CN110221358B - Delta sedimentary subphase digital discrimination method - Google Patents
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Abstract
The invention provides a method for digitally judging a delta sedimentary subphase, which comprises the following steps: step 1, establishing an electrical identification template of a sedimentary subgrain rock of delta, and performing single-well facies division; step 2, performing difference analysis to obtain difference characteristic parameters capable of representing different deposition subphases; step 3, establishing a deposition subphase multivariate parameter identification template by utilizing a spider-web diagram characteristic parameter difference analysis method; step 4, fitting the characteristic parameters by using a multiple regression mathematical fitting method, and establishing a deposition subphase quantitative discrimination function; step 5, performing correlation analysis on the function value and the single well phase, and defining threshold ranges of different deposition sub-phase function values; and 6, inputting the characteristic parameters of the actual drilling well to obtain a delta sedimentary subphase digital plan. The delta sedimentary subphase digital discrimination method utilizes a multivariate regression method to establish a sedimentary subphase digital discrimination function, and combines geological knowledge to determine a definite sedimentary subphase boundary threshold, thereby performing accurate sedimentary subphase division.
Description
Technical Field
The invention relates to the field of sedimentary subphase division application, in particular to a delta sedimentary subphase digital discrimination method.
Background
With the increasing development degree of exploration, the requirements on exploration work are increasingly refined. The sedimentary facies division technology is used as an important means for reconstructing sedimentary environments in geological history periods, and plays an important guiding role in oil and gas exploration and development. The current mainstream sedimentary facies division technology is a method for determining facies zone boundaries according to personal experience by using single well facies control points and seismic facies control surfaces, and has the defects that drilling and seismic data are mutually isolated, and the facies zone boundaries are identified without reliable basis, so that sedimentary facies zone division is inaccurate.
The method for digitally judging the deposition subphase of the delta is an effective method for dividing the deposition subphase in a delta deposition system. When the traditional sedimentary subphase division technology is used for determining sedimentary subphase boundaries, a method of manual experience extrapolation based on single well facies is used, and the problems that the identification of the facies boundary is not standard, the facies boundary division is not accurate and the like are caused. Therefore, a novel delta sedimentary subphase digital discrimination method is invented, and the technical problems are solved.
Disclosure of Invention
The invention aims to provide a method for judging and identifying the deposition subphase of the delta, which organically combines well drilling and seismic data by using a mathematical geology method, and overcomes the defects of the traditional division method by using a method for judging and identifying a template and determining a threshold by well-seismic union control.
The object of the invention can be achieved by the following technical measures: the method for digitally judging the deposition subphase of the delta comprises the following steps: step 1, establishing an electrical identification template of a sedimentary subgrain rock of delta, and performing single-well facies division; step 2, carrying out difference analysis on the rock physical, electrical and seismic properties of different deposition subphases by using a multi-parameter intersection analysis method to obtain difference characteristic parameters capable of representing different deposition subphases; step 3, establishing a deposition subphase multivariate parameter identification template by utilizing a spider-web diagram characteristic parameter difference analysis method; step 4, fitting the characteristic parameters by using a multiple regression mathematical fitting method, and establishing a deposition subphase quantitative discrimination function; step 5, performing correlation analysis on the function value and the single well phase, and defining threshold ranges of different deposition sub-phase function values; and 6, inputting the characteristic parameters of the actual drilling well to obtain a delta sedimentary subphase digital plan.
The object of the invention can also be achieved by the following technical measures:
in step 1, on the basis of the analysis of drilling and recording data and electrical measurement data and under the guidance of geological theory knowledge of sedimentary facies of an Delta sedimentary system, a Delta sedimentary sub-facies recognition template is established according to the drilling, recording, electrical and seismic data, and single well facies division is carried out.
In step 1, the single well phases are divided into:
plain subphase: the thick-layer sandstone sandstones sandwich the thin-layer mudstone, SP curves (natural potential curves) are bell-shaped and box-shaped, medium-strong amplitude and medium-strong continuity in the same-direction axis are realized, and frequency spectrums represent high-frequency energy clusters;
leading edge subphase: the SP curve is funnel-shaped, the equidirectional axis is medium and continuous in medium amplitude, and the frequency spectrum is expressed as a medium and high energy cluster;
front delta subphase: the thick-layer shale and the oil shale have flat SP curves, are in medium continuity in the same-direction axis weak amplitude, and have low-frequency energy clusters represented by frequency spectrums.
In step 2, the acquired difference characteristic parameters include:
standardizing an AC curve, and eliminating environmental errors and value domain errors; plain subphase: 95< mudstone AC <140, leading edge subphase: 75< mudstone AC <98, anterior delta subphase: 90< mudstone AC <105, the mudstone developed in delta plain subphase has obvious high AC value, namely low speed characteristic;
standardizing the SP curve, and resampling the SP curve according to seismic resolution; plain subphase: 120< SP resample <140, leading edge subphase: 120< SP resample <150, anterior delta subphase SP resample >150, anterior delta subphase has an apparent high SP resample value;
and (3) carrying out statistics on the dip angle of the stratums of the same direction under different deposition subphase conditions, wherein the plain subphase: 1< dip <6, leading edge subphase: 5< dip <12, anterior delta subphase: 0.8< dip <5.7, delta front subphase has a significant high formation angle value.
In step 3, normalizing mudstone AC (acoustic wave time difference of the mudstone), a stratum inclination angle, a mud content and an SP resampling curve, establishing a four-corner coordinate system by utilizing the four parameters, wherein spider webs surrounded by the four parameters with different numerical values under different deposition subphases are different;
delta plain subphase: the first quadrant spider web area and the fourth quadrant spider web area are larger than the second quadrant spider web area and the third quadrant spider web area and the fourth quadrant spider web area are larger than the first quadrant spider web area and the second quadrant spider web area, and the long axis of the spider web graph is in the X direction and is mainly distributed in the first quadrant and the third quadrant;
delta front edge subphase: the spider web area of the second quadrant and the third quadrant is larger than that of the first quadrant and the fourth quadrant, the spider web area of the first quadrant and the second quadrant is larger than that of the third quadrant and the fourth quadrant, and the long axis of the spider web is in the Y direction and mainly distributed in the first quadrant and the second quadrant;
front delta subphase: the spider web areas of the three and four quadrants are larger than the spider web areas of the first and second quadrants, the spider web areas of the second and third quadrants are larger than the spider web areas of the first and fourth quadrants, and the spider web diagram has no obvious long axis direction and is mainly distributed in the third quadrant.
In step 4, according to the difference of the four-parameter spider-web diagram obtained in step 3 under different depositional subphases, a depositional facies characterization formula is established by using four parameters through mathematical fitting:
S＝(α×103+A×102)/(H*P)；
where S represents the sedimentary subphase, α represents the formation dip, A represents the AC curve value, H represents the shale content, and P represents the SP resampling curve value.
In step 5, inputting and operating the four parameters of the actual drilling according to the mathematical formula obtained in step 4 to obtain an S value of the actual drilling, identifying a template according to the single well facies obtained in step 1, comparing the S value (representing the value of the sedimentary subphase) with the dividing result of the single well facies, and performing step 5, wherein the S value and the numerical value do not accord with each other, and repeating step 4.
In step 5, the threshold values of the S-discriminant function at different deposition subphases are determined: delta plain subphase S >500, delta leading edge subphase 300< S <500, and front delta subphase S < 300.
In step 5, an S discrimination function is established according to step 4, four parameter data of the exploratory well in the work area are input, a digital planogram of the delta sedimentary sub-phases is obtained, and the sedimentary sub-phases are divided by the different sedimentary sub-phase discrimination threshold values obtained in step 5 at the root.
The delta sedimentary subphase digital discrimination method utilizes the dual information constraint of earthquake and well drilling, utilizes a multivariate regression method to establish a sedimentary subphase digital discrimination function, and combines geological knowledge to determine a clear sedimentary subphase boundary threshold, thereby performing accurate sedimentary subphase division.
Drawings
FIG. 1 is a flowchart of an embodiment of a delta sedimentary subphase digital determination method of the present invention;
FIG. 2 is a schematic diagram of an electrical identification template for delta sedimentary subphase rocks in accordance with an embodiment of the present invention;
FIG. 3 is a schematic diagram of a recognition template for a deposition phase spider-web of Delta in an embodiment of the present invention;
FIG. 4 is a digitized plan view of a delta depositional subphase in accordance with an embodiment of the present invention.
Detailed Description
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
As shown in fig. 1, fig. 1 is a flowchart of the delta sedimentary subphase digital determination method of the present invention.
Step 101, on the basis of analysis of drilling and recording data and electrical measurement data and under the guidance of geologic theory knowledge of sedimentary facies of a delta sedimentary system, establishing an electrical recognition template of a sedimentary sub-facies rock of the delta, and performing single-well facies division:
establishing an identification template of the delta sedimentary sub-phase according to drilling, recording, electricity and seismic data:
plain subphase: the thick-layer sandstone sandstones sandwich the thin-layer mudstone, SP curves (natural potential curves) are bell-shaped and box-shaped, medium-strong amplitude and medium-strong continuity in the same-direction axis are realized, and frequency spectrums represent high-frequency energy clusters;
leading edge subphase: the SP curve is funnel-shaped, the equidirectional axis is medium and continuous in medium amplitude, and the frequency spectrum is expressed as a medium and high energy cluster;
front delta subphase: the thick-layer shale and the oil shale have flat SP curves, are in medium continuity in the same-direction axis weak amplitude, and have low-frequency energy clusters represented by frequency spectrums.
102, carrying out difference analysis on the rock physical, electrical and seismic properties of different deposition subphases by using a multi-parameter intersection analysis method to obtain difference characteristic parameters capable of representing different deposition subphases:
standardizing an AC curve, and eliminating environmental errors and value domain errors; 95< mudstone AC (plain subphase) <140,75< mudstone AC (leading edge subphase) <98,90< mudstone AC (front delta subphase) <105, mudstone developed within the delta plain subphase has an obvious high AC value, i.e. low speed characteristic;
standardizing the SP curve, and resampling the SP curve according to seismic resolution; 120< SP resample (plain subphase) <140,120< SP resample (leading edge subphase) <150, SP resample (anterior delta subphase) >150, anterior delta subphase has a significant high SP resample value;
and (3) carrying out statistics on the dip angles of the stratums of the same direction under different deposition subphase conditions: 1< dip (plain subphase) <6, 5< dip (front subphase) <12, 0.8< dip (front delta subphase) <5.7, delta front subphase having a significant high formation angle value;
103, establishing a deposition subphase multivariate parameter identification template by using a spider-web diagram characteristic parameter difference analysis method:
normalizing mudstone AC (acoustic wave time difference of mudstone), stratum inclination angle, shale content and SP resampling curve, establishing a four-corner coordinate system (as shown in figure 3) by utilizing the four parameters, wherein spider webs surrounded by different values of the four parameters under different deposition subphases are different;
delta plain subphase: the first quadrant spider web area and the fourth quadrant spider web area are larger than the second quadrant spider web area and the third quadrant spider web area and the fourth quadrant spider web area are larger than the first quadrant spider web area and the second quadrant spider web area, and the long axis of the spider web graph is in the X direction and is mainly distributed in the first quadrant and the third quadrant;
delta front edge subphase: the spider web area of the second quadrant and the third quadrant is larger than that of the first quadrant and the fourth quadrant, the spider web area of the first quadrant and the second quadrant is larger than that of the third quadrant and the fourth quadrant, and the long axis of the spider web is in the Y direction and mainly distributed in the first quadrant and the second quadrant;
front delta subphase: three, four-quadrant spider web area > first, two, quadrant spider web area, two, three-quadrant spider web area > first, four-quadrant spider web area, spider web picture have obvious major axis direction, mainly distribute in the third quadrant;
104, fitting the characteristic parameters by using a multiple regression mathematical fitting method, and establishing a deposition subphase quantitative discriminant function:
according to the difference of the four-parameter spider-web diagram obtained in the step 103 under different deposition subphases, a deposition phase characterization formula is established by using four parameters through mathematical fitting:
S＝(α×103+A×102)/(H*P)；
wherein S represents a sedimentary sub-phase, alpha represents a formation dip angle, A represents an AC curve value, H represents a shale content, and P represents an SP resampling curve value;
step 105, performing correlation analysis on the function value and the single well phase, and defining threshold ranges of different depositional subphase function values:
inputting and operating the four parameters of the actual drilling according to the mathematical formula obtained in the step 104 to obtain an S value of the actual drilling, comparing the S value with the division result of the single well phase according to the single well phase identification template obtained in the step 101, and if the S value and the division result of the single well phase are consistent, performing the step 105, and if the S value and the division result of the single well phase are inconsistent, repeating the step 104;
determining threshold values of the S discriminant function under different deposition subphases: s (delta plain subphase) >500,300< S (delta leading edge subphase) <500, S (front delta subphase) < 300;
and 106, inputting real drilling characteristic parameters to obtain a delta sedimentary subphase digital plan.
And (5) establishing an S discrimination function according to the step 104, inputting four parameter data of the exploratory well in the work area to obtain a digital planogram of the delta sedimentary sub-facies, and finishing the partition of the sedimentary sub-facies by obtaining different sedimentary sub-facies discrimination threshold values in the root step 105.
In one embodiment of the present invention, the method comprises the following steps:
the first step is as follows: the lithology and the electrical property under different delta sedimentary subphases are analyzed, a delta sedimentary subphases electrical identification template (shown as a figure 2) is established by combining geological theory, and single-well facies division is carried out on the basis to obtain a single-well sedimentary subphase mode diagram.
The second step is that: and performing difference analysis on the physical parameters, well logging and seismic properties of rocks under different Delta sedimentary subphases, and performing correlation analysis and screening to obtain difference characteristic parameters capable of independently representing different sedimentary subphases.
The third step: and (3) normalizing each characteristic parameter by using a spider-web image identification method, and projecting the normalized characteristic parameters into the spider-web image to establish different Delta sedimentary subphase identification templates such as an image (3).
The fourth step: and performing multiple regression mathematical fitting on the difference characteristic parameters to obtain a quantification function of the delta sedimentary subphase, thereby realizing digital discrimination of the delta sedimentary subphase.
The fifth step: and (4) correcting the environmental error, improving the function value identification precision, comparing the identification result with the actual drilling single well, and defining the function value threshold ranges of different sedimentary sub-phases according to the actual drilling single well phase data, wherein the coincidence degree of the two is low, and the fourth step is repeated.
And a sixth step: and (4) carrying out judgment of the delta sedimentary sub-facies in the whole work area by utilizing a judgment function to obtain a digital planform of the delta sedimentary sub-facies as shown in a figure (4).
The method for digitally judging the sedimentary subphase of the delta innovatively utilizes a mode of digitally dividing the sedimentary subphase, ensures the accuracy and reliability of identifying the sedimentary subphase boundary, can more truly reflect the sedimentary environment in the sedimentary period of the delta and the propelling direction to a lake basin in the growth process of the delta, and further can provide a reliable geological model medium for the subsequent determination of a nepheloid rock development area in a delta system and the oil-gas exploration development.
Claims (4)
1. The method for digitally judging the deposition subphase of the delta is characterized by comprising the following steps of:
step 1, establishing an electrical identification template of a sedimentary subgrain rock of delta, and performing single-well facies division;
step 2, carrying out difference analysis on the rock physical, electrical and seismic properties of different deposition subphases by using a multi-parameter intersection analysis method to obtain difference characteristic parameters capable of representing different deposition subphases;
step 3, establishing a deposition subphase multivariate parameter identification template by utilizing a spider-web diagram characteristic parameter difference analysis method;
step 4, fitting the characteristic parameters by using a multiple regression mathematical fitting method, and establishing a deposition subphase quantitative discrimination function;
step 5, performing correlation analysis on the function value and the single well phase, and defining threshold ranges of different deposition sub-phase function values;
step 6, inputting real drilling characteristic parameters to obtain a delta sedimentary subphase digital plan;
in step 3, normalizing mudstone AC, stratum inclination angle, shale content and SP resampling curves, establishing a four-corner coordinate system by using the four parameters, wherein spider webs surrounded by different values of the four parameters under different sedimentary subphases are different in shape;
delta plain subphase: the first quadrant spider web area and the fourth quadrant spider web area are larger than the second quadrant spider web area and the third quadrant spider web area and the fourth quadrant spider web area are larger than the first quadrant spider web area and the second quadrant spider web area, and the long axis of the spider web graph is in the X direction and is mainly distributed in the first quadrant and the third quadrant;
delta front edge subphase: the spider web area of the second quadrant and the third quadrant is larger than that of the first quadrant and the fourth quadrant, the spider web area of the first quadrant and the second quadrant is larger than that of the third quadrant and the fourth quadrant, and the long axis of the spider web is in the Y direction and mainly distributed in the first quadrant and the second quadrant;
front delta subphase: three, four-quadrant spider web area > first, two, quadrant spider web area, two, three-quadrant spider web area > first, four-quadrant spider web area, spider web picture have obvious major axis direction, mainly distribute in the third quadrant;
in step 4, according to the difference of the four-parameter spider-web diagram obtained in step 3 under different depositional subphases, a depositional facies characterization formula is established by using four parameters through mathematical fitting:
S＝(α×103+A×102)/(H*P)；
wherein S represents a sedimentary sub-phase, alpha represents a formation dip angle, A represents an AC curve value, H represents a shale content, and P represents an SP resampling curve value;
in step 5, inputting and operating the four parameters of the actual drilling according to the mathematical formula obtained in the step 4 to obtain an S value of the actual drilling, comparing the S value with the dividing result of the single well phase according to the single well phase identification template obtained in the step 1, and performing the step 5 if the S value and the dividing result of the single well phase are consistent, and repeating the step 4 if the S value and the dividing result of the single well phase are inconsistent;
determining threshold values of the S discriminant function under different deposition subphases: delta plain subphase S >500, delta leading edge subphase 300< S <500, front delta subphase S < 300;
and (4) establishing an S discrimination function according to the step (4), inputting four parameter data of the exploratory well in the work area to obtain a digital planogram of the delta sedimentary sub-facies, and finishing the partition of the sedimentary sub-facies by the different sedimentary sub-facies discrimination threshold values obtained in the step (5) at the root part.
2. The method for digitally discriminating the subgrade phase of Delta sedimentary facies according to claim 1, wherein in step 1, on the basis of the analysis of drilling and recording data and electrical measurement data, and under the guidance of geological theory knowledge of the sedimentary facies of the Delta sedimentary system, a subgrade phase recognition template of Delta sedimentary facies is established according to the drilling, recording, electrical and seismic data, so as to divide the single well facies.
3. The method for digitally discriminating a sedimentary subgrade of Delta according to claim 2, wherein in step 1, the single-well facies is divided into:
plain subphase: the thick-layer sandstone sandstones sandwich the thin-layer mudstone, SP curves are bell-shaped and box-shaped, medium-strong amplitude and medium-strong continuity in the same-direction axis are realized, and frequency spectrums represent high-frequency energy clusters;
leading edge subphase: the SP curve is funnel-shaped, the equidirectional axis is medium and continuous in medium amplitude, and the frequency spectrum is expressed as a medium and high energy cluster;
front delta subphase: the thick-layer shale and the oil shale have flat SP curves, are in medium continuity in the same-direction axis weak amplitude, and have low-frequency energy clusters represented by frequency spectrums.
4. The method according to claim 1, wherein the difference characteristic parameters obtained in step 2 include:
standardizing an AC curve, and eliminating environmental errors and value domain errors; plain subphase: 95< mudstone AC <140, leading edge subphase: 75< mudstone AC <98, anterior delta subphase: 90< mudstone AC <105, the mudstone developed in delta plain subphase has obvious high AC value, namely low speed characteristic;
standardizing the SP curve, and resampling the SP curve according to seismic resolution; plain subphase: 120< SP resample <140, leading edge subphase: 120< SP resample <150, anterior delta subphase SP resample >150, anterior delta subphase has an apparent high SP resample value;
and (3) carrying out statistics on the dip angle of the stratums of the same direction under different deposition subphase conditions, wherein the plain subphase: 1< dip <6, leading edge subphase: 5< dip <12, anterior delta subphase: 0.8< dip <5.7, delta front subphase has a significant high formation angle value.
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