CN110907990B - Quantitative prediction method and system for post-stack seismic cracks - Google Patents
Quantitative prediction method and system for post-stack seismic cracks Download PDFInfo
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Abstract
The invention relates to a quantitative prediction method and a quantitative prediction system for post-stack seismic cracks, and belongs to the technical field of seismic exploration. And simulating and establishing a relational expression between variance body attribute values under different time window lengths corresponding to a fracture zone with set fracture density according to the obtained post-stack seismic data body of the work area, the structure interpretation horizon of the research group section, the geology for describing fracture development characteristics and logging data, calculating to obtain a work area variance body with set fracture density, obtaining a work area fracture variance attribute body of a set fracture density interval by combining the calculation process, and predicting the fracture according to the obtained work area fracture prediction variance attribute body. The technical scheme provided by the invention can realize quantitative prediction of the micro-scale crack zones, can realize identification and differentiation of the crack zones with different scales, has better practicability and economical efficiency, and can greatly save the production cost especially in the areas where the existing seismic data do not meet the application of the pre-stack crack prediction technology.
Description
Technical Field
The invention relates to a quantitative prediction method and a quantitative prediction system for post-stack seismic cracks, and belongs to the technical field of seismic exploration.
Background
The crack oil gas is stored in China and distributed widely, especially at the present of higher and higher exploration degree, the crack type non-structural oil gas reservoir gradually becomes the main attack direction of the exploration field, but due to the strong heterogeneity of the crack distribution and the complexity of the distribution rule, the recognition and prediction of the crack are always difficult points of exploration. The crack prediction method is various, such as earthquake, geology, well logging and the like, and the earthquake method has stronger practicability due to the characteristic of transverse continuity, and the application effect of the method is better and better.
When seismic waves pass through fracture and crack development zones, the dynamic characteristics (amplitude) and the kinematic characteristics (travel time) of the seismic waves are changed, and fault and crack development zones can be indirectly predicted by extracting seismic wave attributes. The pre-stack seismic fracture prediction technology can realize semi-quantitative fracture prediction by utilizing more information such as fracture azimuth and the like, but has higher requirements on acquisition azimuth, offset and coverage times of pre-stack seismic data, and high application cost, and relatively, the post-stack seismic fracture prediction technology has better economy and applicability.
The post-stack seismic crack prediction technology mainly comprises single-channel attributes such as amplitude, frequency and phase, coherence, curvature, ant tracking and the like, the seismic single-channel attribute technology cannot establish a one-to-one correspondence relationship between crack development strength and attribute parameters, and the multi-solution is strong; the ant tracing technology provides a method for qualitatively depicting the space distribution of medium and small-scale cracks based on an ant algorithm; the coherent body technology is most widely applied at present, cracks are predicted by analyzing spatial discontinuity of earthquake combined traces, the technology is developed from a first generation cross-correlation algorithm to a second generation similarity algorithm and a third generation intrinsic structure algorithm, the noise immunity and the prediction effect are more prominent, and the transverse continuity of a crack development zone is more clearly depicted. But the method is only limited to the qualitative description of cracks, mainly aims at fractures and cracks above meter level, and does not consider the detection and the differentiation of micro-scale crack belts formed by crack units below meter level.
The invention discloses a method for quantitative prediction of cracks based on seismic attributes, which is based on a curvature attribute body and a coherent body attribute body after value domain correction, indicates crack development strength by using the curvature attribute, represents crack distribution form by using the coherent body attribute, and calculates to obtain a crack prediction attribute body. However, the method does not really establish direct connection between the crack density and the curvature attribute, only gives the relative development strength of the crack, and meanwhile, the sensitivity of the curvature attribute to the micro-scale crack belt is low, so that the quantitative identification and prediction of the micro-scale crack belt are difficult to realize.
It can be seen that the correspondence between the crack density and the seismic attributes, the quantitative identification of the micro-scale crack zones below the meter level (the scales mentioned in the present invention are all the crack unit scales constituting the crack zones, and are not the crack zone scales), and the differentiation between the micro-scale crack zones and the large-scale fracture and crack zones are all problems to be solved by the post-stack seismic crack quantitative prediction technology.
Disclosure of Invention
The invention aims to provide a quantitative prediction method and a quantitative prediction system for post-stack seismic cracks, which are used for solving the problem of poor prediction reliability caused by the fact that the existing quantitative prediction technology for post-stack cracks cannot realize the quantitative prediction of micro-scale crack zones.
In order to achieve the above object, the present invention includes the following technical solutions.
A quantitative prediction method for post-stack seismic fractures comprises the following steps:
(1) acquiring a post-stack seismic data volume of a work area, a structure interpretation horizon of a research group section, geology for describing crack development characteristics and logging information;
(2) simulating and establishing a relational expression between variance body attribute values under different time window lengths corresponding to the crack zone with set crack density, and calculating to obtain a work area variance body with set crack density;
(3) calculating to obtain a work area crack prediction variance attribute body of a set crack density interval according to the step (2);
(4) and predicting the spatial distribution and the relative strength of the crack by using the obtained work area crack prediction variance attribute body of the set crack density interval and the structure interpretation horizon of the research group section.
The variance body is adopted as the seismic attribute for establishing the corresponding relation with the crack density, belongs to the second type coherence body technology, is in positive correlation variation trend with the crack density, has strong sensitivity to the crack development zone, can detect the discontinuous boundary of the micro-scale crack zone, and ensures the feasibility of implementation of the scheme. According to the scheme, a direct corresponding relation is established among the crack unit size, the crack density and the variance attribute, the variance attribute corresponding to the micro-scale crack zone in any crack density interval can be obtained by utilizing the corresponding relation, and quantitative prediction of the micro-scale crack zone is realized; furthermore, the identification and the distinction of the crack belts with different scales can be realized by utilizing the corresponding relation. In addition, the prediction method provided by the scheme has better practicability and economical efficiency, and particularly can greatly save the production cost in the area where the existing seismic data do not meet the application of the pre-stack crack prediction technology.
Further, the step (2) specifically comprises:
1) establishing a depth domain velocity field of the set fracture density by using the geology and logging information of the research group section describing fracture development characteristics obtained in the step (1);
2) forward modeling and migration are carried out on the established depth domain velocity field, and a post-stack migration profile with set crack density is obtained;
3) extracting the variation t of seismic wave travel time corresponding to the positions containing the cracks and the positions not containing the cracks from the obtained post-stack migration profile;
4) taking n multiples nt of the variation t of seismic wave travel time corresponding to the extracted positions containing the cracks and the positions not containing the cracks as time window lengths for calculating a variance body, and respectively calculating the variance body of the post-stack migration section to obtain n time window lengths of the set crack density of the variance body section;
5) extracting variance body attribute values corresponding to a crack development area from the obtained variance body section with n time window lengths for setting the crack density, and establishing a relational expression between the variance body attribute values under the n time window lengths;
6) calculating the variance body of the work area post-stack seismic data body according to the time window length of the variance body obtained by calculation to obtain work area variance bodies with n time window lengths;
7) and extracting variance body attribute values meeting the relation from the work area variance bodies with the n time window lengths by using the established relation among the variance body attribute values with the n time window lengths to obtain the work area variance body with the set crack density.
The working area variance cube of the set crack density can be obtained through the implementation process. Moreover, through forward modeling, a direct corresponding relation is established among the crack unit size, the crack density and the variance body attributes, the variance body result corresponding to the size to be researched and the crack density to be researched can be obtained, and the separation of crack zones with different sizes and the quantitative prediction of the set crack density are realized.
Further, the step (3) specifically comprises:
i) selecting k fracture density values from the set fracture density interval, obtaining a group of time window lengths corresponding to the fracture density values in the k fracture density values according to the correlation process in the step (2), obtaining k groups of time window lengths together, establishing a relational expression which is satisfied by the variance body attribute values under the k groups of time window lengths, and determining m time window lengths used by the relational expression;
ii) respectively calculating variance bodies of the acquired post-stack seismic data bodies of the work area according to the m time window lengths determined in the step i) to obtain work area variance bodies under the m time window lengths;
and iii) extracting the variance body attribute values meeting the relation from the work area variance bodies with m time window lengths by using the relation formula which is jointly met by the variance body attribute values under the k groups of time window lengths, and obtaining the work area fracture prediction variance attribute body of the set fracture density interval.
The working area crack prediction variance attribute body of the set crack density interval can be accurately and reliably obtained through the implementation process.
Further, when the established depth domain velocity field is subjected to forward modeling, a variable-grid sound wave forward modeling method is adopted when the dimension of the crack unit is smaller than the meter level, and a conventional sound wave forward modeling method is adopted when the dimension of the crack unit is at the meter level or above. And performing reliable forward modeling on the established depth domain speed field by adopting a corresponding forward modeling method according to different satisfied conditions.
A quantitative post-stack seismic fracture prediction system comprising a prediction module comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor when executing the computer program implementing a control process comprising:
(1) acquiring a post-stack seismic data volume of a work area, a structure interpretation horizon of a research group section, geology for describing crack development characteristics and logging information;
(2) simulating and establishing a relational expression between variance body attribute values under different time window lengths corresponding to the crack zone with set crack density, and calculating to obtain a work area variance body with set crack density;
(3) calculating to obtain a work area crack prediction variance attribute body of a set crack density interval according to the step (2);
(4) and predicting the spatial distribution and the relative strength of the crack by using the obtained work area crack prediction variance attribute body of the set crack density interval and the structure interpretation horizon of the research group section.
The prediction system adopts the variance body as the seismic attribute for establishing the corresponding relation with the crack density, the variance body belongs to the second type coherence body technology, the variance body has positive correlation variation trend with the crack density, and has strong sensitivity to a crack development zone, so that the discontinuous boundary of a micro-scale crack zone can be detected, and the feasibility of implementation of a scheme is ensured. The prediction system establishes a direct corresponding relation among the crack unit size, the crack density and the variance attribute, and can obtain the variance attribute corresponding to the micro-scale crack zone in any crack density interval by utilizing the corresponding relation so as to realize quantitative prediction of the micro-scale crack zone; furthermore, the identification and the distinction of the crack belts with different scales can be realized by utilizing the corresponding relation. In addition, the prediction system has better practicability and economical efficiency, and particularly in the areas where the existing seismic data do not meet the application of the pre-stack crack prediction technology, the prediction system can greatly save the production cost.
Further, the step (2) specifically comprises:
1) establishing a depth domain velocity field of the set fracture density by using the geology and logging information of the research group section describing fracture development characteristics obtained in the step (1);
2) forward modeling and migration are carried out on the established depth domain velocity field, and a post-stack migration profile with set crack density is obtained;
3) extracting the variation t of seismic wave travel time corresponding to the positions containing the cracks and the positions not containing the cracks from the obtained post-stack migration profile;
4) taking n multiples nt of the variation t of seismic wave travel time corresponding to the extracted positions containing the cracks and the positions not containing the cracks as time window lengths for calculating a variance body, and respectively calculating the variance body of the post-stack migration section to obtain n time window lengths of the set crack density of the variance body section;
5) extracting variance body attribute values corresponding to a crack development area from the obtained variance body section with n time window lengths for setting the crack density, and establishing a relational expression between the variance body attribute values under the n time window lengths;
6) calculating the variance body of the work area post-stack seismic data body according to the time window length of the variance body obtained by calculation to obtain work area variance bodies with n time window lengths;
7) and extracting variance body attribute values meeting the relation from the work area variance bodies with the n time window lengths by using the established relation among the variance body attribute values with the n time window lengths to obtain the work area variance body with the set crack density.
The working area variance cube of the set crack density can be obtained through the implementation process. Moreover, through forward modeling, a direct corresponding relation is established among the crack unit size, the crack density and the variance body attributes, the variance body result corresponding to the size to be researched and the crack density to be researched can be obtained, and the separation of crack zones with different sizes and the quantitative prediction of the set crack density are realized.
Further, the step (3) specifically comprises:
i) selecting k fracture density values from the set fracture density interval, obtaining a group of time window lengths corresponding to the fracture density values in the k fracture density values according to the correlation process in the step (2), obtaining k groups of time window lengths together, establishing a relational expression which is satisfied by the variance body attribute values under the k groups of time window lengths, and determining m time window lengths used by the relational expression;
ii) respectively calculating variance bodies of the acquired post-stack seismic data bodies of the work area according to the m time window lengths determined in the step i) to obtain work area variance bodies under the m time window lengths;
and iii) extracting the variance body attribute values meeting the relation from the work area variance bodies with m time window lengths by using the relation formula which is jointly met by the variance body attribute values under the k groups of time window lengths, and obtaining the work area fracture prediction variance attribute body of the set fracture density interval.
The working area crack prediction variance attribute body of the set crack density interval can be accurately and reliably obtained through the implementation process.
Further, when the established depth domain velocity field is subjected to forward modeling, a variable-grid sound wave forward modeling method is adopted when the dimension of the crack unit is smaller than the meter level, and a conventional sound wave forward modeling method is adopted when the dimension of the crack unit is at the meter level or above. And performing reliable forward modeling on the established depth domain speed field by adopting a corresponding forward modeling method according to different satisfied conditions.
Drawings
FIG. 1 is a flow chart illustrating a method for quantitatively predicting a post-stack seismic fracture according to an embodiment of the present invention;
FIG. 2-a is a schematic diagram of a background mesh model of a depth-domain velocity field with a fracture density of 0.05;
FIG. 2-b is a schematic diagram of a condensed grid model of a fracture development zone;
FIG. 3-a is a schematic diagram of forward shot gathers of 10 th to 15 th shots;
FIG. 3-b is a schematic representation of a post-stack migration profile with a fracture density of 0.05;
FIG. 4-a is an enlarged view of the 4ms window length variance volume profile in the fracture growth zone;
FIG. 4-b is an enlarged view of the 8ms window length variance volume profile in the fracture growth zone;
FIG. 5-a is a plan view of a conventional variance cube taken along a certain interval of the T3x set with a time window length of 4 ms;
FIG. 5-b is a plan view of a fracture density interval [0.05, 0.2] taken along an interval of T3x group;
FIG. 6-a is an enlarged partial view of FIG. 5-b at the location of the J1 well;
FIG. 6-b is an enlarged partial view of FIG. 5-b at the J2 well location;
FIG. 6-c is an enlarged partial view of FIG. 5-b at the J3 well location;
FIG. 6-d is an enlarged partial view of FIG. 5-b at the J4 well location;
FIG. 6-e is an enlarged partial view of FIG. 5-b at the J5 well location;
FIG. 7-a is a cross-sectional view of a zonal variation through a J1 well with a fracture density interval [0.05, 0.2 ];
FIG. 7-b is a cross-sectional view of a zonal variation through a J6 well with a fracture density interval [0.05, 0.2 ];
FIG. 7-c is a cross-sectional view of a zonal variation through a J7 well with a fracture density interval of [0.05, 0.2 ].
Detailed Description
A quantitative prediction method for post-stack seismic fractures comprises the following steps:
(1) acquiring a post-stack seismic data volume of a work area, a structure interpretation horizon of a research group section, geology for describing crack development characteristics and logging information;
(2) simulating and establishing a relational expression between variance body attribute values under different time window lengths corresponding to the crack zone with set crack density, and calculating to obtain a work area variance body with set crack density;
(3) calculating to obtain a work area crack prediction variance attribute body of a set crack density interval according to the step (2);
(4) and predicting the spatial distribution and the relative strength of the crack by using the obtained work area crack prediction variance attribute body of the set crack density interval and the structure interpretation horizon of the research group section.
Based on the basic technical scheme of the post-stack seismic fracture quantitative prediction method, the steps of the prediction method are specifically described below with reference to the accompanying drawings.
As shown in fig. 1, the quantitative prediction method for post-stack seismic fractures includes the following major parts:
1. preparing data: and acquiring a post-stack seismic data volume of the work area, a structural interpretation horizon of a research group section, geology for describing crack development characteristics and logging information.
2. And (2) simulating and establishing a relational expression between variance body attribute values under different time window lengths corresponding to the set crack density by using the post-stack seismic data volume of the work area, the geology for describing crack development characteristics of a research group section and logging data acquired in the step (1), wherein the set crack density is expressed by the crack density e, and then simulating and establishing a relational expression between variance body attribute values under different time window lengths corresponding to a crack zone with the crack density e, thereby calculating and obtaining the work area variance body with the crack density e. The specific implementation process of the step is given as follows:
2.1, describing geology and well logging information of crack development characteristics by using the research group section obtained in the step 1, and establishing a depth domain velocity field with the crack density of e;
2.2, forward modeling and shifting the depth domain velocity field with the crack density e established in the step 2.1 to obtain a post-stack shifting section with the crack density e, wherein a variable grid sound wave forward modeling method is adopted when the crack unit size is smaller than meter level, and a conventional sound wave forward modeling method is adopted when the crack unit size is meter level or above;
2.3, extracting the seismic wave travel time variation t corresponding to the positions containing the cracks and the positions not containing the cracks from the post-stack migration profile with the crack density e obtained in the step 2.2;
2.4, taking n multiples nt (n is 1, 2, 3, …, namely n multiples are continuously taken from 1 to n) of the variation t of the seismic wave travel time corresponding to the positions containing the cracks and the positions not containing the cracks extracted in the step 2.3 as the time window length for calculating the variance body, respectively calculating the variance body of the post-stack migration cross section with the crack density e obtained in the step 2.2, and obtaining n time window length variance body cross sections with the crack density e;
2.5, extracting variance body attribute values f (nt) corresponding to the fracture development areas from the variance body sections with the n time window lengths with the fracture density of e obtained in the step 2.4, and establishing a relational expression y (g (f (nt)) between the variance body attribute values f (nt)) under the n time window lengths;
2.6, respectively calculating the variance body of the seismic data body after the work area stack obtained in the step 1 according to the time window length nt of the variance body calculated in the step 2.4 to obtain work area variance bodies with n time window lengths;
and 2.7, extracting variance body attribute values meeting the relational expression from the work area variance bodies with the n time window lengths obtained in the step 2.6 by using the relational expression y ═ g (f (nt)) between the variance body attribute values f (nt) under the n time window lengths established in the step 2.5, and obtaining the work area variance body with the fracture density e.
3. The property of the prediction variance of the work zone fracture is calculated in accordance with the above step 2, and the set fracture density interval is represented by an interval [ e1, e2 ]. The specific implementation process of the step is given as follows:
3.1 from the set crack density interval [ e1, e2]]Selecting k density values b (k), wherein b (k) belongs to [ e1, e2]]And k is 1, 2, 3 and …, and the seismic wave travel time variation t of the positions containing the cracks and not containing the cracks corresponding to the density values of the cracks in the k crack densities is obtained according to the steps 2.1 to 2.5kN time window lengths, then, in total, this is trueTo obtain a fracture interval [ e1, e2]]K sets of time window lengths, and a total of nk. Then, the variance body attribute value f under k groups of time window lengths is establishedbk(ntk) The commonly satisfied relation y ═ h (p (nt)k) Where p ═ f), in whichbkAnd determining m time window lengths used in the relation, wherein m is 1, 2, 3 and …;
3.2, respectively calculating variance bodies of the seismic data bodies after the work area stacking obtained in the step 1 according to the m time window lengths determined in the step 3.1 to obtain work area variance bodies under the m time window lengths;
3.3, the equation y ═ h (p (nt) commonly satisfied by the variance volume attribute values for the k sets of time window lengths obtained in step 3.1 (n ═ k [ (- ])k))，p＝fbkN is 1, 2, 3, …, k is 1, 2, 3, …, and variance data attribute values satisfying the relation are extracted from the work area variance data of m time window lengths obtained in step 3.2 to obtain fracture density intervals [ e1, e2]]The variance attribute of the work area crack prediction.
Therefore, by setting the scale range of the fracture unit in the depth domain velocity field modeling, the work area fracture prediction variance attribute bodies corresponding to fracture zones with different scales and fracture density intervals can be obtained.
4. And (3) predicting the spatial distribution and the relative strength of the fracture according to the obtained work area fracture prediction variance attribute body with the fracture density interval [ e1, e2] and the structure interpretation horizon of the research group section obtained in the step 1.
Taking a T3x group of a work area of the Sichuan basin as a research layer group, taking a micro-scale crack zone with crack units below meter level and crack quantitative prediction with a crack density interval of [0.05, 0.2] as an example according to the actual situation of the layer group, and combining the accompanying drawings to detail the quantitative prediction method of the post-stack seismic cracks, wherein the specific steps are as follows:
1. preparing data: and acquiring a post-stack seismic data volume of a work area, and a structural interpretation horizon of a T3x group of the work area, geology describing crack development characteristics and logging information.
2. And (3) simulating and establishing a relational expression between variance body attribute values under different time window lengths corresponding to a crack zone with the crack density of 0.05 by using the post-stack seismic data volume of the work area obtained in the step (1) and the geological and well logging data of the work area T3x group for describing crack development characteristics, and calculating to obtain a work area variance body with the crack density of 0.05. The method specifically comprises the following implementation processes:
2.1, establishing a depth domain velocity field with fracture density of 0.05 by using geological and well logging information describing fracture development characteristics of the T3x group of work area acquired in the step 1: the depth domain velocity field size is 7.5km x 4.0km, the background velocity is 4200-5500 m/s, the depth domain velocity field level is 3550 m-3900 m, the region with the depth of 2915 m-3465 m is a crack development region, the opening of a crack unit is 0.5m, the crack filling speed is 3000m/s, the seismic dominant frequency is 30Hz, the background grid dimension of the depth domain velocity field is determined to be 5m by using a formula (1) and a formula (2) in combination with the crack opening, the time step size is 0.2ms, the encryption grid dimension of the crack development region is 0.5m, and the encryption time step size is 0.02ms, so that the grid model of the depth domain velocity field with the crack density of 0.05 is established. FIG. 2-a shows a background grid model of a depth domain velocity field with a crack density of 0.05, with a grid size of 1501 x 801, and FIG. 2-b shows a dense grid model of a crack growth zone;
wherein, Δ x: background grid scale of the depth domain velocity field, Δ t: background time step, v, of the depth-domain velocity fieldmin: minimum velocity, v, of the depth-domain velocity fieldmax: maximum velocity of the depth domain velocity field, feq: earthquake dominant frequency;
2.2, forward modeling and deviation are carried out on the depth domain velocity field with the crack density of 0.05, which is established in the step 2.1, a variable grid forward modeling method is adopted, and forward modeling parameters are as follows: the total number of 101 cannons is 101, the calculation range of each cannon is a full-speed field, the starting cannon point position is 1250m, the interval of the cannon points is 50m, the cannon line and the receiving line are at the depth of 25m, and a forward shot set of 10 th to 15 th cannons is shown in a figure 3-a; the migration method was Kirchhoff pre-stack time migration, thereby yielding a post-stack migration profile with a fracture density of 0.05, as shown in fig. 3-b;
2.3, extracting the variation t of the seismic wave travel time corresponding to the positions containing the cracks and the positions not containing the cracks from the post-stack migration section with the crack density of 0.05 obtained in the step 2.2, wherein the t is 4 ms;
2.4, taking multiples of the variation t of seismic wave travel time corresponding to the positions containing the cracks and the positions not containing the cracks extracted in the step 2.3, namely 4ms and 8ms (namely 1 time and 2 times of the variation t) as time window lengths for calculating a variance body, respectively calculating the variance body of the post-stack migration cross section with the crack density of 0.05 obtained in the step 2.2, and obtaining variance body cross sections with the crack density of 0.05, wherein a graph 4-a and a graph 4-b are respectively enlarged images of the variance body cross sections in a crack development area, wherein the graph 4-a is an enlarged image corresponding to the length of the 4ms time window, and the graph 4-b is an enlarged image corresponding to the length of the 8ms time window;
2.5, extracting variance body attribute values f (t) and f (2t) corresponding to the crack positions in the variance body section with the crack density of 0.05 obtained in the step 2.4, and establishing a relational expression between the variance body attribute values under the two time window lengths, wherein the relational expression is f (t) -2f (2t) approximately equal to 0;
2.6, respectively calculating the variance bodies of the seismic data bodies after the work area stacking obtained in the step 1 according to the time window lengths of 4ms and 8ms of the variance bodies calculated in the step 2.4 to obtain work area variance bodies with two time window lengths;
2.7, extracting the variance body attribute value meeting the relational expression from the work area variance body with the two time window lengths obtained in the step 2.6 by using the relational expression f (t) -2f (2t) between the variance body attribute values under the two time window lengths established in the step 2.5 to obtain the work area variance body with the crack density of 0.05;
3. and (4) calculating according to the step 2 to obtain a work area crack prediction variance attribute body with a crack density interval of [0.05, 0.2 ]. The method specifically comprises the following implementation processes:
3.1, selecting interval [0.05, 0.2]]3 density values of 0.05, 0.1 and 0.2, 3 groups of time window lengths with crack densities of 0.05, 0.1 and 0.2, 4ms, 8ms, 5ms, 10ms, 7ms and 14ms (t is t) are obtained according to the steps 2.1-2.50.05＝4ms，t0.1＝5ms，t0.17ms), a variance volume attribute value f is established under 3 groups of time window lengths0.05(t) and f0.05(2t)、f0.1(t) and f0.1(2t)、f0.2(t) and f0.2(2t) commonly satisfied relational expression (p (t)0.05)-2p(t0.1)≤-0.08)and(p(t0.1)-p(2t0.1)≥0.08)，p＝f0.05，f0.1，f0.2Determining the length t of 3 time windows used in the relation0.05、t0.1、2t0.1；
3.2 3 time window lengths t used according to the relation determined in step 3.10.05、t0.1、2t0.1Respectively calculating the variance bodies of the post-stack seismic data bodies of the work area obtained in the step 1 to obtain work area variance bodies under the length of 3 time windows;
3.3, using the relation (p (t) commonly satisfied by the variance body attribute values under the 3 groups of time window lengths obtained in the step 3.10.05)-2p(t0.1)≤-0.08)and(p(t0.1)-p(2t0.1)≥0.08)，p＝f0.05，f0.1，f0.2Extracting variance body attribute values meeting the relation from the work area variance body with 3 time window lengths obtained in the step 3.2 to obtain a fracture density interval of [0.05, 0.2]]The variance attribute of the work area crack prediction.
Comparative example: 5-a is a plan view of a conventional variance cube with a time window length of 4ms acquired along a certain interval of T3x group, and 5-b is a plan view of a fracture density interval of [0.05, 0.2] acquired along a certain interval of T3x group, as can be seen by comparison, the fracture prediction result obtained according to the technical process of the invention can better eliminate variance abnormal high values caused by large-scale fracture and fracture, retain variance attribute response of a micro-scale fracture zone, realize identification and differentiation of different-scale fracture zones, and only retain variance attribute values corresponding to the fracture density interval of [0.05, 0.2] in the fracture prediction result, thereby realizing quantitative prediction of the micro-scale fracture zone.
Compare FIG. 5-b with drilled wells: the J1 well had statistically higher fracture density in the core of the interval, and the J1 well fell at the variance high point in FIG. 5-b, which coincided with the predicted result, as shown in FIG. 6-a; the J2 log was interpreted as a fracture-pore type gas zone, corresponding to the high variance values in fig. 5-b, consistent with the predicted results, as shown in fig. 6-b; j3 and J4 wells drilled encountered faults in this group of sections, shown in FIG. 5-b as low variance regions falling in the fault zone, consistent with the predicted results, as shown in FIGS. 6-c and 6-d; the core of the group of J5 wells is 1.37m, the statistical crack of the rock core does not develop, the square-free difference in the plane is always displayed and accords with the prediction result, as shown in figure 6-e, the coincidence rate of the statistical work area is more than 80%, and the method has higher accuracy.
7-a, 7-b and 7-c are well-crossing profiles of the obtained work area variance volume crossing J1 (FIG. 7-a), J6 (FIG. 7-b) and J7 (FIG. 7-c) wells with fracture density intervals of [0.05, 0.2], respectively, wherein the well logging curves in the FIGS. 7-a and 7-b are core statistical fracture density curves, the well logging explanation or statistical data of each well section indicated by an arrow in the figures shows fractures, and the positions indicated by the arrows correspond to variance values of different degrees, so that the reliability and the effectiveness of the fracture quantitative prediction method provided by the invention are further verified.
The specific embodiments are given above, but the present invention is not limited to the described embodiments. The basic idea of the present invention lies in the above basic scheme, and it is obvious to those skilled in the art that no creative effort is needed to design various modified models, formulas and parameters according to the teaching of the present invention. Variations, modifications, substitutions and alterations may be made to the embodiments without departing from the principles and spirit of the invention, and still fall within the scope of the invention.
The quantitative prediction method for the post-stack seismic fractures can be used as a computer program, loaded into a memory in a prediction module in a quantitative prediction system for the post-stack seismic fractures, and run on a processor in the prediction module.
Claims (6)
1. A quantitative prediction method for post-stack seismic fractures is characterized by comprising the following steps:
(1) acquiring a post-stack seismic data volume of a work area, a structure interpretation horizon of a research group section, geology for describing crack development characteristics and logging information;
(2) simulating and establishing a relational expression between variance body attribute values under different time window lengths corresponding to the fracture zone with set fracture density, and calculating to obtain the work area variance body with set fracture density, wherein the step (2) specifically comprises the following steps:
1) establishing a depth domain velocity field of the set fracture density by using the geology and logging information of the research group section describing fracture development characteristics obtained in the step (1);
2) forward modeling and migration are carried out on the established depth domain velocity field, and a post-stack migration profile with set crack density is obtained;
3) extracting the variation t of seismic wave travel time corresponding to the positions containing the cracks and the positions not containing the cracks from the obtained post-stack migration profile;
4) taking n multiples nt of the variation t of seismic wave travel time corresponding to the extracted positions containing the cracks and the positions not containing the cracks as time window lengths for calculating a variance body, and respectively calculating the variance body of the post-stack migration section to obtain n time window lengths of the set crack density of the variance body section;
5) extracting variance body attribute values corresponding to a crack development area from the obtained variance body section with n time window lengths for setting the crack density, and establishing a relational expression between the variance body attribute values under the n time window lengths;
6) calculating the variance body of the work area post-stack seismic data body according to the time window length of the variance body obtained by calculation to obtain work area variance bodies with n time window lengths;
7) extracting variance body attribute values meeting the relation from the work area variance bodies with the n time window lengths by using the established relation among the variance body attribute values with the n time window lengths to obtain the work area variance body with the set crack density;
(3) calculating to obtain a work area crack prediction variance attribute body of a set crack density interval according to the step (2);
(4) and predicting the spatial distribution and the relative strength of the crack by using the obtained work area crack prediction variance attribute body of the set crack density interval and the structure interpretation horizon of the research group section.
2. The quantitative prediction method for post-stack seismic fractures according to claim 1, characterized in that step (3) specifically comprises:
i) selecting k fracture density values from the set fracture density interval, obtaining a group of time window lengths corresponding to the fracture density values in the k fracture density values according to the correlation process in the step (2), obtaining k groups of time window lengths together, establishing a relational expression which is satisfied by the variance body attribute values under the k groups of time window lengths, and determining m time window lengths used by the relational expression;
ii) respectively calculating variance bodies of the acquired post-stack seismic data bodies of the work area according to the m time window lengths determined in the step i) to obtain work area variance bodies under the m time window lengths;
and iii) extracting the variance body attribute values meeting the relation from the work area variance bodies with m time window lengths by using the relation formula which is jointly met by the variance body attribute values under the k groups of time window lengths, and obtaining the work area fracture prediction variance attribute body of the set fracture density interval.
3. The quantitative prediction method for the post-stack seismic fractures according to claim 1, characterized in that when the established depth domain velocity field is forward calculated, a grid-variable acoustic forward calculation method is adopted when the fracture unit dimension is smaller than meter level, and a conventional acoustic forward calculation method is adopted when the fracture unit dimension is at meter level and above.
4. A quantitative post-stack seismic fracture prediction system comprising a prediction module including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements a control process comprising:
(1) acquiring a post-stack seismic data volume of a work area, a structure interpretation horizon of a research group section, geology for describing crack development characteristics and logging information;
(2) simulating and establishing a relational expression between variance body attribute values under different time window lengths corresponding to the fracture zone with set fracture density, and calculating to obtain the work area variance body with set fracture density, wherein the step (2) specifically comprises the following steps:
1) establishing a depth domain velocity field of the set fracture density by using the geology and logging information of the research group section describing fracture development characteristics obtained in the step (1);
2) forward modeling and migration are carried out on the established depth domain velocity field, and a post-stack migration profile with set crack density is obtained;
3) extracting the variation t of seismic wave travel time corresponding to the positions containing the cracks and the positions not containing the cracks from the obtained post-stack migration profile;
4) taking n multiples nt of the variation t of seismic wave travel time corresponding to the extracted positions containing the cracks and the positions not containing the cracks as time window lengths for calculating a variance body, and respectively calculating the variance body of the post-stack migration section to obtain n time window lengths of the set crack density of the variance body section;
5) extracting variance body attribute values corresponding to a crack development area from the obtained variance body section with n time window lengths for setting the crack density, and establishing a relational expression between the variance body attribute values under the n time window lengths;
6) calculating the variance body of the work area post-stack seismic data body according to the time window length of the variance body obtained by calculation to obtain work area variance bodies with n time window lengths;
7) extracting variance body attribute values meeting the relation from the work area variance bodies with the n time window lengths by using the established relation among the variance body attribute values with the n time window lengths to obtain the work area variance body with the set crack density;
(3) calculating to obtain a work area crack prediction variance attribute body of a set crack density interval according to the step (2);
(4) and predicting the spatial distribution and the relative strength of the crack by using the obtained work area crack prediction variance attribute body of the set crack density interval and the structure interpretation horizon of the research group section.
5. The quantitative prediction system for post-stack seismic fractures according to claim 4, characterized in that step (3) specifically comprises:
i) selecting k fracture density values from the set fracture density interval, obtaining a group of time window lengths corresponding to the fracture density values in the k fracture density values according to the correlation process in the step (2), obtaining k groups of time window lengths together, establishing a relational expression which is satisfied by the variance body attribute values under the k groups of time window lengths, and determining m time window lengths used by the relational expression;
ii) respectively calculating variance bodies of the acquired post-stack seismic data bodies of the work area according to the m time window lengths determined in the step i) to obtain work area variance bodies under the m time window lengths;
and iii) extracting the variance body attribute values meeting the relation from the work area variance bodies with m time window lengths by using the relation formula which is jointly met by the variance body attribute values under the k groups of time window lengths, and obtaining the work area fracture prediction variance attribute body of the set fracture density interval.
6. The quantitative prediction system for post-stack seismic fractures according to claim 4, characterized in that when forward modeling is performed on the established depth domain velocity field, a grid-variable acoustic forward modeling method is adopted when the fracture unit dimension is smaller than meter level, and a conventional acoustic forward modeling method is adopted when the fracture unit dimension is at meter level and above.
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