CN117130066A - Region crack identification method and device, storage medium and electronic equipment - Google Patents
Region crack identification method and device, storage medium and electronic equipment Download PDFInfo
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Abstract
The application relates to the technical field of oil reservoir exploration, in particular to a regional fracture identification method, a regional fracture identification device, a storage medium and electronic equipment, which comprise the following steps: acquiring logging data of a target area; determining a logging curve according to the logging data; calculating a logging curve extremum according to lithology and anomaly type of the logging curve; taking an absolute value of the logging curve extremum and carrying out normalization treatment; and obtaining a crack indication curve Frac according to the logging curve extremum after normalization treatment. The application carries out the process of amplifying the abnormal response extremum by the lithology-dividing optimized fracture sensitive curve, achieves the aim of identifying the development position and the number of the fractures, wherein the number of the Frac peaks of the fracture indication curve is matched with the number of the fractures, and the peak position is the development well section of the fracture.
Description
Technical Field
The application relates to the technical field of oil reservoir exploration, in particular to a regional fracture identification method and device, a storage medium and electronic equipment.
Background
The erdos basin is a stable basin in which folds and faults do not develop relatively, but have an unstable factor on a stable background, and cracks remain widely present in the basin under regional structural stresses. This structural fracture that develops in the weak deformation structural zone is also referred to as a regional fracture. The method is controlled by the stress field of the regional structure, and the regional cracks are distributed regularly, large in scale, wide in interval, wide in development range, relatively stable in occurrence, relatively far in horizontal extension, free of obvious horizontal dislocation at two sides of the cracks and perpendicular to the rock stratum surface, and can form a good crack network system.
The tight sandstone reservoir crack identification method mainly comprises three types:
1. crack identification method based on special logging data
The method mainly comprises imaging logging, stratum dip angle logging, array acoustic logging, nuclear magnetic resonance logging and the like, and can intuitively judge the occurrence and the type of cracks and calculate the related parameters such as the length, the density, the opening degree, the porosity and the like of the cracks; however, since special logging is more expensive than ordinary logging, there are typically few or no wells with special logging data [ B1].
2. Crack identification method based on conventional logging data
(1) The principle of the method for constructing the fracture identification characteristic indication parameter is based on the logging response characteristic analysis of the natural fracture, and the conventional logging curve containing the fracture anomaly information is subjected to anomaly amplification, curve reconstruction and targeted screening so as to highlight the natural fracture anomaly characteristic on the conventional logging curve and identify the fracture. The characteristic indicating parameters which are widely applied are (1) a deep lateral-microsphere focusing resistivity method DR based on different detection depths and a resistivity invasion correction difference ratio method RTC, and the method is inapplicable because the radial resistivity relation of oil layers in some research areas is expressed as a diversity characteristic; (2) the acoustic wave porosity and neutron porosity difference ratio method DP has better display for low-angle cracks, but has poorer indication effect for high-angle cracks; (3) the curve change rate method is characterized in that a logging curve such as microelectrode, microlateral, sound wave, density, neutron, natural gamma logging and the like with higher longitudinal resolution and shallower detection depth is usually adopted, the method is simple, convenient and easy to implement, and the main interference factor is that the interlayer in the reservoir layer often causes abnormal characteristics similar to cracks; (4) the saturation ratio method, when the crack is very developed, the cutting invasion causes SXO to be equal to SW, and the method fails; (5) the disadvantage of the three-porosity ratio method is that sonic velocity logging reflects primarily native inter-particulate porosity and horizontal fractures. Other characteristic indicating parameters such as a cross skeleton index method, a pore structure index m, a stratum factor ratio method, a rock modulus method E and the like are not commonly used because related parameters are not easy to obtain.
(2) The comprehensive identification method based on the characteristic indication parameters adopts complex theory and algorithm to identify the crack on the basis of constructing the crack characteristic indication parameters. (1) The comprehensive probability method is characterized in that the capability of identifying the fracture of each fracture indication characteristic parameter is required to be compared with the fracture identification result of the rock core or imaging logging data, so that the proper weight coefficient of each indication parameter is given, abundant data is required, and the assigned artificial factors of the weight coefficient are large; (2) the neural network method can avoid a logging interpretation model which is built in advance, automatically determine complex problems between a fracture zone and each logging response or characteristic parameter through the result of an algorithm of the neural network method, but needs a large amount of coring data as a learning sample; (3) the fractal theory is adopted, a logging curve with better correlation between waveform change characteristics and crack characteristics of rock is selected, and the fractal dimension D value of the logging curve is calculated, so that the development degree of cracks can be reflected; (4) the wavelet multi-scale analysis method extracts wavelet high-frequency attribute to identify cracks, and the development of vertical non-average property of a reservoir layer such as calcareous interlayer has larger interference on the two methods (3) and (4).
3. Dynamic identification method for cracks
According to the dynamic response characteristics of the cracks in the oil reservoir development process, the development condition of the cracks of the reservoir is identified and evaluated by utilizing oil reservoir engineering methods such as a drilling engineering method, a well testing analysis method, a dynamic monitoring data analysis method, a pressure analysis method and the like, and the cracks identified by well logging can be verified and supplemented. Dynamic data is not readily available as compared to conventional logging data.
Disclosure of Invention
Aiming at the problems, the application provides a regional crack identification method, a regional crack identification device, a storage medium and electronic equipment, which on one hand make up for the defect of core data, and on the other hand disclose a process of carrying out abnormal response extremum amplification on a lithology-dividing optimized crack sensitivity curve so as to achieve the purpose of identifying the development positions and the number of cracks.
In a first aspect, the present application provides a method for identifying a region fracture, the method comprising:
acquiring logging data of a target area;
determining a logging curve according to the logging data;
calculating a logging curve extremum according to lithology and anomaly type of the logging curve;
taking an absolute value of the logging curve extremum and carrying out normalization treatment;
and obtaining a crack indication curve Frac according to the logging curve extremum after normalization treatment.
In some embodiments, the determining a log from the log data comprises:
and selecting lithology from the logging data as a borehole diameter and a natural gamma curve of tight sandstone, and selecting lithology as a borehole diameter, a natural gamma and a sonic time difference curve of shale.
In some embodiments, the calculating a log extremum from lithology and anomaly type of the log comprises:
if the lithology is compact sandstone and the abnormal type is fracture development section well diameter expansion, calculating the maximum value of the well diameter curve;
if the lithology is compact sandstone and the abnormal type is natural gamma increase, calculating the maximum value of a natural gamma curve;
if the lithology is shale and the abnormal type is crack development section well diameter expansion, calculating the maximum value of well diameter curve;
if the lithology is shale and the abnormal type is that the acoustic time difference is increased, calculating the maximum value of an acoustic time difference curve;
if the lithology is shale and the abnormal type is natural gamma reduction, calculating the minimum value of the natural gamma curve.
In some embodiments, taking absolute values of the log extrema and normalizing the log extrema comprises:
and taking an absolute value of the logging curve extremum through matlab and carrying out normalization processing.
In some embodiments, the obtaining the fracture indication curve Frac according to the logging curve extremum after normalization processing includes:
multiplying extremum values of different types of logging curves with lithology of tight sandstone to obtain a first product;
multiplying extremum values of logging curves of different types with lithology of shale to obtain a second product;
and adding the first product and the second product to obtain the crack indication curve Frac.
In a second aspect, an area fracture identification apparatus, the apparatus comprising:
the acquisition unit is used for acquiring logging data of the target area;
the determining unit is used for determining a logging curve according to the logging data;
the first calculation unit is used for calculating a logging curve extremum according to lithology and anomaly types of the logging curve;
the processing unit is used for taking an absolute value of the logging curve extremum and carrying out normalization processing;
and the second calculation unit is used for calculating a crack indication curve Frac according to the logging curve extremum after normalization processing.
In some embodiments, the determining unit is configured to select a borehole diameter and a natural gamma curve for lithology of tight sandstone in the logging data, and the lithology selects a borehole diameter, a natural gamma and a sonic time difference curve for shale.
In some embodiments, the first calculating unit is configured to calculate a maximum value of the borehole radius curvature if the lithology is tight sandstone and the anomaly type is a fracture development section borehole diameter expansion; if the lithology is compact sandstone and the abnormal type is natural gamma increase, calculating the maximum value of a natural gamma curve; if the lithology is shale and the abnormal type is crack development section well diameter expansion, calculating the maximum value of well diameter curve; if the lithology is shale and the abnormal type is that the acoustic time difference is increased, calculating the maximum value of an acoustic time difference curve; if the lithology is shale and the abnormal type is natural gamma reduction, calculating the minimum value of the natural gamma curve.
In some embodiments, the processing unit is configured to take an absolute value of the log extremum by matlab and perform normalization processing.
In some embodiments, the second calculation unit is configured to multiply extrema of different types of logging curves with lithology of tight sandstone to obtain a first product; multiplying extremum values of logging curves of different types with lithology of shale to obtain a second product; and adding the first product and the second product to obtain the crack indication curve Frac.
In a third aspect, a storage medium stores a computer program executable by one or more processors for implementing the method for identifying a region fracture according to the first aspect.
In a fourth aspect, an electronic device includes a memory and a processor, where the memory stores a computer program, where the memory and the processor are communicatively connected to each other, and where the computer program, when executed by the processor, performs the method for identifying a region crack according to the first aspect.
The application provides a method and a device for identifying regional cracks, a storage medium and electronic equipment, wherein the method comprises the following steps: acquiring logging data of a target area; determining a logging curve according to the logging data; calculating a logging curve extremum according to lithology and anomaly type of the logging curve; taking an absolute value of the logging curve extremum and carrying out normalization treatment; and obtaining a crack indication curve Frac according to the logging curve extremum after normalization treatment. The application carries out the process of amplifying the abnormal response extremum by the lithology-dividing optimized fracture sensitive curve, achieves the aim of identifying the development position and the number of the fractures, wherein the number of the Frac peaks of the fracture indication curve is matched with the number of the fractures, and the peak position is the development well section of the fracture.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present application, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a method for identifying a regional crack according to an embodiment of the present application;
FIG. 2 is a schematic diagram of extremum method crack recognition according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a crack development characteristic of a sand body region of a large bridge of a Jia county Linjia yellow river with a long 7 estuary in a field geological section according to an embodiment of the application;
fig. 4 is a schematic diagram of a core fracture development characteristic of a fixed-edge oilfield eastern kernel ditch block long 7 reservoir group according to an embodiment of the present application;
FIG. 5 is a schematic diagram of the identification result of the method for determining the extremum of the crack of the 1783 well long 7 oil layer set by the Dongren ditch block according to the embodiment of the application;
FIG. 6 is a graph showing the relationship between the linear density of the cracks of the vertical well production well sections of the east Asian canal block length 7 reservoir group coring well and the non-coring well and the daily liquid production amount in the initial circumference;
fig. 7 is a schematic structural diagram of a device for identifying an area crack according to an embodiment of the present application;
fig. 8 is a connection block diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The following will describe embodiments of the present application in detail with reference to the drawings and examples, thereby solving the technical problems by applying technical means to the present application, and realizing the corresponding technical effects can be fully understood and implemented accordingly. The embodiment of the application and the characteristics in the embodiment can be mutually combined on the premise of no conflict, and the formed technical scheme is within the protection scope of the application.
As known from the background art, in the existing fracture identification method, the data required by the special logging data fracture identification method and the dynamic fracture identification method are not easy to obtain, or the cost is further increased, but in the existing fracture identification method adopting the conventional logging data, the required data is not easy to obtain, or the method is only suitable for low-angle fractures, and for high angles, the identification result of the fractures with short extension is poor.
In view of the above, the application provides a method, a device, a storage medium and an electronic device for identifying regional cracks, which make up for the defect of core data on one hand, and on the other hand, disclose a process of carrying out abnormal response extremum amplification on a lithology-dividing optimized crack sensitive curve, so as to achieve the purpose of identifying the development positions and the number of cracks, and the method is particularly suitable for identifying cracks with high angles and short extension.
Example 1
Fig. 1 is a flow chart of a method for identifying an area crack according to an embodiment of the present application, as shown in fig. 1, the method includes:
s101, acquiring logging data of a target area;
s102, determining a logging curve according to the logging data;
s103, calculating a logging curve extremum according to lithology and anomaly type of the logging curve;
s104, taking an absolute value of the logging curve extremum and carrying out normalization processing;
s105, obtaining a crack indication curve Frac according to the logging curve extremum after normalization processing.
The application provides an identification method-extremum method for a tight sandstone reservoir area fracture based on a conventional logging curve. According to the characteristic that the crack occurrence in the area of a research area is relatively stable and has a high angle and short extension, the abnormal increase or decrease of the curve value of the development section of the crack is highlighted by adopting a method for extremum solving the well logging curve, and the purpose of identifying the development position and the number of the crack by utilizing the conventional well logging curve under the condition of very limited well drilling data is achieved.
In some embodiments, the determining a log from the log data comprises:
and selecting lithology from the logging data as a borehole diameter and a natural gamma curve of tight sandstone, and selecting lithology as a borehole diameter, a natural gamma and a sonic time difference curve of shale.
The sensitivity of the well logging curve to different fracture occurrence is fully considered, and the interference of factors such as the depth of mud invasion, calcareous or argillaceous interlayer in a well hole and a reservoir to fracture identification is fully considered, so that the well logging curve which has definite abnormal response to the fracture and can exclude interference factors is selected.
Under lithology influence, the fractures developed in different lithology rock formations also have different logging response characteristics, thus distinguishing sandstone from shale to identify the fracture. Tight sandstone selects borehole diameter (CAL, in) and natural gamma (GR, API) curves, and shale selects CAL, GR and sonic time difference (AC, us/ft) curves.
In some embodiments, the calculating a log extremum from lithology and anomaly type of the log comprises:
if the lithology is compact sandstone and the abnormal type is fracture development section well diameter expansion, calculating the maximum value of the well diameter curve;
if the lithology is compact sandstone and the abnormal type is natural gamma increase, calculating the maximum value of a natural gamma curve;
if the lithology is shale and the abnormal type is crack development section well diameter expansion, calculating the maximum value of well diameter curve;
if the lithology is shale and the abnormal type is that the acoustic time difference is increased, calculating the maximum value of an acoustic time difference curve;
if the lithology is shale and the abnormal type is natural gamma reduction, calculating the minimum value of the natural gamma curve.
The sandstone and shale are distinguished, and the maximum value or the minimum value is calculated according to abnormal increase or decrease of the logging curve value. And (3) expanding the well diameter of the tight sandstone crack development section, and obtaining the maximum value of the well diameter and a natural gamma curve during crack identification due to high natural gamma abnormality. The diameter of the well bore of the shale fracture development section is expanded, the acoustic wave time difference is slightly increased, and the maximum value of the well bore and acoustic wave time difference curve is obtained during fracture identification; natural gamma is slightly reduced but far exceeds the natural gamma value (abnormal) of sandstone, and the minimum value of a natural gamma curve is calculated during crack identification.
Specifically, as shown in fig. 2, an extremum method crack identification schematic diagram is shown.
Logging curve extremum calculation with matlab software, the calculation flow is as follows (taking the determination of 1783 well CAL and GR curves as an example):
(1) Loading the CAL and GR curve values of the well section of the target layer and the corresponding well depth into an excel table, and reading data by using matlab software;
b1 =xlsread ('definite search 1783.Xlsx', 'sheet1', 'B2: B562'); % original CAL curve, data in column B, lines 2-562
c1 =xlsread ('definite search 1783.Xlsx', 'sheet1', 'C2: C562'); % original GR curve, data on columns C, rows 2-562
(2) Maximum value (CAL) is calculated for CAL logging curve max ) Formula (VI)
CAL max ＝diff(diff(b1))；
CAL max ＝[0,0,0,0,0,CAL max ']'；
CAL max (CAL max >0)＝0；
Minimum value (GR) of GR log min ) Formula (VI)
GR min ＝diff(diff(c1))；
GR min ＝[0,0,0,0,0,GR min ']'；
GR min (GR min <0)＝0；
In some embodiments, taking absolute values of the log extrema and normalizing the log extrema comprises:
and taking an absolute value of the logging curve extremum through matlab and carrying out normalization processing.
It should be noted that, the absolute value of the logging extremum is taken by matlab and normalized as follows:
curve extremum processing
(1) Taking absolute value of extremum of curve (R2, R3)
for i＝1:length(CAL max )
R2＝abs(CAL max )；
end
for i＝1:length(GR min )
R3＝abs(GR min )；
end
(2) The absolute value is normalized (normalized to between 0 and 100).
for i＝1:length(R2)
R_CAL max (i)＝100*(R2(i)-min(R2))/(max(R2)-min(R2))；
end
for i＝1:length(R3)
R_GR min (i)＝100*(R3(i)-min(R3))/(max(R3)-min(R3))；
end
In some embodiments, the obtaining the fracture indication curve Frac according to the logging curve extremum after normalization processing includes:
multiplying extremum values of different types of logging curves with lithology of tight sandstone to obtain a first product;
multiplying extremum values of logging curves of different types with lithology of shale to obtain a second product;
and adding the first product and the second product to obtain the crack indication curve Frac.
It should be noted that, distinguishing different lithology multiplies the extreme values processed by different crack sensitive curves with the same depth, so as to achieve the purpose of "abnormal amplification" of the conventional logging curve containing the abnormal information of the crack, the peak value number of the crack indication curve Frac (which is dimensionless) is matched with the crack number, and the peak value position is the crack development well section.
Specifically, the process is performed by matlab processing as follows:
for i＝1:length(c1)
if(c1<90)
F sand (i)＝R_CAL max (i)*R_GR max (i)
else
F mud (i)＝R_CAL max (i)*R_GR max (i)
end
for i＝1:length(c1)
Frac(i)＝F sand (i)+F mud (i)
end
if the acoustic time difference curve of the shale exists, the method can be used for processing the' F mud (i)＝R_CAL max (i)*R_GR max (i) "modified to" F mud (i)＝R_CAL max (i)*R_GR max (i)*R_AC max (i) "calculate.
It should be further noted that the method has high coincidence degree between the crack development position identified by the method and the core observation position, and high matching degree between the peak value number of the crack indication curve and the number of the core cracks, is quite suitable for the conditions of relatively stable yield of a research area, mainly including 'high angle and short extension' cracks, and particularly has high vertical resolution.
Dividing the number of cracks identified by a vertical well production well section with centering data of an eastern kernel ditch block of a fixed-edge oilfield with 7 oil layers in the research area by the thickness of the production well section to obtain the linear density of the cracks based on the thickness of the production well section, wherein the linear density accords with the development rule of the cracks in a field geological section, and is in a proportional relation with the initial daily liquid yield of the vertical well oil test production. The fracture identified by the non-cored well also meets the conditions above, indicating the reliability of the natural fracture identification method.
In summary, an embodiment of the present application provides a method for identifying a region crack, where the method includes: acquiring logging data of a target area; determining a logging curve according to the logging data; calculating a logging curve extremum according to lithology and anomaly type of the logging curve; taking an absolute value of the logging curve extremum and carrying out normalization treatment; and obtaining a crack indication curve Frac according to the logging curve extremum after normalization treatment. The application carries out the process of amplifying the abnormal response extremum by the lithology-dividing optimized fracture sensitive curve, achieves the aim of identifying the development position and the number of the fractures, wherein the number of the Frac peaks of the fracture indication curve is matched with the number of the fractures, and the peak position is the development well section of the fracture.
Example two
Based on the above-described region crack recognition method disclosed in the embodiment of the present application, calculation result analysis is performed in the following with specific examples.
FIG. 3 is a schematic diagram showing the development characteristics of cracks in a sand body region of a large bridge of a Jia Huang river with a length of 7 estuaries in field geological section, the overall yield is single, the cracks are divided in sandstone and mudstone, and the linear density of the cracks is influenced by lithology and thickness. The concrete condition is that the sand body with a thick layer of 2-5 m is downwards, upwards and upwards convex, and the reverse rhythm is the sand body of the front edge estuary dam of the delta. The total section length is 22m, the crack linear density of the sand body of the estuary dam is about 1.2 pieces/m, the mat sand is 1.8 pieces/m, and the 2m thick mudstone is 5 pieces/m.
FIG. 4 is a schematic diagram of the development characteristics of core cracks of a fixed-edge oilfield eastern core group with a length of 7 reservoir blocks, mainly vertical cracks and high-angle cracks, and occasionally calcite filling; the condition that more than 2 cracks are developed in the same rock core in the rock core observation and description is rare. The length of a single crack is between 0.05 and 1.0m, and is more than 0.3m, the crack generally develops in a rock mechanical layer, and the length of the crack is controlled in a single sand body for the sand body. Wherein, a-decides 1729 well, 2219.0m, vertical slit; b-setting 1781 well, 2325.63m, high angle slit; c-setting 1783 well, 2214.07m, calcite half-filling vertical seam; d, e-setting 1783 well, horizontally slipping off the seam, 2214.6m; f-fix 1387 well, 2436.4m, vertical slots.
Fig. 5 is a schematic diagram of an identification result of an extremum method of a group of cracks of an eastern kernel ditch block fixed-detection 1783 well long 7-oil layer, wherein the crack development position and the number indicated by a crack indication curve Frac are high in matching degree with a rock core observation result. In the figure, CALmax is a maximum value of well diameter, GRmax is a maximum value of natural gamma, GRmin is a minimum value of natural gamma, and ACmax is a maximum value of acoustic wave time difference. And calibrating the well with the coring well, wherein a crack indication curve Frac value >2 of the research area indicates a crack development well section.
FIG. 6 is a graph showing the relationship between the linear density of cracks at the production well section of a vertical well and the initial daily liquid production amount of a core well and a non-core well of an east Asian ditch block long 7-reservoir group according to an embodiment of the present application.
Taking the example of determining 1783 wells in an eastern canal block of a fixed-edge oilfield (shown in figure 5), the identified crack development position is high in coincidence with the observed position of the core, and the number of peak values of the crack indication curve is high in matching degree with the number of cracks of the core. In the figure, cracks at the top and bottom oil shale parts and the interlayer part of the thin sandstone and mudstone of the long 7 oil layer group are especially developed, which is consistent with field geological observation results.
At present, part of straight wells in the east-west ditch block adopts a perforation fracturing mode to mine thick-layer sand bodies at the top of a long 7-oil layer group, and the thickness of a production well section is 4-8 m, and the average thickness is 5m. Dividing the number of cracks identified by the production well section of the vertical well by the thickness of the production well section to obtain the linear density of the cracks based on the thickness of the production well section, wherein the average linear density of the cracks is 0.38 pieces/m, natural cracks are relatively developed, and the formation of a sand-added fracture network system is facilitated. And calculating the average value of the linear density of the cracks of the 5 m-thickness sand body development to be 0.32 pieces/m by using a crack development rule fitting formula in the field geological section, and approaching to a crack identification result. The relationship between the linear density of the natural cracks in the coring well section and the initial daily production liquid of the oil test and production test can be seen (shown in fig. 6), the development degree of the cracks is in a direct proportion relationship with the production liquid amount, and the cracks recognized by the non-coring well also accord with the rule, so that the reliability of the natural crack recognition method is fully illustrated.
Example III
Based on the above-described method for identifying an area slit according to the embodiment of the present application, fig. 7 specifically discloses an area slit identification device applying the method for identifying an area slit.
As shown in fig. 7, an embodiment of the present application discloses a device for identifying an area crack, including:
an acquisition unit 701, configured to acquire logging data of a target area;
a determining unit 702 for determining a log from the log data;
a first calculation unit 703, configured to calculate a log extremum according to lithology and anomaly type of the log;
a processing unit 704, configured to take an absolute value of the logging extremum and perform normalization processing;
the second calculating unit 705 is configured to calculate a fracture indication curve Frac according to the logging curve extremum after the normalization processing.
The application provides an identification method-extremum method for a tight sandstone reservoir area fracture based on a conventional logging curve. According to the characteristic that the crack occurrence in the area of a research area is relatively stable and has a high angle and short extension, the abnormal increase or decrease of the curve value of the development section of the crack is highlighted by adopting a method for extremum solving the well logging curve, and the purpose of identifying the development position and the number of the crack by utilizing the conventional well logging curve under the condition of very limited well drilling data is achieved.
In some embodiments, the determining unit is configured to select a borehole diameter and a natural gamma curve for lithology of tight sandstone in the logging data, and the lithology selects a borehole diameter, a natural gamma and a sonic time difference curve for shale.
The sensitivity of the well logging curve to different fracture occurrence is fully considered, and the interference of factors such as the depth of mud invasion, calcareous or argillaceous interlayer in a well hole and a reservoir to fracture identification is fully considered, so that the well logging curve which has definite abnormal response to the fracture and can exclude interference factors is selected.
Under lithology influence, the fractures developed in different lithology rock formations also have different logging response characteristics, thus distinguishing sandstone from shale to identify the fracture. Tight sandstone selects borehole diameter (CAL, in) and natural gamma (GR, API) curves, and shale selects CAL, GR and sonic time difference (AC, us/ft) curves.
In some embodiments, the first calculating unit is configured to calculate a maximum value of the borehole radius curvature if the lithology is tight sandstone and the anomaly type is a fracture development section borehole diameter expansion; if the lithology is compact sandstone and the abnormal type is natural gamma increase, calculating the maximum value of a natural gamma curve; if the lithology is shale and the abnormal type is crack development section well diameter expansion, calculating the maximum value of well diameter curve; if the lithology is shale and the abnormal type is that the acoustic time difference is increased, calculating the maximum value of an acoustic time difference curve; if the lithology is shale and the abnormal type is natural gamma reduction, calculating the minimum value of the natural gamma curve.
The sandstone and shale are distinguished, and the maximum value or the minimum value is calculated according to abnormal increase or decrease of the logging curve value. And (3) expanding the well diameter of the tight sandstone crack development section, and obtaining the maximum value of the well diameter and a natural gamma curve during crack identification due to high natural gamma abnormality. The diameter of the well bore of the shale fracture development section is expanded, the acoustic wave time difference is slightly increased, and the maximum value of the well bore and acoustic wave time difference curve is obtained during fracture identification; natural gamma is slightly reduced but far exceeds the natural gamma value (abnormal) of sandstone, and the minimum value of a natural gamma curve is calculated during crack identification.
Specifically, as shown in fig. 2, an extremum method crack identification schematic diagram is shown.
Logging curve extremum calculation with matlab software, the calculation flow is as follows (taking the determination of 1783 well CAL and GR curves as an example):
(1) Loading the CAL and GR curve values of the well section of the target layer and the corresponding well depth into an excel table, and reading data by using matlab software;
b1 =xlsread ('definite search 1783.Xlsx', 'sheet1', 'B2: B562'); % original CAL curve, data in column B, lines 2-562
c1 =xlsread ('definite search 1783.Xlsx', 'sheet1', 'C2: C562'); % original GR curve, data on columns C, rows 2-562
(2) Maximum value (CAL) is calculated for CAL logging curve max ) Formula (VI)
CAL max ＝diff(diff(b1))；
CAL max ＝[0,0,0,0,0,CAL max ']'；
CAL max (CAL max >0)＝0；
Minimum value (GR) of GR log min ) Formula (VI)
GR min ＝diff(diff(c1))；
GR min ＝[0,0,0,0,0,GR min ']'；
GR min (GR min <0)＝0；
In some embodiments, the processing unit is configured to take an absolute value of the log extremum by matlab and perform normalization processing.
It should be noted that, the absolute value of the logging extremum is taken by matlab and normalized as follows:
curve extremum processing
(1) Taking absolute value of extremum of curve (R2, R3)
for i＝1:length(CAL max )
R2＝abs(CAL max )；
end
for i＝1:length(GR min )
R3＝abs(GR min )；
end
(2) The absolute value is normalized (normalized to between 0 and 100).
for i＝1:length(R2)
R_CAL max (i)＝100*(R2(i)-min(R2))/(max(R2)-min(R2))；
end
for i＝1:length(R3)
R_GR min (i)＝100*(R3(i)-min(R3))/(max(R3)-min(R3))；
end
In some embodiments, the second calculation unit is configured to multiply extrema of different types of logging curves with lithology of tight sandstone to obtain a first product; multiplying extremum values of logging curves of different types with lithology of shale to obtain a second product; and adding the first product and the second product to obtain the crack indication curve Frac.
It should be noted that, distinguishing different lithology multiplies the extreme values processed by different crack sensitive curves with the same depth, so as to achieve the purpose of "abnormal amplification" of the conventional logging curve containing the abnormal information of the crack, the peak value number of the crack indication curve Frac (which is dimensionless) is matched with the crack number, and the peak value position is the crack development well section.
Specifically, the process is performed by matlab processing as follows:
if the acoustic time difference curve of the shale exists, the method can be used for processing the' F mud (i)＝R_CAL max (i)*R_GR max (i) "modified to" F mud (i)＝R_CAL max (i)*R_GR max (i)*R_AC max (i) "calculate.
It should be further noted that the method has high coincidence degree between the crack development position identified by the method and the core observation position, and high matching degree between the peak value number of the crack indication curve and the number of the core cracks, is quite suitable for the conditions of relatively stable yield of a research area, mainly including 'high angle and short extension' cracks, and particularly has high vertical resolution.
Dividing the number of cracks identified by a vertical well production well section with centering data of an eastern kernel ditch block of a fixed-edge oilfield with 7 oil layers in the research area by the thickness of the production well section to obtain the linear density of the cracks based on the thickness of the production well section, wherein the linear density accords with the development rule of the cracks in a field geological section, and is in a proportional relation with the initial daily liquid yield of the vertical well oil test production. The fracture identified by the non-cored well also meets the conditions above, indicating the reliability of the natural fracture identification method.
In summary, an embodiment of the present application provides a device for identifying an area crack, including: acquiring logging data of a target area; determining a logging curve according to the logging data; calculating a logging curve extremum according to lithology and anomaly type of the logging curve; taking an absolute value of the logging curve extremum and carrying out normalization treatment; and obtaining a crack indication curve Frac according to the logging curve extremum after normalization treatment. The application carries out the process of amplifying the abnormal response extremum by the lithology-dividing optimized fracture sensitive curve, achieves the aim of identifying the development position and the number of the fractures, wherein the number of the Frac peaks of the fracture indication curve is matched with the number of the fractures, and the peak position is the development well section of the fracture.
Example IV
The present embodiment also provides a computer readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application store, etc., on which a computer program is stored, which when executed by a processor, can implement the method steps as in the first embodiment, and the present embodiment will not be repeated here.
Example five
Fig. 8 is a connection block diagram of an electronic device 500 according to an embodiment of the present application, as shown in fig. 8, the electronic device 500 may include: a processor 501, a memory 502, a multimedia component 503, an input/output (I/O) interface 504, and a communication component 505.
Wherein the processor 501 is configured to perform all or part of the steps in the region fracture identification method as in the first embodiment. The memory 502 is used to store various types of data, which may include, for example, instructions for any application or method in the electronic device, as well as application-related data.
The processor 501 may be an application specific integrated circuit (Application Specific Integrated Circuit, abbreviated as ASIC), a digital signal processor (Digital Signal Processor, abbreviated as DSP), a digital signal processing device (Digital Signal Processing Device, abbreviated as DSPD), a programmable logic device (Programmable Logic Device, abbreviated as PLD), a field programmable gate array (Field Programmable Gate Array, abbreviated as FPGA), a controller, a microcontroller, a microprocessor, or other electronic component implementation for executing the region fracture identification method in the above embodiment.
The Memory 502 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as static random access Memory (Static Random Access Memory, SRAM for short), electrically erasable programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM for short), erasable programmable Read-Only Memory (Erasable Programmable Read-Only Memory, EPROM for short), programmable Read-Only Memory (Programmable Read-Only Memory, PROM for short), read-Only Memory (ROM for short), magnetic Memory, flash Memory, magnetic disk, or optical disk.
The multimedia component 503 may include a screen, which may be a touch screen, and an audio component for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in a memory or transmitted through a communication component. The audio assembly further comprises at least one speaker for outputting audio signals.
The I/O interface 504 provides an interface between the processor 501 and other interface modules, which may be a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons.
The communication component 505 is used for wired or wireless communication between the electronic device 500 and other devices. Wireless communication, such as Wi-Fi, bluetooth, near field communication (Near Field Communication, NFC for short), 2G, 3G or 4G, or a combination of one or more thereof, the corresponding communication component 505 may thus comprise: wi-Fi module, bluetooth module, NFC module.
In summary, the present application provides a method, an apparatus, a storage medium, and an electronic device for identifying an area crack, where the method includes: acquiring logging data of a target area; determining a logging curve according to the logging data; calculating a logging curve extremum according to lithology and anomaly type of the logging curve; taking an absolute value of the logging curve extremum and carrying out normalization treatment; and obtaining a crack indication curve Frac according to the logging curve extremum after normalization treatment. The application carries out the process of amplifying the abnormal response extremum by the lithology-dividing optimized fracture sensitive curve, achieves the aim of identifying the development position and the number of the fractures, wherein the number of the Frac peaks of the fracture indication curve is matched with the number of the fractures, and the peak position is the development well section of the fracture.
In the embodiments provided in the present application, it should be understood that the disclosed method may be implemented in other manners. The method embodiments described above are merely illustrative.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
Although the embodiments of the present application are described above, the above description is only for the convenience of understanding the present application, and is not intended to limit the present application. Any person skilled in the art can make any modification and variation in form and detail without departing from the spirit and scope of the present disclosure, but the scope of the present disclosure is still subject to the scope of the appended claims.
Claims (12)
1. A method of identifying a region fracture, the method comprising:
acquiring logging data of a target area;
determining a logging curve according to the logging data;
calculating a logging curve extremum according to lithology and anomaly type of the logging curve;
taking an absolute value of the logging curve extremum and carrying out normalization treatment;
and obtaining a crack indication curve Frac according to the logging curve extremum after normalization treatment.
2. The method of claim 1, wherein the determining a log from the log data comprises:
and selecting lithology from the logging data as a borehole diameter and a natural gamma curve of tight sandstone, and selecting lithology as a borehole diameter, a natural gamma and a sonic time difference curve of shale.
3. The method of claim 2, wherein said calculating a log extremum from lithology and anomaly type of said log comprises:
if the lithology is compact sandstone and the abnormal type is fracture development section well diameter expansion, calculating the maximum value of the well diameter curve;
if the lithology is compact sandstone and the abnormal type is natural gamma increase, calculating the maximum value of a natural gamma curve;
if the lithology is shale and the abnormal type is crack development section well diameter expansion, calculating the maximum value of well diameter curve;
if the lithology is shale and the abnormal type is that the acoustic time difference is increased, calculating the maximum value of an acoustic time difference curve;
if the lithology is shale and the abnormal type is natural gamma reduction, calculating the minimum value of the natural gamma curve.
4. The method of claim 1, wherein taking absolute values of the log extrema and normalizing the log extrema comprises:
and taking an absolute value of the logging curve extremum through matlab and carrying out normalization processing.
5. The method of claim 1, wherein deriving the fracture indication curve Frac from the normalized log extremum comprises:
multiplying extremum values of different types of logging curves with lithology of tight sandstone to obtain a first product;
multiplying extremum values of logging curves of different types with lithology of shale to obtain a second product;
and adding the first product and the second product to obtain the crack indication curve Frac.
6. An area fracture identification device, the device comprising:
the acquisition unit is used for acquiring logging data of the target area;
the determining unit is used for determining a logging curve according to the logging data;
the first calculation unit is used for calculating a logging curve extremum according to lithology and anomaly types of the logging curve;
the processing unit is used for taking an absolute value of the logging curve extremum and carrying out normalization processing;
and the second calculation unit is used for calculating a crack indication curve Frac according to the logging curve extremum after normalization processing.
7. The apparatus of claim 6, wherein the determining unit is configured to select a borehole diameter and a natural gamma curve for lithology of tight sandstone and a borehole diameter, natural gamma and sonic time difference curve for lithology of shale in the well log.
8. The apparatus of claim 7, wherein the first calculation unit is configured to calculate a maximum value of the borehole curvature if the lithology is tight sandstone and the anomaly type is a fracture development section borehole expansion; if the lithology is compact sandstone and the abnormal type is natural gamma increase, calculating the maximum value of a natural gamma curve; if the lithology is shale and the abnormal type is crack development section well diameter expansion, calculating the maximum value of well diameter curve; if the lithology is shale and the abnormal type is that the acoustic time difference is increased, calculating the maximum value of an acoustic time difference curve; if the lithology is shale and the abnormal type is natural gamma reduction, calculating the minimum value of the natural gamma curve.
9. The apparatus of claim 6, wherein the processing unit is configured to take an absolute value of the log extremum by matlab and normalize the absolute value.
10. The apparatus of claim 6, wherein the second computing unit is configured to multiply extrema of different types of log curves having lithology of tight sandstone to obtain a first product; multiplying extremum values of logging curves of different types with lithology of shale to obtain a second product; and adding the first product and the second product to obtain the crack indication curve Frac.
11. A storage medium storing a computer program executable by one or more processors for implementing the method of region fracture identification of any one of claims 1 to 5.
12. An electronic device comprising a memory and a processor, wherein the memory has stored thereon a computer program, the memory and the processor being communicatively coupled to each other, the computer program, when executed by the processor, performing the method of identifying a region fracture as claimed in any one of claims 1 to 5.
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