CN109779609B - Method and device for predicting scaling trend of shaft - Google Patents
Method and device for predicting scaling trend of shaft Download PDFInfo
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- CN109779609B CN109779609B CN201910098986.3A CN201910098986A CN109779609B CN 109779609 B CN109779609 B CN 109779609B CN 201910098986 A CN201910098986 A CN 201910098986A CN 109779609 B CN109779609 B CN 109779609B
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Abstract
The invention provides a method and a device for predicting a shaft scaling trend, which comprise the following steps: determining continuous matrix porosity data of a reservoir section to be logged; determining matrix permeability data corresponding to the well to be logged according to the preset corresponding relation between the porosity data and the permeability data; determining longitudinal fracture development data of a reservoir section to be logged; determining a corresponding phase section of a reservoir to be logged according to the matrix permeability data and the longitudinal fracture development data; and determining the scaling trend of the reservoir to be logged according to the corresponding phase section of the reservoir to be logged. The method for predicting the fouling tendency of the well bore is used for predicting the fouling tendency of the well bore.
Description
Technical Field
The invention relates to the field of oil exploitation, in particular to a method and a device for predicting a shaft scaling trend.
Background
In the process of petroleum production, an oil-gas well with deep original formation pressure of more than 60MPa in a production interval, namely a fractured sandstone high-pressure oil-gas well, becomes an important production field in the field of gas field exploitation at present. However, the phenomenon of shaft scaling in the production process of the fractured sandstone high-pressure oil-gas well is more and more common, and the stable production is seriously influenced.
In the prior art, the type and degree of shaft scaling of a fractured sandstone high-pressure oil-gas well cannot be predicted, so that the difficulty is increased for an applicable scaling prevention process adopted in the well completion stage of the oil-gas well, accurate scaling prevention is difficult to realize, capital waste is caused, long-term stable production of the oil-gas well is even greatly influenced, and efficient development of an oil-gas reservoir is restricted.
Disclosure of Invention
The invention provides a method and a device for predicting a shaft scaling trend, which are used for predicting the shaft scaling trend.
In a first aspect, the present invention provides a method for predicting a fouling tendency of a wellbore, comprising:
determining continuous matrix porosity data of a reservoir section to be logged;
determining matrix permeability data corresponding to the well to be logged according to a preset corresponding relation between porosity data and permeability data;
determining longitudinal fracture development data of a reservoir section to be logged;
determining the phase section distribution of the reservoir to be logged according to the matrix permeability data and the longitudinal fracture development data;
and determining the scaling trend of the reservoir to be logged according to the phase section distribution of the reservoir to be logged.
Optionally, the determining the matrix porosity data of the reservoir section to be logged comprises:
obtaining lithologic density data of the reservoir section to be measured, wherein the lithologic density data of the reservoir section is obtained by measuring the acoustic moveout of the well to be measured;
and determining continuous matrix porosity data of the reservoir section to be logged according to the reservoir section lithology density data.
Optionally, the determining longitudinal fracture development data of the reservoir section to be logged includes:
acquiring at least one imaging log data;
and interpreting the crack development degree of the to-be-logged well according to the at least one imaging logging data, and determining the longitudinal fracture development data of the reservoir section to be logged.
Optionally, the determining the phase section distribution of the reservoir to be logged according to the matrix permeability data and the longitudinal fracture development data includes:
inputting the matrix permeability data and the longitudinal fracture development data into a phase section empirical selection model to obtain the phase section distribution of the reservoir to be logged, which is output by the phase section empirical selection model, wherein the phase section comprises at least one of a fracture system permeable phase section, a matrix reservoir permeable phase section and a matrix reservoir diffusion phase section.
Optionally, the determining the scaling trend of the reservoir to be logged according to the phase section distribution of the reservoir to be logged includes:
acquiring the total thickness of the permeable phase section of the reservoir stratum of the well to be detected, the total thickness of the permeable phase section of the matrix reservoir stratum and the total thickness of the diffusion phase section of the matrix reservoir stratum;
determining a scaling tendency value of the well to be measured by adopting a formula F (h3)/(h1+ h2+ h3), wherein F is the scaling tendency value of the well to be measured, h1 is the total thickness of the permeable phase section of the fracture system, h2 is the total thickness of the permeable phase section of the matrix reservoir, and h3 is the total thickness of the diffusion phase section of the matrix reservoir;
and determining the scaling trend of the well to be logged according to the scaling trend value of the well to be logged.
A second aspect of the present invention provides a wellbore fouling tendency prediction device, comprising:
the porosity determination module is used for determining continuous matrix porosity data of a reservoir section to be logged;
the permeability determining module is used for determining matrix permeability data corresponding to the well to be logged according to the corresponding relation between preset porosity data and permeability data;
the fracture development determining module is used for determining longitudinal fracture development data of a reservoir section to be logged;
the phase section selection module is used for determining the phase section distribution of the reservoir to be logged according to the matrix permeability data and the longitudinal fracture development data;
and the trend determining module is used for determining the scaling trend of the reservoir to be logged according to the phase section distribution of the reservoir to be logged.
Optionally, the porosity determination module includes:
the first acquisition unit is used for acquiring the lithologic density data of the reservoir section to be measured, wherein the lithologic density data of the reservoir section is obtained by measuring the acoustic time difference of the well to be measured;
and the first determination unit is used for determining continuous matrix porosity data of the reservoir section to be logged according to the lithologic density data of the reservoir section.
Optionally, the fracture development determining module includes:
the second acquisition unit is used for acquiring at least one imaging logging data;
and the second determination unit is used for explaining the development degree of the crack of the reservoir section to be logged according to the at least one imaging logging data and determining the longitudinal fracture development data of the reservoir section to be logged.
Optionally, the phase section selection module is specifically configured to input the matrix permeability data and the longitudinal fracture development data into a phase section empirical selection model, and obtain the phase section distribution of the reservoir to be logged, which is output by the phase section empirical selection model, where the phase section includes at least one of a fracture system permeable phase section, a matrix reservoir permeable phase section, and a matrix reservoir diffusion phase section.
Optionally, the trend determining module includes:
the third acquisition unit is used for acquiring the total thickness of the permeable phase section of the reservoir stratum of the well to be detected, the total thickness of the permeable phase section of the matrix reservoir stratum and the total thickness of the diffusion phase section of the matrix reservoir stratum;
the calculation unit is used for determining the scaling tendency value of the well to be measured by adopting a formula F (h3)/(h1+ h2+ h3), wherein F is the scaling tendency value of the well to be measured, h1 is the total thickness of the permeable phase section of the fracture system, h2 is the total thickness of the permeable phase section of the matrix reservoir, and h3 is the total thickness of the diffusion phase section of the matrix reservoir;
and the prediction unit is used for determining the scaling trend of the well to be logged according to the scaling trend value of the well to be logged.
A third aspect of the present invention provides an electronic apparatus comprising: a memory and a processor;
the memory for storing executable instructions of the processor;
the processor is configured to perform the method referred to in the first aspect and alternatives thereof via execution of the executable instructions.
In a fourth aspect of the present invention, there is provided a storage medium having stored thereon a computer program which, when executed by a processor, implements the method of the first aspect and its alternatives.
According to the method and the device for predicting the shaft scaling trend, the matrix permeability data is determined by determining the matrix porosity data to be logged, the corresponding phase section of the reservoir to be logged is determined according to the matrix permeability data and the determined longitudinal crack development data, and the scaling trend of the shaft to be logged is determined, so that the scaling trend of the shaft can be predicted, accurate scale prevention is performed, and long-term stable production of an oil-gas well is guaranteed.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for predicting a fouling tendency of a wellbore according to an embodiment of the present invention;
fig. 2 is a schematic flowchart of step S11 according to the embodiment of the present invention;
fig. 3 is a schematic flowchart of step S13 according to the embodiment of the present invention;
fig. 4 is a schematic flowchart of a step S15 according to the embodiment of the present invention;
FIG. 5 is a schematic flow chart of a wellbore fouling tendency prediction device according to an embodiment of the present invention;
FIG. 6 is a schematic structural diagram of a porosity determination module according to an embodiment of the present invention;
FIG. 7 is a schematic structural diagram of a fracture development determination module according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of a trend determining module according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," and the like in the description of the invention and the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein.
It should be understood that, in various embodiments of the present invention, the sequence numbers of the processes do not mean the execution sequence, and the execution sequence of the processes should be determined by the functions and the internal logic of the processes, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
It should be understood that in the present application, "comprising" and "having" and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be understood that in the present invention, "B corresponding to a", "a corresponds to B", or "B corresponds to a" means that B is associated with a, from which B can be determined. Determining B from a does not mean determining B from a alone, but may be determined from a and/or other information.
As used herein, "if" may be interpreted as "at … …" or "when … …" or "in response to a determination" or "in response to a detection", depending on the context.
The technical solution of the present invention will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.
Fig. 1 is a schematic flow chart of a method for predicting a fouling tendency of a wellbore according to an embodiment of the present invention.
The method may be performed by a wellbore fouling tendency prediction device, which may optionally be provided separately or integrated in the processor.
Referring to fig. 1, a method for determining the volume of a miscible zone in a reservoir of a sandstone reservoir comprises the following steps:
s11: and determining continuous matrix porosity data of the reservoir section to be logged.
In practical application, continuous matrix porosity data of a reservoir section to be logged can be obtained firstly, and a specific obtaining method can be determined by a sound wave phase detection method.
S12: and determining the matrix permeability data corresponding to the well to be logged according to the preset corresponding relation between the porosity data and the permeability data.
In practical application, because the porosity data and the permeability data have a corresponding relationship, when the continuous matrix porosity data of the reservoir section to be logged is determined, the corresponding matrix permeability data can be determined through the corresponding relationship preset by a user.
S13: and determining longitudinal fracture development data of the reservoir section to be logged.
In practical application, the longitudinal crack development data of the reservoir section of the well to be measured can be obtained by carrying out well logging imaging on the well to be measured, acquiring corresponding imaging data according to the imaging, and explaining the crack development degree of the well to be measured according to the imaging well logging data.
S14: and determining the phase section distribution of the reservoir to be logged according to the matrix permeability data and the longitudinal fracture development data.
Optionally, the determining the phase section distribution of the reservoir to be logged according to the matrix permeability data and the longitudinal fracture development data includes:
inputting the matrix permeability data and the longitudinal fracture development data into a phase section empirical selection model to obtain the phase section distribution of the reservoir to be logged, which is output by the phase section empirical selection model, wherein the phase section comprises at least one of a fracture system permeable phase section, a matrix reservoir permeable phase section and a matrix reservoir diffusion phase section.
The permeable phase of the fracture system is a fracture centralized development section, and reservoirs in the section are communicated with each other; the permeable phase of the matrix reservoir is a reservoir section with a fracture undeveloped section and the permeability of the matrix reservoir is more than 0.1 millidarcy; the matrix reservoir diffusion phase refers to a reservoir interval in which fractures do not develop, but the permeability of the matrix reservoir is less than 0.1 millidarcy.
In practical application, different oil and gas reservoirs have different division modes according to fracture properties and permeability, so that a phase section experience selection model can be established, and the fracture properties and permeability of wells of different oil and gas reservoirs and corresponding phase sections are input into the phase section experience selection model to be trained. After the training is completed, the phase section empirical selection model can directly output the phase section distribution of the well reservoir according to the input matrix permeability data and the longitudinal fracture development data.
In another possible embodiment, slots with a longitudinal spacing of less than 5 m can also be divided into concentrated segments.
S15: and determining the scaling trend of the well to be logged according to the phase section distribution of the reservoir to be logged.
In practical application, the trend value corresponding to the well to be measured can be determined by determining the total thickness of each phase section of the reservoir of the well to be measured. And determining the scaling trend of the well to be logged through the trend value.
According to the method for predicting the shaft scaling trend, the matrix permeability data is determined by determining the matrix porosity data to be logged, the corresponding phase section of the reservoir to be logged is determined according to the matrix permeability data and the determined longitudinal fracture development data, and the scaling trend of the shaft to be logged is determined, so that the scaling trend of the shaft can be predicted, accurate scale prevention is performed, and long-term stable production of oil and gas wells is guaranteed.
Fig. 2 is a schematic flowchart of step S11 according to an embodiment of the present invention.
Referring to fig. 2, step S11 includes:
s21: and acquiring lithologic density data of the reservoir section to be logged, wherein the lithologic density data of the reservoir section is obtained by performing acoustic moveout measurement on the reservoir section to be logged.
S22: and determining continuous matrix porosity data of the reservoir section to be logged according to the lithologic density data of the reservoir section.
In practical application, acoustic detection can be carried out on the to-be-logged well and a feedback acoustic signal can be obtained, and lithologic density data of the reservoir section to be logged can be determined through a logging analysis technology from acoustic time difference in the feedback acoustic signal. Meanwhile, the lithologic density data and the matrix porosity data have relevance, and continuous matrix porosity data of the reservoir section to be logged can be determined according to the obtained lithologic density data of the reservoir section to be logged.
In another possible implementation mode, the lithology density data can also be directly obtained through lithology density logging, and the accuracy of the porosity interpretation of the data obtained through the direct lithology density logging is higher than that of the result obtained through the acoustic wave time difference calculation.
Fig. 3 is a flowchart illustrating a step S13 according to an embodiment of the present invention.
Referring to fig. 3, step S13 includes:
s31: at least one imaging log is acquired.
S32: and interpreting the development degree of the crack to be logged according to at least one imaging logging data, and determining the longitudinal crack development data of the reservoir section to be logged.
The imaging log data may be data obtained by imaging a formation to be logged, and the formation imaging may include: formation micro-resistivity scanning imaging (FMI), high resolution imaging (FMS), and electromagnetic Interference imaging (EMI).
In practical application, after at least one type of data is acquired, the fracture development degree of the reservoir section to be logged can be interpreted according to the imaging data, and fracture development data in the longitudinal direction of the reservoir section to be logged are determined.
Fig. 4 is a flowchart illustrating a step S15 according to an embodiment of the present invention.
Referring to fig. 4, step S14 includes:
s41: and acquiring the total thickness of the permeable phase section of the reservoir stratum of the well to be detected, the total thickness of the permeable phase section of the matrix reservoir stratum and the total thickness of the diffusion phase section of the matrix reservoir stratum.
In practice, it is also desirable to obtain the total thickness of the various phase sections of the reservoir section of the well. Specifically, the total thickness of the permeable phase section of the fracture system, the total thickness of the permeable phase section of the matrix reservoir and the total thickness of the diffusion phase section of the matrix reservoir need to be determined respectively. In addition, the total thickness of each phase section comprises the sum of the thicknesses of the non-perforated production sections communicating with the production reservoir section corresponding to that phase section.
S42: and determining a scaling tendency value of the well to be measured by adopting a formula F (h3)/(h1+ h2+ h3), wherein F is the scaling tendency value of the well to be measured, h1 is the total thickness of the permeable phase section of the fracture system, h2 is the total thickness of the permeable phase section of the matrix reservoir, and h3 is the total thickness of the permeable phase section of the matrix reservoir.
S43: and determining the scaling trend of the well to be logged according to the scaling trend value of the well to be logged.
In practical application, when the scaling tendency value is less than 0.1, the oil and gas well can be determined not to be scaled; when the fouling tendency value is greater than or equal to 0.1, it can be determined that fouling of the oil and gas well may occur.
And when F is more than or equal to 0.1 and less than or equal to 1, the larger F is, the stronger the scaling capacity of the oil-gas well is, the trend values in the range can be classified, and the corresponding scaling method is determined according to different types.
According to the method for predicting the shaft scaling trend, the matrix permeability data is determined by determining the matrix porosity data to be logged, the corresponding phase section of the reservoir to be logged is determined according to the matrix permeability data and the determined longitudinal fracture development data, and the scaling trend of the shaft to be logged is determined, so that the scaling trend of the shaft can be predicted, accurate scale prevention is performed, and long-term stable production of oil and gas wells is guaranteed.
Fig. 5 is a schematic flow chart of a wellbore fouling tendency prediction apparatus according to an embodiment of the present invention.
Referring to fig. 5, the apparatus for predicting a fouling tendency of a wellbore includes:
and a porosity determination module 51 for determining continuous matrix porosity data of the reservoir section to be logged.
And a permeability determining module 52, configured to determine matrix permeability data corresponding to the well to be logged according to a preset correspondence between the porosity data and the permeability data.
And the fracture development determining module 53 is used for determining longitudinal fracture development data of the reservoir section to be measured.
And the phase section selection module 54 is used for determining the phase section distribution of the reservoir to be logged according to the matrix permeability data and the longitudinal fracture development data.
The phase section selection module 54 is specifically configured to input the matrix permeability data and the longitudinal fracture development data into the phase section empirical selection model, and obtain the phase section distribution of the reservoir to be logged, which is output by the phase section empirical selection model, where the phase section includes at least one of a permeable phase section of the fracture system, a permeable phase section of the matrix reservoir, and a diffusion phase section of the matrix reservoir.
And the trend determining module 55 is used for determining the scaling trend of the reservoir to be logged according to the phase section distribution of the reservoir to be logged.
The device for predicting the shaft scaling trend determines the matrix permeability data by determining the matrix porosity data to be logged, determines the corresponding phase section of the reservoir to be logged according to the matrix permeability data and the determined longitudinal fracture development data, and determines the scaling trend of the well to be logged, so that the scaling trend of the shaft can be predicted, accurate scale prevention is performed, and long-term stable generation of an oil-gas well is ensured.
Fig. 6 is a schematic structural diagram of a porosity determination module according to an embodiment of the present invention.
Referring to fig. 6, the porosity determination module includes:
the first obtaining unit 61 is configured to obtain lithology density data of a reservoir section to be logged, where the lithology density data of the reservoir section is obtained by performing acoustic moveout measurement on the reservoir section to be logged.
The first determination unit 62 is configured to determine continuous matrix porosity data of the reservoir section to be logged according to the lithologic density data of the reservoir section.
FIG. 7 is a schematic structural diagram of a fracture development determination module according to an embodiment of the present invention;
referring to fig. 7, the fracture development determination module includes:
a second acquisition unit 71 for acquiring at least one imaging log data.
And the second determining unit 72 is configured to interpret the crack development degree to be logged according to the at least one imaging logging data, and determine the longitudinal fracture development data of the reservoir section to be logged.
Fig. 8 is a schematic structural diagram of a trend determining module according to an embodiment of the present invention.
Referring to fig. 8, the trend determining module includes:
and the third obtaining unit 81 is configured to obtain the total thickness of the permeable phase section of the fracture system, the total thickness of the permeable phase section of the matrix reservoir and the total thickness of the diffusion phase section of the matrix reservoir of the reservoir to be logged.
And the calculating unit 82 is used for determining a scaling tendency value of the well to be measured by adopting a formula F ═ h3)/(h1+ h2+ h3, wherein F is the scaling tendency value of the well to be measured, h1 is the total thickness of the permeable phase section of the fracture system, h2 is the total thickness of the permeable phase section of the matrix reservoir, and h3 is the total thickness of the diffusion phase section of the matrix reservoir.
And the prediction unit 83 is used for determining the scaling trend of the well to be logged according to the scaling trend value of the well to be logged.
The device for predicting the shaft scaling trend determines the matrix permeability data by determining the matrix porosity data to be logged, determines the corresponding phase section of the reservoir to be logged according to the matrix permeability data and the determined longitudinal fracture development data, and determines the scaling trend of the well to be logged, so that the scaling trend of the shaft can be predicted, accurate scale prevention is performed, and long-term stable generation of an oil-gas well is ensured.
The present invention also provides an electronic device, comprising: a memory and a processor;
a memory for storing executable instructions of the processor;
the processor is configured to perform the method for determining the volume of the miscible zone in a reservoir of a sandstone reservoir as referred to in figures 1-3, via execution of executable instructions.
The readable storage medium may be a computer storage medium or a communication medium. Communication media includes any medium that facilitates transfer of a computer program from one place to another. Computer storage media may be any media that can be accessed by a general purpose or special purpose computer. For example, a readable storage medium is coupled to the processor such that the processor can read information from, and write information to, the readable storage medium. Of course, the readable storage medium may also be an integral part of the processor. The processor and the readable storage medium may reside in an Application Specific Integrated Circuits (ASIC). Additionally, the ASIC may reside in user equipment. Of course, the processor and the readable storage medium may also reside as discrete components in a communication device.
The present invention also provides a storage medium having stored thereon a computer program which, when executed by a processor, implements the method of determining the volume of a miscible zone in a reservoir of a sandstone reservoir of figures 1-3.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A wellbore fouling trend prediction method, comprising:
determining continuous matrix porosity data of a reservoir section to be logged;
determining matrix permeability data corresponding to the well to be logged according to a preset corresponding relation between porosity data and permeability data;
determining longitudinal fracture development data of a reservoir section to be logged;
determining the phase section distribution of the reservoir to be logged according to the matrix permeability data and the longitudinal fracture development data; the phase section comprises at least one of a fracture system permeable phase section, a matrix reservoir permeable phase section and a matrix reservoir diffusion phase section; the permeable phase of the fracture system is a fracture centralized development section, and reservoirs in the section are communicated with each other; the permeable phase of the matrix reservoir is a reservoir section with a fracture undeveloped section and the permeability of the matrix reservoir is more than 0.1 millidarcy; the matrix reservoir diffusion phase refers to a reservoir section of which the fracture does not develop but the matrix reservoir permeability is less than 0.1 millidarcy;
acquiring the total thickness of the permeable phase section of the reservoir to be logged, the total thickness of the permeable phase section of the matrix reservoir and the total thickness of the diffusion phase section of the matrix reservoir;
determining a scaling tendency value of the well to be measured by adopting a formula F (h3)/(h1+ h2+ h3), wherein F is the scaling tendency value of the well to be measured, h1 is the total thickness of the permeable phase section of the fracture system, h2 is the total thickness of the permeable phase section of the matrix reservoir, and h3 is the total thickness of the diffusion phase section of the matrix reservoir;
determining the scaling trend of the well to be logged according to the scaling trend value of the well to be logged;
when the scaling tendency value is less than 0.1, determining that the oil and gas well is not scaled; when the scaling tendency value is greater than or equal to 0.1, determining that the oil and gas well is scaled;
and when F is more than or equal to 0.1 and less than or equal to 1, classifying the trend values in the range, and determining the corresponding descaling method according to different types.
2. The method of claim 1, wherein determining the continuous matrix porosity data for the reservoir section to be logged comprises:
obtaining lithologic density data of the reservoir section to be measured, wherein the lithologic density data of the reservoir section is obtained by measuring the acoustic moveout of the well to be measured;
and determining continuous matrix porosity data of the reservoir section to be logged according to the reservoir section lithology density data.
3. The method of claim 1, wherein determining longitudinal fracture development data for the reservoir section to be logged comprises:
acquiring at least one imaging log data;
and interpreting the crack development degree of the to-be-logged well according to the at least one imaging logging data, and determining the longitudinal fracture development data of the reservoir section to be logged.
4. The method of claim 1, wherein determining a facies segment distribution for the reservoir to be logged from the matrix permeability data and the longitudinal fracture development data comprises:
and inputting the matrix permeability data and the longitudinal fracture development data into a phase section empirical selection model to obtain the phase section distribution of the reservoir to be logged, which is output by the phase section empirical selection model.
5. A wellbore fouling trend prediction device, comprising:
the porosity determination module is used for determining continuous matrix porosity data of a reservoir section to be logged;
the permeability determining module is used for determining matrix permeability data corresponding to the well to be logged according to the corresponding relation between preset porosity data and permeability data;
the fracture development determining module is used for determining longitudinal fracture development data of a reservoir section to be logged;
the phase section selection module is used for determining the phase section distribution of the reservoir to be logged according to the matrix permeability data and the longitudinal fracture development data; the phase section comprises at least one of a fracture system permeable phase section, a matrix reservoir permeable phase section and a matrix reservoir diffusion phase section; the permeable phase of the fracture system is a fracture centralized development section, and reservoirs in the section are communicated with each other; the permeable phase of the matrix reservoir is a reservoir section with a fracture undeveloped section and the permeability of the matrix reservoir is more than 0.1 millidarcy; the matrix reservoir diffusion phase refers to a reservoir section of which the fracture does not develop but the matrix reservoir permeability is less than 0.1 millidarcy;
the third acquisition unit is used for acquiring the total thickness of the permeable phase section of the reservoir to be logged, the total thickness of the permeable phase section of the matrix reservoir and the total thickness of the diffusion phase section of the matrix reservoir;
the calculation unit is used for determining the scaling tendency value of the well to be measured by adopting a formula F (h3)/(h1+ h2+ h3), wherein F is the scaling tendency value of the well to be measured, h1 is the total thickness of the permeable phase section of the fracture system, h2 is the total thickness of the permeable phase section of the matrix reservoir, and h3 is the total thickness of the diffusion phase section of the matrix reservoir; the prediction unit is used for determining the scaling trend of the well to be logged according to the scaling trend value of the well to be logged;
when the scaling tendency value is less than 0.1, determining that the oil and gas well is not scaled; when the scaling tendency value is greater than or equal to 0.1, determining that the oil and gas well is scaled;
and when F is more than or equal to 0.1 and less than or equal to 1, classifying the trend values in the range, and determining the corresponding descaling method according to different types.
6. The apparatus of claim 5, wherein the porosity determination module comprises:
the first acquisition unit is used for acquiring the lithologic density data of the reservoir section to be measured, wherein the lithologic density data of the reservoir section is obtained by measuring the acoustic time difference of the well to be measured;
and the first determination unit is used for determining continuous matrix porosity data of the reservoir section to be logged according to the lithologic density data of the reservoir section.
7. The apparatus of claim 5, wherein the fracture development determination module comprises:
the second acquisition unit is used for acquiring at least one imaging logging data;
and the second determination unit is used for explaining the development degree of the crack of the reservoir section to be logged according to the at least one imaging logging data and determining the longitudinal fracture development data of the reservoir section to be logged.
8. The apparatus of claim 5, wherein the phase section selection module is specifically configured to input the matrix permeability data and the longitudinal fracture development data into a phase section empirical selection model, and obtain a phase section distribution of the reservoir to be logged output by the phase section empirical selection model.
9. An electronic device, comprising: a memory and a processor;
the memory for storing executable instructions of the processor;
the processor is configured to perform the method of any of claims 1-4 via execution of the executable instructions.
10. A storage medium having a computer program stored thereon, comprising: the program, when executed by a processor, implements the method of any of claims 1-4.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910098986.3A CN109779609B (en) | 2019-01-31 | 2019-01-31 | Method and device for predicting scaling trend of shaft |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910098986.3A CN109779609B (en) | 2019-01-31 | 2019-01-31 | Method and device for predicting scaling trend of shaft |
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