CN111781661A - Method and device for predicting sedimentary microphase plane spread in small-well area - Google Patents
Method and device for predicting sedimentary microphase plane spread in small-well area Download PDFInfo
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Abstract
The invention provides a method and a device for predicting sedimentary microphase plane spread in a well-lacking area, wherein the method comprises the following steps: determining sand contents corresponding to different types of sediment micro-phases according to exploratory well data of the area with less wells; determining a characteristic value of seismic attribute data of a target stratum according to seismic data of a well-lacking area; obtaining the relationship between the sand content corresponding to the sedimentary micro-facies of different types and the characteristic value of the seismic attribute data according to the sand content corresponding to the sedimentary micro-facies of different types and the characteristic value of the seismic attribute data of the target stratum; and obtaining sedimentary microfacies plane spread data of the target stratum in the low-well area according to the relationship between the sand content corresponding to different types of sedimentary microfacies and the characteristic value of the seismic attribute data of the target stratum. The invention can predict the sedimentary microphase plane distribution in the area with few wells, and has high prediction precision.
Description
Technical Field
The invention relates to the technical field of geological research, in particular to a sedimentary microphase plane spread prediction method and a sedimentary microphase plane spread prediction device in a small well area.
Background
The sedimentary microfacies plane spread determines the plane spread of favorable reservoirs, and directly influences the trap area determination, resource quantity estimation and exploratory well deployment schemes of the constructed lithologic oil and gas reservoirs. In the exploration stage, if the sedimentary microphase plane spread of the main target interval can be accurately predicted by means of a small amount of exploratory well information and combining seismic data, the exploratory well success rate and the prospecting effect of the lithologic oil and gas reservoir can be greatly improved.
At present, for an early exploration stage, the prior art only determines the type of a large sedimentary facies according to a few exploratory well information, or schematically outlines the planar form of a large sedimentary system according to seismic attributes, so that the prior art is only limited to research of a macroscopic sedimentary system and cannot accurately depict the planar distribution of various microphases in the macroscopic sedimentary system.
Disclosure of Invention
The invention provides a sedimentary microfacies plane spread prediction method for a well-lacking area, which is used for predicting sedimentary microfacies plane spread of the well-lacking area and has high prediction precision and comprises the following steps:
determining sand contents corresponding to different types of sediment micro-phases according to exploratory well data of the area with less wells;
determining a characteristic value of seismic attribute data of a target stratum according to seismic data of a well-lacking area;
obtaining the relationship between the sand content corresponding to the sedimentary micro-facies of different types and the characteristic value of the seismic attribute data according to the sand content corresponding to the sedimentary micro-facies of different types and the characteristic value of the seismic attribute data of the target stratum;
and obtaining sedimentary microfacies plane spread data of the well-lacking area according to the relationship between the sand content corresponding to different types of sedimentary microfacies and the characteristic value of the seismic attribute data.
The invention provides a sedimentary microfacies plane spread prediction method for a well-lacking area, which is used for predicting sedimentary microfacies plane spread of the well-lacking area and has high prediction precision, and the device comprises the following steps:
the sand content determining module is used for determining sand content corresponding to different types of sediment micro-phases according to exploratory well data of the area with less wells;
the seismic attribute data characteristic value determining module is used for determining the characteristic value of the seismic attribute data of the target stratum according to the seismic data of the less-well area;
the relation data acquisition module is used for acquiring the relation between the sand content corresponding to the different types of sedimentary micro-facies and the characteristic value of the seismic attribute data of the target stratum according to the sand content corresponding to the different types of sedimentary micro-facies and the characteristic value of the seismic attribute data of the target stratum;
and the sedimentary microfacies plane spread data acquisition module is used for acquiring sedimentary microfacies plane spread data of the area with less wells according to the relationship between the sand content corresponding to different types of sedimentary microfacies and the characteristic value of the seismic attribute data.
The embodiment of the invention also provides computer equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein when the processor executes the computer program, the method for predicting the sedimentary microphase planform spread of the well-poor area is realized.
The embodiment of the invention also provides a computer readable storage medium, which stores a computer program for executing the sedimentary microphase planar spread prediction method in the well-lacking area.
In the embodiment of the invention, the sand content corresponding to different types of sediment micro-phases is determined according to exploratory well data of a low-well area; determining a characteristic value of seismic attribute data of a target stratum according to seismic data of a well-lacking area; obtaining the relationship between the sand content corresponding to the sedimentary micro-facies of different types and the characteristic value of the seismic attribute data according to the sand content corresponding to the sedimentary micro-facies of different types and the characteristic value of the seismic attribute data of the target stratum; and obtaining sedimentary microfacies plane spread data of the well-lacking area according to the relationship between the sand content corresponding to different types of sedimentary microfacies and the characteristic value of the seismic attribute data. In the embodiment of the invention, the sand content corresponding to different types of sedimentary microfacies is firstly obtained, then the characteristic value of the seismic attribute data is obtained, then the relation between the sand content corresponding to different types of sedimentary microfacies and the characteristic value of the seismic attribute data is constructed, and the sedimentary microfacies planar spread data of the low-well area is obtained based on the relation, so that the sedimentary microfacies planar spread data of the low-well area is obtained by taking the relation between the sand content corresponding to different types of sedimentary microfacies and the characteristic value of the seismic attribute data into consideration, and the sedimentary microfacies planar spread prediction result is more accurate.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:
FIG. 1 is a flow chart of a method for predicting facies planform spread of sediment in a well-deficient area according to an embodiment of the present invention;
FIG. 2 is a chart of sand content corresponding to different deposition micro-phases as determined in an embodiment of the present invention;
FIG. 3 is a diagram of virtual control points based on seismic attribute data established in an example of the present invention;
FIG. 4 is a plan view of a sand fraction contour line drawn using a method according to an embodiment of the present invention;
FIG. 5 is a sand content equivalence curve chart drawn only according to exploratory well data in the prior art;
FIG. 6 is a schematic representation of a deposition microphase planar layout as drawn in an embodiment of the present invention;
fig. 7 is a schematic diagram of a prediction apparatus for microphase planar spread in a low-well area according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
The inventor thinks that in the prior art, the prediction precision is not high due to the fact that the potential correlation between exploratory well data and seismic data is not fully utilized to conduct sedimentary microfacies plane spreading research, and based on the fact, the invention considers the potential correlation between the exploratory well data and the seismic data, namely the relation between the sand content corresponding to different types of sedimentary microfacies and the characteristic value of seismic attribute data, so as to improve the prediction precision.
Fig. 1 is a flowchart of a method for predicting facies planespread of sedimentary microfacies in a well-deficient area according to an embodiment of the present invention, as shown in fig. 1, the method includes:
103, obtaining the relationship between the sand content corresponding to the sedimentary micro-facies of different types and the characteristic value of the seismic attribute data according to the sand content corresponding to the sedimentary micro-facies of different types and the characteristic value of the seismic attribute data of the target stratum;
and 104, obtaining sedimentary microfacies plane spread data of the target stratum in the low-well area according to the relationship between the sand content corresponding to different types of sedimentary microfacies and the characteristic value of the seismic attribute data of the target stratum.
In the embodiment of the invention, the sand content corresponding to different types of sedimentary microfacies is firstly obtained, then the characteristic value of the seismic attribute data is obtained, then the relation between the sand content corresponding to different types of sedimentary microfacies and the characteristic value of the seismic attribute data is constructed, and the sedimentary microfacies planar spread data of the low-well area is obtained based on the relation, so that the sedimentary microfacies planar spread data of the low-well area is obtained by taking the relation between the sand content corresponding to different types of sedimentary microfacies and the characteristic value of the seismic attribute data into consideration, and the sedimentary microfacies planar spread prediction result is more accurate.
The deposition microphase refers to the minimum unit with deposition characteristics and a certain plane arrangement rule on the section with unique rock structure, thickness, rhythm and the like in the range of a subphase band.
In one embodiment, before determining the sand content corresponding to different types of depositional micro-domains according to exploratory well data of a low-well area, the method further comprises the following steps:
and analyzing the sedimentary background, the rock core and the logging facies of the low-well area, and determining the type of the sedimentary microfacies of the target stratum of the low-well area.
In specific implementation, the types of sedimentary microfacies of the target formation in the low-well area include various types, such as an underwater diversion river channel, an underwater diversion bay, an estuary dam, a sand mat and a shoal lake, wherein the dominant microfacies are the underwater diversion river channel, the estuary dam and the sand mat, and the background microfacies are the underwater diversion bay and the shoal lake.
In one embodiment, the sand fraction may be a correlation chart between different types of sedimentary microphases and sand fraction.
In one embodiment, determining eigenvalues of seismic attribute data of a target formation from seismic data of a low-well region comprises:
acquiring seismic attribute data of a target stratum according to seismic data of a well-lacking area;
and determining the characteristic value of the seismic attribute data of the target stratum according to the seismic attribute data of the target stratum.
In one embodiment, the seismic attribute data includes one or any combination of average arc length, average amplitude, root mean square amplitude, maximum amplitude, average frequency.
In specific implementation, seismic attribute data such as the average arc length, the average amplitude, the root-mean-square amplitude, the maximum amplitude, the average frequency and the like of different types of sedimentary microfacies can be obtained according to seismic data of a few-well area.
In one embodiment, determining the eigenvalues of the seismic attribute data of the target formation from the seismic attribute data of the target formation comprises:
determining plane extension ranges of different types of sedimentary microfacies according to exploratory well data of the area with few wells;
establishing virtual control point attribute values of different types of sedimentary microfacies according to the plane extension range of the different types of sedimentary microfacies and seismic attribute data of a target stratum;
and determining the characteristic value of the seismic attribute data of the target stratum according to the plane extension range and the virtual control point attribute values of the sedimentary microfacies of different types.
In specific implementation, the planar extension ranges of the different types of deposited microphases are different, for example, the planar extension range of the underwater diversion river channel is 800-1340 m.
And then, taking the plane extension range of the different types of sedimentary microfacies as a constraint condition, and establishing virtual control point attribute values of the different types of sedimentary microfacies according to the principle that at least 3 points control one microfacies. For example, taking a estuary dam as an example, taking a plane extension range 600m as a lower limit, and performing thinning on seismic attribute data at an interval of 300m according to the principle that at least 3 points control one microphase to obtain attribute values of 748 virtual control points depositing the microphase.
In one embodiment, before obtaining the relationship between the sand content corresponding to the different types of depositional micro-facies and the characteristic value of the seismic attribute data according to the sand content corresponding to the different types of depositional micro-facies and the characteristic value of the seismic attribute data of the target stratum, the method further comprises:
carrying out normalization processing on the characteristic value of the seismic attribute data of the target stratum;
obtaining the relationship between the sand content corresponding to the sedimentary micro-facies of different types and the characteristic value of the seismic attribute data according to the sand content corresponding to the sedimentary micro-facies of different types and the characteristic value of the seismic attribute data of the target stratum, wherein the relationship comprises the following steps:
and obtaining the relation between the sand content and the characteristic value of the seismic attribute data corresponding to the different types of sedimentary microfacies according to the relation between the different types of sedimentary microfacies and the sand content and the characteristic value of the seismic attribute data of the target stratum after normalization processing.
In specific implementation, the planar extension range of the sedimentary microfacies can be used as a search radius, the average value of a certain type of seismic attribute data in the planar extension radius range is used as the characteristic value of a certain type of seismic attribute data in a target stratum based on the attribute value of the virtual control point of the sedimentary microfacies, and all the characteristic values are subjected to normalization processing. For example, based on the attribute values of the virtual control points of 748 sedimentary microfacies, the average values of 5 types of seismic attribute data of average arc length, average amplitude, root mean square amplitude, maximum amplitude and average frequency are obtained by taking the plane extension range 600m of the dominant microfacies as the search radius, the characteristic values of 5 types of seismic attribute data of average arc length, average amplitude, root mean square amplitude, maximum amplitude and average frequency of the three sections of the riverway group of the target stratum are taken as the characteristic values, and all the characteristic values are normalized.
In one embodiment, obtaining the relationship between the sand content corresponding to the different types of depositional micro-facies and the eigenvalue of the seismic attribute data of the target formation according to the sand content corresponding to the different types of depositional micro-facies and the eigenvalue of the seismic attribute data may include:
and analyzing the relation between the sand content of the known exploratory well and the seismic attribute data of various target stratums, and establishing a quantitative relation R between the sand content of the exploratory well and the seismic attribute data. For example, the correlation coefficient R in a fitting relationship2Selecting more than 0.80 as a lower limit of reliability, and finally determining and selecting a combination of three seismic attribute data of root-mean-square amplitude, average arc length and average bandwidth to fit the relationship between the three seismic attribute data through screening, wherein the specific quantitative relation R is that the sand content is-0.88488 × average arc length +1.041814 × average bandwidth +0.468967 × root-mean-square amplitude (wherein R is the ratio of the sand content to the average arc length of-0.88488 × average arc length +1.041814 × average bandwidth +0.468967 × root-mean-square2＝0.85)。
In one embodiment, obtaining depositional microfacies planar spread data for a well-poor region based on a relationship between sand content corresponding to different types of depositional microfacies and eigenvalues of seismic attribute data comprises:
obtaining sand content equivalent data according to the relationship between the sand content corresponding to different types of sedimentary micro-facies and the characteristic value of the seismic attribute data;
and obtaining sedimentary microfacies plane distribution data of the area with few wells according to the sand content equivalent data.
In one embodiment, the sand content contour data is a sand content contour plan;
according to the sand content equivalent data, the sedimentary microfacies plane spreading data of the area with few wells is obtained, which comprises the following steps:
and obtaining a sedimentary microphase plane layout map of the area with few wells according to the sand content isoline plane map.
In specific implementation, the sand content equivalent data can be obtained by using a quantitative relation R, for example, the sand content is equal to-0.88488 × average arc length +1.041814 × average bandwidth +0.468967 × root mean square amplitude (where R is20.85), converting the seismic attribute characteristic values of the virtual control points of the multiple sedimentary microfacies into sand content values, and drawing a sand content contour line plan by combining the sand contents corresponding to the different types of sedimentary microfacies of the multiple exploratory wells, wherein the precision and the geological recognition matching of the obtained sand content contour line map are obviously higher than those of the sand content contour line map drawn only according to exploratory well data. And finally, obtaining a sedimentary microphase plane layout map in the area with few wells according to the sand content isoline plane map.
An embodiment is given below to illustrate the specific application of the prediction method for the facies planeness of sedimentary microfacies in the area with few wells.
In this embodiment, taking three segments of the kazakhstan group as an example, first, the sedimentary background, the rock core and the logging facies of the target layer in the region are analyzed, the sedimentary microfacies type of the target stratum is determined, and finally, the microfacies type of the three segments of the kazakhstan group is determined to be 5 types including an underwater diversion river channel, an underwater diversion bay, an estuary dam, mat-shaped sand and a shoal lake, wherein the dominant microfacies are the underwater diversion river channel, the estuary dam and the mat-shaped sand, and the background microfacies are the underwater diversion bay and the shoal lake.
Determining the sand content corresponding to different types of sediment micro-phases according to exploratory well data of a well-lacking area, and specifically comprising the following steps: based on 11 exploratory well data and 5 types of microphase types in the research area, sand content corresponding to different sedimentary microphase is obtained, wherein the sand content corresponding to background microphase (underwater diversion bay and shoal lake) is 0-15%, the sand content corresponding to mat sand is 15-30%, the sand content corresponding to underwater diversion river channel is 30-40%, and the sand content corresponding to estuary dam is more than 40%. FIG. 2 is a chart of sand content corresponding to different deposition micro-phases determined in an embodiment of the present invention.
Then, the top and bottom surfaces of three segments of the sand river street group are taken as constraints, and the target research area is 100km 25 types of seismic attribute data of average arc length, average amplitude, root-mean-square amplitude, maximum amplitude and average frequency are extracted from the seismic data.
According to 11 exploratory well data of the area with few wells, the equivalent of the plane extension range of the sedimentary microfacies of the following types is determined, and the method comprises the following steps:
the thickness range of the underwater diversion river channel is 4.1-6.7 m, the average thickness is 5.0m, the plane extension range (Lw-c) is 800-1340 m, and the cumulative distribution frequency (Pw-c) is 29%; the thickness range of the estuary dam is 3.5-5.6 m, the average thickness is 4.5m, the plane extension range (Lw-b) is 600-1050 m, and the cumulative distribution frequency (Pw-b) is 7%; the thickness range of the mat-shaped sand is 1.1 m-2.6 m, the average thickness is 1.7m, the plane extension range (Lw-s) is 1100 m-2600 m, and the cumulative distribution frequency (Pw-s) is 40%.
Establishing virtual control point attribute values of different types of sedimentary microfacies according to the plane extension range of the different types of sedimentary microfacies and seismic attribute data of a target stratum, and specifically comprising the following steps of:
and establishing a virtual control point attribute value based on the original seismic attribute according to the principle that at least 3 points control one microphase by taking the plane extension range (Lw) of the sedimentary microphase as a constraint condition. In this embodiment, the plane extension ranges (Lw) of three dominant microfacies of the sandstone river street group of the target stratum in the research area are as follows: the plane extension range (Lw-c) of the underwater diversion river channel is 800-1340 m, the plane extension range (Lw-b) of the estuary dam is 600-1050 m, and the plane extension range (Lw-s) of the mat-shaped sand is 1100-2600 m. With the minimum planar extension 600m as the lower limit. According to the principle that at least 3 points control one microphase, thinning the seismic attribute data at the interval of 300m to obtain 748 virtual control point attribute values of sedimentary microphase, and fig. 3 is a virtual control point based on the seismic attribute data established in the embodiment of the invention.
Determining the characteristic value of seismic attribute data of a target stratum according to the plane extension range and the virtual control point attribute values of different types of sedimentary microfacies, and specifically comprises the following steps: and taking the plane extension range (Lw) of the sedimentary microfacies as a search radius, taking the average value of a certain type of seismic attribute data in the plane extension radius range as the characteristic value of a certain type of seismic attribute data of the target stratum based on the attribute value of the virtual control point of the sedimentary microfacies. In this embodiment, based on the attribute values of 748 virtual control points, the attribute values respectively use 11 exploratory well positions as the center, the minimum plane extension range 600m of the dominant microfacies as the search radius, and the average value of 5 types of seismic attributes including average arc length, average amplitude, root mean square amplitude, maximum amplitude and average frequency is obtained and used as the characteristic value of 5 types of seismic attribute data including average arc length, average amplitude, root mean square amplitude, maximum amplitude and average frequency of the target formation sandstone river street group at the exploratory well position.
Then, normalization processing is performed on the characteristic values of 5 types of seismic attribute data, namely the average arc length, the average amplitude, the root-mean-square amplitude, the maximum amplitude and the average frequency.
Obtaining the relationship between the sand content corresponding to the sedimentary micro-facies of different types and the characteristic value of the seismic attribute data according to the sand content corresponding to the sedimentary micro-facies of different types and the characteristic value after the normalization processing of the seismic attribute data of the target stratum, expressing the relationship by a quantitative relational expression R, and expressing the relationship by a correlation coefficient R of a fitting relationship2And (3) taking the value greater than 0.80 as a lower reliability limit, and finally determining and selecting a combination of three seismic attribute data of root-mean-square amplitude, average arc length and average bandwidth to fit the relationship between the three seismic attribute data through screening, wherein a specific relational expression R is as follows:sand content-0.88488 × average arc length +1.041814 × average bandwidth +0.468967 × root mean square amplitude (where R is2＝0.85)。
According to the relationship between the sand content corresponding to different types of sedimentary micro-facies and the characteristic value of the seismic attribute data of the target stratum, namely, a quantitative relational expression R is utilized to convert the characteristic value of the seismic attribute data of the virtual control point into a sand content value, and a sand content isoline plan is drawn by combining the actual sand content value of a small number of exploratory wells, wherein in the embodiment, the sand content of the relational expression R is-0.88488 × average arc length +1.041814 × average bandwidth +0.468967 × root mean square amplitude (R is the average arc length +1.041814 × average bandwidth +0.468967 × root mean square amplitude)20.85), converting the characteristic values of the seismic attribute data of 749 virtual control points into sand content values, combining the actual sand content values of 11 wells to compile a sand content contour plan, fig. 4 is a sand content contour plan drawn by the method of the embodiment of the invention, fig. 5 is a sand content contour map drawn only according to exploratory well data in the prior art, and as can be seen from fig. 4 and 5, the precision and geological recognition matching of the sand content contour map drawn by the embodiment of the invention are obviously higher than those of the sand content contour map compiled only according to exploratory well data.
And quantitatively converting the sand content isoline plane graph into a sedimentary microfacies plane layout graph according to the sand content corresponding to different types of sedimentary microfacies, so as to realize quantitative prediction of sedimentary microfacies plane layout in the well-lacking area.
In this embodiment, the relationship between the deposited micro-phases of the three sections of the target stratum sand street group and the sand content is utilized, that is, the sand content corresponding to the background micro-phases (the underwater diversion bay and the shoal lake) is 0 to 15%, the sand content corresponding to the mat-shaped sand is 15 to 30%, the sand content corresponding to the underwater diversion river is 30 to 40%, and the sand content corresponding to the estuary dam is more than 40%. Quantitatively converting the sand content isoline plan into a sedimentary microfacies plan, finely depicting two leaf bodies and the plane distribution of dominant microfacies such as an underwater diversion river channel, a estuary dam, mat sand and the like. Fig. 6 is a plan view of a deposited microphase plotted in an embodiment of the present invention, as shown in fig. 6, which accurately plots the plan view of different types of deposited microphases.
In the method for predicting the plane spread of the sedimentary microfacies in the well-lacking area, which is provided by the embodiment of the invention, the sand content corresponding to different types of sedimentary microfacies is determined according to the exploratory well data of the well-lacking area; determining a characteristic value of seismic attribute data of a target stratum according to seismic data of a well-lacking area; obtaining the relationship between the sand content corresponding to the sedimentary micro-facies of different types and the characteristic value of the seismic attribute data according to the sand content corresponding to the sedimentary micro-facies of different types and the characteristic value of the seismic attribute data of the target stratum; and obtaining sedimentary microfacies plane spread data of the well-lacking area according to the relationship between the sand content corresponding to different types of sedimentary microfacies and the characteristic value of the seismic attribute data. In the embodiment of the invention, the sand content corresponding to different types of sedimentary microfacies is firstly obtained, then the characteristic value of the seismic attribute data is obtained, then the relation between the sand content corresponding to different types of sedimentary microfacies and the characteristic value of the seismic attribute data is constructed, and the sedimentary microfacies planar spread data of the low-well area is obtained based on the relation, so that the sedimentary microfacies planar spread data of the low-well area is obtained by taking the relation between the sand content corresponding to different types of sedimentary microfacies and the characteristic value of the seismic attribute data into consideration, and the sedimentary microfacies planar spread prediction result is more accurate.
Based on the same inventive concept, the embodiment of the invention also provides a device for predicting the planar distribution of sedimentary microphase in the area with few wells, as described in the following embodiment. Because the principles of these solutions are similar to the prediction method of microphase planar distribution in the area with few wells, the implementation of the device can be referred to the implementation of the method, and the repeated parts are not repeated.
Fig. 7 is a schematic diagram of a prediction apparatus for microphase planar spread in a low-well area according to an embodiment of the present invention, as shown in fig. 7, the apparatus includes:
the sand content determining module 701 is used for determining sand content corresponding to different types of sediment micro-phases according to exploratory well data of a low-well area;
a seismic attribute data eigenvalue determination module 702, configured to determine an eigenvalue of seismic attribute data of a target formation according to seismic data of a well-lacking region;
a relation data obtaining module 703, configured to obtain, according to sand contents corresponding to different types of depositional micro-facies and a feature value of seismic attribute data of a target formation, a relation between the sand contents corresponding to the different types of depositional micro-facies and the feature value of the seismic attribute data;
the sedimentary microfacies plane spread data acquisition module 704 is configured to acquire sedimentary microfacies plane spread data of a low-well area according to a relationship between sand content corresponding to different types of sedimentary microfacies and a feature value of seismic attribute data.
In one embodiment, the apparatus further comprises: and a depositional microfacies type determination module 705 for analyzing the depositional background, the core and the log facies of the low-well area and determining the types of the depositional microfacies of the target stratum of the low-well area.
In an embodiment, the apparatus further comprises a normalization processing module 706 configured to: carrying out normalization processing on the characteristic value of the seismic attribute data of the target stratum;
the relationship data obtaining module 703 is specifically configured to: and obtaining the relation between the sand content and the characteristic value of the seismic attribute data corresponding to the different types of sedimentary microfacies according to the relation between the different types of sedimentary microfacies and the sand content and the characteristic value of the seismic attribute data of the target stratum after normalization processing.
In summary, in the prediction apparatus for planar distribution of sedimentary microfacies in a low-well area provided in the embodiment of the present invention, the sand content determining module is configured to determine sand contents corresponding to different types of sedimentary microfacies according to the exploration well data of the low-well area; the seismic attribute data characteristic value determining module is used for determining the characteristic value of the seismic attribute data of the target stratum according to the seismic data of the less-well area; the relation data acquisition module is used for acquiring the relation between the sand content corresponding to the different types of sedimentary micro-facies and the characteristic value of the seismic attribute data of the target stratum according to the sand content corresponding to the different types of sedimentary micro-facies and the characteristic value of the seismic attribute data of the target stratum; and the sedimentary microfacies plane spread data acquisition module is used for acquiring sedimentary microfacies plane spread data of the area with less wells according to the relationship between the sand content corresponding to different types of sedimentary microfacies and the characteristic value of the seismic attribute data. In the embodiment of the invention, the sand content corresponding to different types of sedimentary microfacies is firstly obtained, then the characteristic value of the seismic attribute data is obtained, then the relation between the sand content corresponding to different types of sedimentary microfacies and the characteristic value of the seismic attribute data is constructed, and the sedimentary microfacies planar spread data of the low-well area is obtained based on the relation, so that the sedimentary microfacies planar spread data of the low-well area is obtained by taking the relation between the sand content corresponding to different types of sedimentary microfacies and the characteristic value of the seismic attribute data into consideration, and the sedimentary microfacies planar spread prediction result is more accurate.
As will be appreciated by one skilled in the art, 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, disk storage, CD-ROM, 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 flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams 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.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (13)
1. A sedimentary microphase plane spread prediction method for a well-poor area is characterized by comprising the following steps:
determining sand contents corresponding to different types of sediment micro-phases according to exploratory well data of the area with less wells;
determining a characteristic value of seismic attribute data of a target stratum according to seismic data of a well-lacking area;
obtaining the relationship between the sand content corresponding to the sedimentary micro-facies of different types and the characteristic value of the seismic attribute data according to the sand content corresponding to the sedimentary micro-facies of different types and the characteristic value of the seismic attribute data of the target stratum;
and obtaining sedimentary microfacies plane spread data of the target stratum in the low-well area according to the relationship between the sand content corresponding to different types of sedimentary microfacies and the characteristic value of the seismic attribute data of the target stratum.
2. The method of claim 1, wherein before determining the sand fraction corresponding to different types of depositional microfacies based on exploratory well data of the low well area, the method further comprises:
and analyzing the sedimentary background, the rock core and the logging facies of the low-well area, and determining the type of the sedimentary microfacies of the target stratum of the low-well area.
3. The method of claim 1, wherein determining the eigenvalues of the seismic attribute data of the target earth formation based on the seismic data of the well-poor region comprises:
acquiring seismic attribute data of a target stratum according to seismic data of a well-lacking area;
and determining the characteristic value of the seismic attribute data of the target stratum according to the seismic attribute data of the target stratum.
4. The method of predicting depositional microphase planar spread in a well-poor area of claim 3, wherein determining the eigenvalues of the seismic attribute data of the target earth formation from the seismic attribute data of the target earth formation comprises:
determining plane extension ranges of different types of sedimentary microfacies according to exploratory well data of the area with few wells;
establishing virtual control point attribute values of different types of sedimentary microfacies according to the plane extension range of the different types of sedimentary microfacies and seismic attribute data of a target stratum;
and determining the characteristic value of the seismic attribute data of the target stratum according to the plane extension range and the virtual control point attribute values of the sedimentary microfacies of different types.
5. The method for predicting the facies planform spread of sedimentary microfacies in a low-well area of claim 1, wherein prior to obtaining the relationship between the sand content corresponding to the sedimentary microfacies of different types and the eigenvalues of the seismic attribute data based on the sand content corresponding to the sedimentary microfacies of different types and the eigenvalues of the seismic attribute data of the target earth formation, further comprising:
carrying out normalization processing on the characteristic value of the seismic attribute data of the target stratum;
obtaining the relationship between the sand content corresponding to the sedimentary micro-facies of different types and the characteristic value of the seismic attribute data according to the sand content corresponding to the sedimentary micro-facies of different types and the characteristic value of the seismic attribute data of the target stratum, wherein the relationship comprises the following steps:
and obtaining the relation between the sand content and the characteristic value of the seismic attribute data corresponding to the different types of sedimentary microfacies according to the relation between the different types of sedimentary microfacies and the sand content and the characteristic value of the seismic attribute data of the target stratum after normalization processing.
6. The method of predicting the facies planespread of sedimentary microfacies in a well-poor area of claim 1, wherein obtaining the facies planespread data of sedimentary microfacies in a well-poor area based on a relationship between sand content corresponding to different types of sedimentary microfacies and eigenvalues of seismic attribute data comprises:
obtaining sand content equivalent data according to the relationship between the sand content corresponding to different types of sedimentary micro-facies and the characteristic value of the seismic attribute data;
and obtaining sedimentary microfacies plane distribution data of the area with few wells according to the sand content equivalent data.
7. The method for predicting the sedimentary microphase planar spread of the well-lacuna region as claimed in claim 6, wherein the sand content contour data is a sand content contour planar graph;
according to the sand content equivalent data, the sedimentary microfacies plane spreading data of the area with few wells is obtained, which comprises the following steps:
and obtaining a sedimentary microphase plane layout map of the area with few wells according to the sand content isoline plane map.
8. The method of claim 1, wherein the seismic attribute data includes one or any combination of average arc length, average amplitude, root mean square amplitude, maximum amplitude, and average frequency.
9. A prediction device for sedimentary microphase planar distribution in a well-poor area is characterized by comprising:
the sand content determining module is used for determining sand content corresponding to different types of sediment micro-phases according to exploratory well data of the area with less wells;
the seismic attribute data characteristic value determining module is used for determining the characteristic value of the seismic attribute data of the target stratum according to the seismic data of the less-well area;
the relation data acquisition module is used for acquiring the relation between the sand content corresponding to the different types of sedimentary micro-facies and the characteristic value of the seismic attribute data of the target stratum according to the sand content corresponding to the different types of sedimentary micro-facies and the characteristic value of the seismic attribute data of the target stratum;
and the sedimentary microfacies plane spread data acquisition module is used for acquiring sedimentary microfacies plane spread data of the area with less wells according to the relationship between the sand content corresponding to different types of sedimentary microfacies and the characteristic value of the seismic attribute data.
10. The well-deficient region sedimentary microfacies planar spread prediction apparatus of claim 9, further comprising a sedimentary microfacies type determination module to: and analyzing the sedimentary background, the rock core and the logging facies of the low-well area, and determining the type of the sedimentary microfacies of the target stratum of the low-well area.
11. The well-deficient region sedimentary microphase planar spread prediction apparatus of claim 9, further comprising a normalization processing module for: carrying out normalization processing on the characteristic value of the seismic attribute data of the target stratum;
the relationship data obtaining module is specifically configured to: and obtaining the relation between the sand content and the characteristic value of the seismic attribute data corresponding to the different types of sedimentary microfacies according to the relation between the different types of sedimentary microfacies and the sand content and the characteristic value of the seismic attribute data of the target stratum after normalization processing.
12. 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 method of any one of claims 1 to 8 when executing the computer program.
13. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1 to 8.
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