and particularly, the research result is insufficient in the aspect of quantitative identification of the carbonate fracture-cavity reservoir. The present invention has been made in view of the above problems, and has as its object to provide a carbonate reservoir type identification method, apparatus, device and application which overcome or at least partially solve the above problems.
In a first aspect, an embodiment of the present invention provides a carbonate reservoir type identification method, which may include:
determining a fracture linear density of the carbonate reservoir based on core observations and/or electrical imaging logging data;
determining a fracture development section of the carbonate reservoir based on the log and the fracture linear density;
the fracture porosity of the fracture development segment is calculated to identify a type of the carbonate reservoir based on the fracture porosity.
Optionally, the determining a fracture development stage of the carbonate reservoir based on the log and the fracture linear density may include:
calibrating a density logging curve, an acoustic time difference logging curve, a compensated neutron logging curve and/or a dual lateral resistivity logging curve to reconstruct crack identification characteristic parameters of a density ratio, an acoustic wave ratio, a neutron ratio and/or a depth lateral resistivity difference ratio of the logging;
performing multivariate correlation coefficient analysis based on the crack identification parameters and the crack linear density to determine weight coefficients of the crack identification parameters;
determining a comprehensive index of the crack development degree based on the crack identification parameters and the weight coefficients;
and determining a fracture development section of the carbonate reservoir based on the composite index of the fracture development degree.
Optionally, before the multi-element correlation coefficient analysis is performed based on the fracture identification parameters and the fracture linear density to determine the weight coefficient of each fracture identification parameter, the method further includes:
and carrying out normalization treatment on the crack identification parameters so as to carry out multi-element correlation coefficient analysis by using the crack identification parameters and the crack linear density after normalization treatment.
Optionally, the determining the fracture development stage of the carbonate reservoir based on the composite index of the fracture development degree may include:
based on the comprehensive index of the crack development degree, a frequency distribution histogram is manufactured;
taking the comprehensive index value corresponding to the frequency peak value of the frequency distribution histogram as the standard lower limit value of the crack development section;
and determining the crack development section of the carbonate reservoir according to the standard lower limit value of the crack development section.
Optionally, the calculating the fracture porosity of the fracture development segment to identify the type of carbonate reservoir based on the fracture porosity may include:
judging the type of the fracture occurrence based on the depth lateral resistivity of the dual lateral resistivity log;
determining fracture porosity of the different occurrence types of fractures based on the depth lateral resistivity and the mud filtrate resistivity of the well log;
the type of the carbonate reservoir is identified based on the fracture porosity of the different occurrence type fractures.
Optionally, the identifying the type of the carbonate reservoir based on the fracture porosity of the different occurrence type fractures may include:
and statistically analyzing the crack porosity ranges of the cracks with different occurrence types, and comprehensively identifying the type of the carbonate reservoir by combining the carbonate reservoir type determined by core observation data, electric imaging logging data and/or nuclear magnetic resonance data.
In a second aspect, embodiments of the present invention provide a carbonate reservoir type recognition device, which may include:
the fracture linear density determining module is used for determining the fracture linear density of the carbonate reservoir based on core observation data and/or electric imaging logging data;
a fracture development segment determination module for determining a fracture development segment of the carbonate reservoir based on a log and the fracture line density;
and the reservoir type identification module is used for calculating the fracture porosity of the fracture development section so as to identify the type of the carbonate reservoir based on the fracture porosity.
In a third aspect, embodiments of the present invention provide a computer readable storage medium having stored thereon a computer program which when executed by a processor implements a carbonate reservoir type identification method as described in the first aspect.
In a fourth aspect, embodiments of the present invention provide a computer device, which may include a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the carbonate reservoir type identification method according to the first aspect when executing the program.
In a fifth aspect, an embodiment of the present invention provides a method for exploiting an oil reservoir, which may include:
identifying a reservoir type of a target zone of the reservoir based on the carbonate reservoir type identification method of the first aspect; the reservoir type includes: hole-type reservoirs, fracture-hole-type reservoirs and fracture-type reservoirs;
and setting a production well position based on the reservoir type of the reservoir target area.
In a sixth aspect, an embodiment of the present invention provides an application of the carbonate reservoir type recognition method according to the first aspect in reservoir development.
The technical scheme provided by the embodiment of the invention has the beneficial effects that at least:
the embodiment of the invention provides a carbonate reservoir type identification method, a device, equipment and application, wherein the method is used for determining a crack identification characteristic parameter through reconstruction processing of a conventional logging curve, calculating to obtain a comprehensive index reflecting the development degree of a crack, and predicting the development probability of the crack so as to determine a carbonate crack development interval; calculating fracture porosity in a fracture development interval; and identifying and dividing the type of the carbonate reservoir according to the porosity of the crack, so as to obtain a better field application effect. The method can effectively divide reservoir types by utilizing the conventional logging curve under the condition of no imaging logging, nuclear magnetic logging and other data, is convenient to apply, has high accuracy, and has great practical value and popularization significance.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of a carbonate reservoir type identification method provided in an embodiment of the present invention;
FIG. 2 is a flowchart showing the steps S12;
fig. 3 is a specific flowchart of step S13;
fig. 4 is a schematic structural diagram of a carbonate reservoir type recognition device according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The embodiment of the invention provides a carbonate reservoir type identification method, which can accurately identify fracture-cavity type, hole type and crack type reservoirs, and is mainly realized by a two-step constraint identification method, wherein the first step of pre-quantitative identification of a carbonate reservoir crack development interval is realized by processing a record carrier (conventional logging curve), amplifying response characteristics of the record carrier to the reservoir and constructing a crack identification probability model of the carbonate reservoir, so that the crack development interval of the reservoir is determined; and secondly, judging the fracture occurrence and calculating the fracture porosity of the corresponding occurrence through an empirical formula under the constraint of a fracture identification probability model, and accurately and conveniently completing quantitative data identification of the carbonate reservoir by utilizing the fracture porosity.
Referring to fig. 1, the method may include the steps of:
and S11, determining the fracture linear density of the carbonate reservoir based on the core observation data and/or the electric imaging logging data.
The method comprises the steps of carrying out actual statistics on fracture lines of a carbonate reservoir through rock core observation data or electric imaging logging data obtained in logging so as to determine the fracture line density of the carbonate reservoir. For example, it is determined what the number of fractures in a 1m core segment is.
It should be noted that, not every well logging will take a core (i.e. not every well logging will have core observation data), the core observation data is the most intuitive data, and the fracture line density of the carbonate reservoir can be effectively counted. However, under the condition of no core observation data, statistics can be performed through the electric imaging logging data, and if both data can be obtained, the effect is better under the condition of comprehensive statistics.
And step S12, determining a fracture development section of the carbonate reservoir based on the logging curve and the fracture linear density.
The step is to determine the fracture development section of the carbonate reservoir by the conventional logging curve and the fracture linear density determined in the step S11, and calculate the fracture porosity in the fracture development section by taking the fracture development section as a constraint condition, so that the fracture porosity of the non-fracture development section is not calculated, the calculated amount is saved, and the identification efficiency is improved.
Specifically, referring to fig. 2, this step may specifically include:
and step S121, calibrating the density logging curve, the acoustic time difference logging curve, the compensated neutron logging curve and/or the dual lateral resistivity logging curve to reconstruct crack identification characteristic parameters of the density ratio, the acoustic wave ratio, the neutron ratio and/or the depth lateral resistivity difference ratio of the logging.
In the embodiment of the invention, four logging curves of density, acoustic time difference, compensated neutron and double lateral resistivity, which are most sensitive to crack development, are preferably selected, and the four crack identification characteristic parameters are respectively reconstructed.
Wherein, the density ratio expression is:
in the method, in the process of the invention,
for density log, g/cm 3 ；/>
API is the true natural gamma value of the single well before normalization;
natural gamma measured maximum value of single well before normalization, < >>
；/>
Natural gamma measured minimum value of single well before normalization,/->
The method comprises the steps of carrying out a first treatment on the surface of the DG is the skeleton density of rock, and dolomite is taken to be 2.87g/cm 3 Limestone 2.71g/cm 3 。
The acoustic wave ratio expression is:
in the method, in the process of the invention,
the value is a sound wave time difference logging value, and mu s/m; />
API is the true natural gamma value of the single well before normalization;
for the measured maximum value of natural gamma of single well before normalization, < + >>
；/>
For the measured minimum value of natural gamma of single well before normalization, < ->
The method comprises the steps of carrying out a first treatment on the surface of the TM is the rock skeleton time difference, and dolomite is taken to be 143 mu s/m, and limestone is taken to be 156 mu s/m.
The neutron ratio expression is:
in the method, in the process of the invention,
neutron porosity log,%; />
API is the true natural gamma value of the single well before normalization;
for the measured maximum value of natural gamma of single well before normalization, < + >>
；/>
For the measured minimum value of natural gamma of single well before normalization, < ->
。
The depth-to-lateral resistivity difference ratio expression is:
in the method, in the process of the invention,
as the ratio of the difference in resistivity,%; />
Is a deep lateral resistivity value, Ω·m; />
Is a shallow lateral resistivity value, Ω·m.
And step S122, carrying out normalization processing on the crack identification parameters so as to carry out multi-element correlation coefficient analysis by using the crack identification parameters and the crack linear density after normalization processing.
In the embodiment of the invention, four crack identification parameters of the density ratio, the sound wave ratio, the neutron ratio and the depth lateral resistivity difference ratio can be normalized according to the following formula:
in the method, in the process of the invention,
identifying a parameter normalization value for the ith crack; />
Identifying a parameter value for the ith fracture; />
Identifying a parameter maximum for the ith fracture; />
Is the ith crackThe slot identification parameter is minimum.
In the embodiment of the invention, the crack identification parameters are normalized, so that the subsequent operation is convenient.
And step S123, performing multivariate correlation coefficient analysis based on the crack identification parameters and the crack linear density to determine the weight coefficient of each crack identification parameter.
The four types of crack identification parameter values normalized in the step S122 are compared with crack linear density values determined by core observation data and imaging logging data of a drilling coring section, and correlation coefficients of each parameter and the crack linear density are determined by utilizing a multi-element correlation coefficient method for analysis, so that weight coefficients Pi of each crack identification parameter are obtained.
It should be noted that, in this step, multiple correlation analysis is performed through each parameter and the fracture linear density value, and the correlation coefficient is the weight coefficient; the values are derived from the results of a large number of well statistics, and the weight coefficient values of different regions are different.
The density ratio, the sound wave ratio, the neutron ratio and the depth side resistivity difference ratio weight coefficient Pi of the ancient carbonate rock gas reservoir under the Jing side gas field are 0.23,0.19,0.27,0.31 respectively.
And step S124, determining the comprehensive index of the crack development degree based on the crack identification parameters and the weight coefficients.
In this step, the comprehensive index reflecting the crack development degree is obtained according to the following formula
：
In the method, in the process of the invention,
identifying a weight value of a parameter for the ith crack; />
Normalized values of parameters are identified for the ith fracture.
And step S125, determining the crack development section of the carbonate reservoir based on the comprehensive index of the crack development degree.
When the step is implemented, firstly, a frequency distribution histogram is manufactured based on the comprehensive index of the crack development degree; then, taking the comprehensive index value corresponding to the frequency peak value of the frequency distribution histogram as the standard lower limit value of the crack development section; and finally, determining the crack development section of the carbonate reservoir by using the standard lower limit value of the crack development section.
Namely: and (3) the comprehensive indexes GL of the fracture development section and the non-fracture development section determined by statistically analyzing the rock core and the imaging logging, and making a frequency distribution histogram, wherein GL corresponding to the GL frequency peak value of the fracture development section is the standard lower limit value of fracture discrimination, and the fracture development section of the carbonate reservoir is determined by the standard lower limit value.
The gas reservoir is kept by the ancient carbonate rock under the Jing side, and when the comprehensive index GL is more than or equal to 0.7, cracks develop.
And S13, calculating the fracture porosity of the fracture development section to identify the type of the carbonate reservoir based on the fracture porosity.
In the embodiment of the invention, the cracks can be divided into 3 types of low-angle cracks, inclined cracks and high-angle cracks according to the crack occurrence, and the crack occurrence is judged and the crack porosity is calculated according to a crack occurrence judgment formula and a porosity empirical formula corresponding to the cracks with different occurrence.
In specific implementation, referring to fig. 3, this step may include the following steps:
step S131, judging the type of the fracture occurrence based on the depth lateral resistivity of the dual lateral resistivity log.
The slit occurrence judgment expression in this step is as follows:
from empirical formula, when Y>0.1, then high angle crack; when Y is more than or equal to 0 and less than 0.1, the oblique joint is formed; when Y is less than 0, the crack is a low-angle crack; in the middle of
、/>
The deep and shallow lateral resistivities are respectively, and Y is the discrimination index.
And step S132, determining the crack porosity of the cracks of different occurrence types based on the depth lateral resistivity and the mud filtrate resistivity of the well logging.
The crack porosity expression in the embodiment of the invention is:
in the method, in the process of the invention,
crack porosity,%; />
The resistivity of the slurry filtrate is; a1, A2, A3 are constants, the values of which are related to crack occurrence (table 1).
Table 1 parameter value table of crack porosity interpretation model
Step S133, identifying the type of carbonate reservoir based on fracture porosity of the different occurrence type fractures.
In the embodiment of the invention, the step S133 can be used for statistically analyzing the crack porosity ranges of the cracks with different occurrence types, and comprehensively identifying the type of the carbonate reservoir by combining the carbonate reservoir type determined by the core observation data, the electric imaging logging data and/or the nuclear magnetic resonance data.
The type of carbonate reservoir in the ancient gas reservoir under the Jing side gas field is determined as the standard
>0.6% of the porous reservoir, 0.4%</>
<0.6% is a fracture-cavity reservoir, < - > in->
<0.4% is a fractured reservoir.
In a specific example, consider the gas field peach 66 well as an example, the well Ma Wu 4 1 And (3) calculating a crack development comprehensive index of 0.81 by section logging, which is larger than a crack development critical value of 0.7, and predicting the crack development of the reservoir by logging. The Y value of the dual-side logging calculation fracture occurrence judgment index is 0.17, the dual-side logging calculation fracture occurrence judgment index is judged to be a high-angle fracture, the calculated fracture porosity is 0.51%, the type of the identified reservoir is a fracture-cavity type reservoir, the reservoir is well matched with the core fracture description data, and the layer of gas testing obtains 8.8 ten thousand unimpeded flow.
In another specific example, consider the field Shaan 254 well, which is Ma Wu 1 3 And (3) calculating a crack development comprehensive index of 0.83 by section logging, which is larger than a crack development critical value of 0.7, and predicting the crack development of the reservoir by logging. And calculating a crack occurrence judgment index Y value of 0.2 by double-side logging, judging the crack occurrence judgment index Y value to be a high-angle crack, calculating the porosity of the crack to be 0.58%, and identifying the type of the reservoir as a fracture-cavity type reservoir, wherein the gas test of the reservoir obtains 34.2 ten thousand unimpeded flow.
According to the carbonate reservoir type identification method provided by the embodiment of the invention, the conventional logging curve is subjected to reconstruction processing, the crack identification characteristic parameters are determined, the comprehensive index GL reflecting the crack development degree is calculated, and the crack development probability is predicted to determine the carbonate crack development interval; calculating fracture porosity in a fracture development interval; and identifying and dividing the type of the carbonate reservoir according to the porosity of the crack, so as to obtain a better field application effect. The method can effectively divide reservoir types by utilizing the conventional logging curve under the condition of no imaging logging, nuclear magnetic logging and other data, is convenient to apply, has high accuracy, and has great practical value and popularization significance.
Based on the same inventive concept, the embodiment of the invention also provides a carbonate reservoir type recognition device, which referring to fig. 4, may include: the fracture linear density determining module 11, the fracture development stage determining module 12 and the reservoir type identifying module 13 operate according to the following principles:
the fracture linear density determining module 11 is used for determining the fracture linear density of the carbonate reservoir based on core observation data and/or electric imaging logging data;
the fracture development stage determination module 12 is configured to determine a fracture development stage of the carbonate reservoir based on the log and the fracture line density;
the reservoir type identification module 13 is used to calculate fracture porosity of the fracture development stage to identify the type of carbonate reservoir based on the fracture porosity.
In an alternative embodiment, the crack-propagation segment determination module 12 is specifically configured to:
calibrating a density logging curve, an acoustic time difference logging curve, a compensated neutron logging curve and/or a dual lateral resistivity logging curve to reconstruct crack identification characteristic parameters of a density ratio, an acoustic wave ratio, a neutron ratio and/or a depth lateral resistivity difference ratio of the logging;
performing multivariate correlation coefficient analysis based on the crack identification parameters and the crack linear density to determine weight coefficients of the crack identification parameters;
determining a comprehensive index of the crack development degree based on the crack identification parameters and the weight coefficients;
and determining a fracture development section of the carbonate reservoir based on the composite index of the fracture development degree.
In another alternative embodiment, the crack-propagation-segment determination module 12 is further configured to, prior to determining the weight coefficients for each crack-recognition parameter:
and carrying out normalization treatment on the crack identification parameters so as to carry out multi-element correlation coefficient analysis by using the crack identification parameters and the crack linear density after normalization treatment.
In another alternative embodiment, the crack-propagation segment determination module 12 is specifically configured to:
based on the comprehensive index of the crack development degree, a frequency distribution histogram is manufactured;
taking the comprehensive index value corresponding to the frequency peak value of the frequency distribution histogram as the standard lower limit value of the crack development section;
and determining the crack development section of the carbonate reservoir according to the standard lower limit value of the crack development section.
In another alternative embodiment, the reservoir type identification module 13 is specifically configured to:
judging the type of the fracture occurrence based on the depth lateral resistivity of the dual lateral resistivity log;
determining fracture porosity of the different occurrence types of fractures based on the depth lateral resistivity and the mud filtrate resistivity of the well log;
the type of the carbonate reservoir is identified based on the fracture porosity of the different occurrence type fractures.
In another alternative embodiment, the reservoir type identification module 13 is specifically further configured to:
and statistically analyzing the crack porosity ranges of the cracks with different occurrence types, and comprehensively identifying the type of the carbonate reservoir by combining the carbonate reservoir type determined by core observation data, electric imaging logging data and/or nuclear magnetic resonance data.
Based on the same inventive concept, there is also provided in an embodiment of the present invention a computer readable storage medium having stored thereon a computer program which when executed by a processor implements the above-mentioned carbonate reservoir type recognition method.
Based on the same inventive concept, the embodiment of the invention also provides a computer device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the carbonate reservoir type identification method when executing the program.
Based on the same inventive concept, the embodiment of the invention also provides an oil reservoir exploitation method, which can comprise the following steps:
firstly, identifying the reservoir type of a target area of an oil reservoir based on the carbonate reservoir type identification method; reservoir types include: hole-type reservoirs, fracture-hole-type reservoirs and fracture-type reservoirs; production well sites are then deployed based on the reservoir type of the reservoir target.
Based on the same inventive concept, the embodiment of the invention also provides application of the carbonate reservoir type identification method in oil reservoir development.
The principles of the above-mentioned apparatus, medium, related equipment and application of the embodiments of the present invention for solving the problems are similar to those of the foregoing carbonate reservoir type identification method, so the implementation of the method may be referred to the implementation of the foregoing method, and the repetition is omitted.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (9)
1. A carbonate reservoir type identification method, comprising:
determining a fracture linear density of the carbonate reservoir based on core observations and/or electrical imaging logging data;
calibrating a density logging curve, an acoustic time difference logging curve, a compensated neutron logging curve and/or a dual lateral resistivity logging curve to reconstruct crack identification parameters of a density ratio, an acoustic wave ratio, a neutron ratio and/or a depth lateral resistivity difference ratio of the log;
performing multivariate correlation coefficient analysis based on the crack identification parameters and the crack linear density to determine weight coefficients of the crack identification parameters;
determining a comprehensive index of the crack development degree based on the crack identification parameters and the weight coefficients;
determining a fracture development section of the carbonate reservoir based on the composite index of the fracture development degree;
judging the type of the fracture occurrence based on the depth lateral resistivity of the dual lateral resistivity log;
determining fracture porosity of the different occurrence types of fractures based on the depth lateral resistivity and the mud filtrate resistivity of the well log;
the type of the carbonate reservoir is identified based on the fracture porosity of the different occurrence type fractures.
2. The method of claim 1, wherein prior to the performing a multivariate correlation coefficient analysis based on the fracture identification parameters and the fracture linear density to determine weight coefficients for each fracture identification parameter, further comprising:
and carrying out normalization treatment on the crack identification parameters so as to carry out multi-element correlation coefficient analysis by using the crack identification parameters and the crack linear density after normalization treatment.
3. The method of claim 1, wherein the determining a fracture development stage of the carbonate reservoir based on the composite index of the extent of fracture development comprises:
based on the comprehensive index of the crack development degree, a frequency distribution histogram is manufactured;
taking the comprehensive index value corresponding to the frequency peak value of the frequency distribution histogram as the standard lower limit value of the crack development section;
and determining the crack development section of the carbonate reservoir according to the standard lower limit value of the crack development section.
4. The method of claim 1, wherein the identifying the type of carbonate reservoir based on the fracture porosity of different occurrence type fractures comprises:
and statistically analyzing the crack porosity ranges of the cracks with different occurrence types, and comprehensively identifying the type of the carbonate reservoir by combining the carbonate reservoir type determined by core observation data, electric imaging logging data and/or nuclear magnetic resonance data.
5. A carbonate reservoir type recognition device, comprising:
the fracture linear density determining module is used for determining the fracture linear density of the carbonate reservoir based on core observation data and/or electric imaging logging data;
the crack development section determining module is used for calibrating a density logging curve, a sound wave time difference logging curve, a compensation neutron logging curve and/or a double lateral resistivity logging curve so as to reconstruct crack identification parameters of a density ratio, a sound wave ratio, a neutron ratio and/or a depth lateral resistivity difference ratio of the logging; performing multivariate correlation coefficient analysis based on the crack identification parameters and the crack linear density to determine weight coefficients of the crack identification parameters; determining a comprehensive index of the crack development degree based on the crack identification parameters and the weight coefficients; determining a fracture development section of the carbonate reservoir based on the composite index of the fracture development degree;
the reservoir type identification module is used for judging the type of the fracture occurrence based on the depth lateral resistivity of the dual lateral resistivity logging curve; determining fracture porosity of the different occurrence types of fractures based on the depth lateral resistivity and the mud filtrate resistivity of the well log; the type of the carbonate reservoir is identified based on the fracture porosity of the different occurrence type fractures.
6. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when executed by a processor, implements the carbonate reservoir type identification method according to any one of claims 1 to 4.
7. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the carbonate reservoir type identification method of any one of claims 1 to 4 when the program is executed by the processor.
8. A method of reservoir recovery, comprising:
the carbonate reservoir type identification method according to any one of claims 1 to 4.
9. The method according to claim 8, comprising:
identifying a reservoir type of a target zone of a reservoir based on the carbonate reservoir type identification method of any one of claims 1-4; the reservoir type includes: hole-type reservoirs, fracture-hole-type reservoirs and fracture-type reservoirs;
and setting a production well position based on the reservoir type of the reservoir target area.
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