CN108761535B - Method for identifying distribution of invaded rocks - Google Patents
Method for identifying distribution of invaded rocks Download PDFInfo
- Publication number
- CN108761535B CN108761535B CN201810895651.XA CN201810895651A CN108761535B CN 108761535 B CN108761535 B CN 108761535B CN 201810895651 A CN201810895651 A CN 201810895651A CN 108761535 B CN108761535 B CN 108761535B
- Authority
- CN
- China
- Prior art keywords
- invaded
- rock
- invaded rock
- wave field
- thickness
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 239000011435 rock Substances 0.000 title claims abstract description 121
- 238000000034 method Methods 0.000 title claims abstract description 18
- 238000004458 analytical method Methods 0.000 claims abstract description 22
- 238000005516 engineering process Methods 0.000 claims abstract description 11
- 238000005553 drilling Methods 0.000 claims description 6
- 238000000926 separation method Methods 0.000 claims description 5
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000012417 linear regression Methods 0.000 claims description 3
- 230000004044 response Effects 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 5
- 230000009545 invasion Effects 0.000 description 5
- 238000004088 simulation Methods 0.000 description 4
- 238000007796 conventional method Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/30—Analysis
- G01V1/306—Analysis for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/62—Physical property of subsurface
- G01V2210/624—Reservoir parameters
Landscapes
- Engineering & Computer Science (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Acoustics & Sound (AREA)
- Environmental & Geological Engineering (AREA)
- Geology (AREA)
- General Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Geophysics (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
The invention relates to a method for identifying distribution of invaded rocks, which comprises the following steps: wave field forward analysis is carried out to determine the reflection characteristics of the invaded rock; separating the invaded rock wave field by applying wavelet reconstruction technology; sensitive attribute analysis is carried out to determine the plane distribution of the invaded rock; and quantitatively predicting the thickness of the invaded rock. The method can accurately identify and depict the spatial distribution of the magma invaded rock under the conditions that the spatial distribution of the magma invaded rock is complex and the frequency of seismic data is low; the purpose of identifying the thickness of the thin layer invaded rock is achieved by establishing a quantitative relation between the sensitive attribute and the thickness of the invaded rock.
Description
Technical Field
The invention relates to a method for identifying the spatial distribution of invaded magmatic rocks in the field of oil exploration, in particular to a method for identifying the distribution of invaded rocks under the conditions of low seismic data frequency and complex spatial distribution of magmatic invaded rocks.
Background
The conventional rock pulp invasion rock carving method can successfully carve the plane distribution range of the invasion rock and can realize the thickness prediction of the invasion rock. However, when the distribution of the invaded rocks is complex, the physical properties of the rocks are close to those of the surrounding rocks, and the frequency of seismic data is low, the ambiguity of identifying the invaded rocks by the conventional method is increased, and the prediction of the thickness of the invaded rocks is difficult to realize. On the other hand, the purpose of reducing the prediction multi-solution can be achieved through simple combination of multiple methods, but the improvement effect is limited, and effective identification of the spatial distribution rule of the thin layer invaded rock cannot be completed. These problems make the conventional method difficult to identify the invaded rock space under complex conditions.
Disclosure of Invention
In view of the above problems, an object of the present invention is to provide a method for identifying invaded rock distribution, which can accurately identify and depict the spatial distribution of the magma invaded rock under the conditions that the spatial distribution of the magma invaded rock is complex and the frequency of seismic data is low.
In order to achieve the purpose, the invention adopts the following technical scheme: a method of identifying the distribution of invaded rocks comprising the steps of: 1) wave field forward analysis is carried out to determine the reflection characteristics of the invaded rock; 2) separating the invaded rock wave field by applying wavelet reconstruction technology; 3) sensitive attribute analysis is carried out to determine the plane distribution of the invaded rock; 4) and quantitatively predicting the thickness of the invaded rock.
Further, in the step 1), the reflected wave field characteristics of the invaded rock at the known position are determined by performing forward analysis on the two-dimensional typical seismic profile and forward results of the one-dimensional single-well wave equation.
Further, in the step 2), according to a wave field forward result, a wavelet reconstruction technology is applied to separate the reflected wave field of the invaded rock on a specific scale, and finally a seismic data body which is consistent with the forward result and can reflect the characteristics of the invaded rock is obtained.
Further, the separation process is as follows: and searching seismic data wave fields of different scales by combining the characteristics of the invaded rock reflection wave field, selecting one or more scales of seismic wave field data capable of reflecting the invaded rock wave field information to obtain seismic data bodies capable of reflecting the characteristics of the thin-layer invaded rock wave field in the reservoir, and further reconstructing the seismic data bodies.
Further, in the step 3), according to the reflection wave field characteristics of the invaded rock at the known position determined in the step 1), sensitive attribute analysis is performed on the seismic data volume obtained in the step 2), so that the plane distribution of the invaded rock is determined.
Further, the sensitive attribute analysis specifically includes: determining the difference between the reflected wave field characteristics of the invaded rock and a surrounding rock reservoir through the forward modeling analysis of the two-dimensional typical seismic profile in the step 1) and the forward modeling result of the one-dimensional single-well wave equation, performing trial calculation on the seismic data obtained in the step 2), selecting the negative amplitude attribute which can best meet the difference, the hard constraint and the condition as the sensitive attribute according to the actual drilling result and the geological knowledge of the invaded rock distribution, and analyzing the plane distribution of the invaded rock.
Further, in the step 4), a quantitative relation between the thickness of the invaded rock and the negative amplitude attribute is established based on the negative amplitude attribute which is the sensitive attribute selected from the seismic data volume obtained by the wavelet reconstruction technology, so that the thickness distribution of the invaded rock is determined.
Further, the thickness distribution of the invaded rock is specifically as follows: based on the sensitivity attribute and the negative amplitude attribute selected by the seismic data volume obtained by the wavelet reconstruction technology in the step 2), quantitatively analyzing the response characteristics of the negative amplitude attribute of the invaded rock with different thicknesses by a linear regression method through the thickness of the invaded rock encountered by partial drilling and the negative amplitude attribute prediction result of the well point position, and determining that the invaded rock thickness and the maximum negative amplitude value have a good linear relation in the quantitative relation between the maximum negative amplitude attribute and the invaded rock thickness within the invaded rock thickness range of 0-100m, and the correlation coefficient can reach 0.91; based on the thickness, the thickness of the invaded rock determined in the step 3) is calculated, so that the thickness distribution of the invaded rock is obtained.
Due to the adoption of the technical scheme, the invention has the following advantages: 1. the method can comprehensively restrict and extract and identify the space distribution of the invaded rocks by multiple methods under the condition that the distribution of the magma invaded rocks is complex. 2. The invention realizes the purpose of identifying the thickness of the thin layer invaded rock by establishing the quantitative relation between the sensitive attribute and the thickness of the invaded rock.
Drawings
FIG. 1 is a schematic overall flow diagram of the present invention;
FIG. 2a is a schematic diagram of a forward modeling model of seismic reflection characteristics of an invaded rock;
FIG. 2b is a schematic representation of a forward cross section of the seismic reflection signature of the invaded rock;
FIG. 3 is a schematic diagram of a single well wave equation forward simulation;
FIG. 4a is a diagram showing the separation result of the wavelet reconstructed wave field of the seismic profile wavelet;
FIG. 4b is a diagram showing the separation result of the reconstructed profile wavelet field;
fig. 5 is a plot of invaded rock thickness versus maximum negative amplitude.
Detailed Description
The invention is described in detail below with reference to the figures and examples.
As shown in fig. 1, the present invention provides a method for identifying distribution of invaded rocks, which comprises the following steps:
1) wave field forward analysis is carried out to determine the reflection characteristics of the invaded rock;
by performing forward analysis of a two-dimensional typical seismic profile and forward results of a one-dimensional single-well wave equation, the reflected wavefield characteristics of the invaded rock at a known location can be determined.
In this embodiment, a complex case where a thin layer invades the near-formation top boundary of rock is taken as an example for explanation. Through two-dimensional forward modeling results (as shown in fig. 2a and fig. 2 b), it can be found that the reflection characteristics of the invaded rock are totally annihilated in the sidelobe of the high amplitude at the top of the reservoir, and no obvious interface characteristics exist. It has also been found that invaded rock results in about a 40% increase in amplitude and the formation has a tendency to thicken. In addition, a one-dimensional wave equation simulation analysis is performed on the known well by a full wave field seismic simulation technique. The simulation results show (as shown in fig. 3) that the presence of invaded rocks significantly enhances the seismic amplitude. But the enhancement percentage is not the same for positive and negative amplitudes. The presence of invaded rocks enhanced the positive amplitude by about 30% while the negative amplitude was enhanced by 70%.
2) And (3) separating the invaded rock wave field by applying wavelet reconstruction technology.
And according to the forward result of the wave field, separating the seismic wave field of the invaded rock on a specific scale by applying a wavelet reconstruction technology, and finally obtaining a seismic data body which is consistent with the forward result and can reflect the characteristics of the invaded rock.
In this example, the separation process is described by taking the complex case of thin layer invasion into the near reservoir top interface as an example:
by applying wavelet transform method, multiple sets of seismic data bodies can be separated from wavelets of different scales. And (2) searching seismic data wave fields of different scales by combining the characteristics of the invaded rock reflection wave field in the step 1), optimizing one or more scales of seismic wave field data capable of reflecting the information of the invaded rock wave field to obtain seismic data bodies capable of reflecting the characteristics of the thin layer invaded rock wave field in the reservoir, and further reconstructing the seismic data bodies. Wavelet reconstruction techniques successfully separate the reflected wavefield from the invaded rock from the wavefield at the top-of-formation interface, with the spatial location of the invaded rock in good agreement with known wells (see fig. 4a, 4 b).
3) Sensitive property analysis to determine planar distribution of invaded rock
According to the reflection characteristics of the invaded rock determined in the step 1), sensitive attribute analysis is carried out on the data body obtained in the step 2), and therefore the plane distribution of the invaded rock is determined.
In this embodiment, the sensitive property analysis is described by taking the complex case of invasion of a thin layer into the top interface of a near reservoir as an example:
determining the difference (generally, but not limited to the analysis of amplitude, frequency, phase and structure type attributes) between the wave field characteristics of the invaded rock and the surrounding rock reservoir through the forward analysis result in the step 1), performing trial calculation on the seismic data volume obtained in the step 2), and preferably selecting the seismic wave field attributes which can best meet the two conditions according to the actual drilling result as hard constraint and the geological knowledge of the invaded rock distribution and finally preferably predicting the plane distribution of the invaded rock by using the negative amplitude attribute.
4) Quantitatively predicting the thickness of the invaded rock;
establishing a quantitative relation between the thickness of the invaded rock and the sensitive attribute according to the sensitive attribute selected by the seismic data obtained by the wavelet reconstruction technology in the step 2) and the forward result of the forward one-dimensional single-well wave equation in the step 1), thereby determining the thickness distribution of the invaded rock.
In this embodiment, a complex case where a thin layer invades into the top interface of the near reservoir will be described as an example. From the forward results given by the well data, it was determined that the presence of invaded rock had a greater effect on the reflected wavefield negative amplitude. Therefore, sensitive attributes are selected based on wavelet reconstruction data in the step 2), response characteristics of the negative amplitude attributes of the invaded rocks with different thicknesses are quantitatively analyzed through the prediction results of the thicknesses of the invaded rocks encountered by partial drilling and the negative amplitude attributes of the well point positions by a linear regression method, and in the quantitative relation between the maximum negative amplitude attributes and the thickness of the invaded rocks, the thickness of the invaded rocks and the maximum negative amplitude values have a good linear relation within the thickness range of the invaded rocks of 0-100m, and the correlation coefficient can reach 0.91 (as shown in fig. 5). Based on this, the thickness of the invaded rock determined in step 3) can be calculated, thereby obtaining the spatial distribution of the invaded rock.
The above embodiments are only for illustrating the present invention, and the structure, size, arrangement position and shape of each component can be changed, and on the basis of the technical scheme of the present invention, the improvement and equivalent transformation of the individual components according to the principle of the present invention should not be excluded from the protection scope of the present invention.
Claims (2)
1. A method of identifying the distribution of invaded rocks, comprising the steps of:
1) wave field forward analysis is carried out to determine the characteristics of the reflection wave field of the invaded rock;
determining the characteristics of the reflection wave field of the invaded rock at the known position by performing forward analysis on a two-dimensional typical seismic profile and forward results of a one-dimensional single-well wave equation;
2) according to the forward analysis of the two-dimensional typical seismic profile and the forward result of the one-dimensional single-well wave equation, separating the invaded rock reflected wave field on a specific scale by applying a wavelet reconstruction technology, and finally obtaining a seismic data volume which is consistent with the forward result and can reflect the invaded rock characteristics;
3) determining the planar distribution of the invaded rock: according to the characteristics of the reflection wave field of the invaded rock at the known position determined in the step 1), performing sensitive attribute analysis on the seismic data obtained in the step 2), and determining the plane distribution of the invaded rock; the sensitive attribute analysis specifically comprises the following steps:
determining the difference between the characteristics of a reflected wave field of the invaded rock and a surrounding rock reservoir through the forward analysis of the two-dimensional typical seismic profile in the step 1) and the forward result of the one-dimensional single-well wave equation, performing trial calculation on the seismic data obtained in the step 2), selecting a negative amplitude attribute which can best meet the difference, the hard constraint and the condition as a sensitive attribute according to the actual drilling result and the geological knowledge of the invaded rock distribution, and analyzing the plane distribution of the invaded rock;
4) quantitative prediction of invaded rock thickness distribution:
establishing a quantitative relation between the thickness of the invaded rock and the negative amplitude attribute based on the sensitive attribute selected by the seismic data volume obtained by the wavelet reconstruction technology, namely the negative amplitude attribute, so as to determine the thickness distribution of the invaded rock;
the thickness distribution of the invaded rock is specifically as follows: based on the sensitive attribute, namely the negative amplitude attribute, selected from the seismic data volume obtained by the wavelet reconstruction technology in the step 2), quantitatively analyzing the thickness of the invaded rock encountered by partial drilling and the negative amplitude attribute prediction result of the well point position by a linear regression method, and quantitatively analyzing the negative amplitude attribute response characteristics of the invaded rock with different thicknesses, wherein the thickness of the invaded rock and the maximum negative amplitude value have a good linear relation in the invaded rock thickness range of 0-100m, and the correlation coefficient is 0.91; then, based on this, the thickness of the invaded rock determined in step 3) is calculated, thereby obtaining the thickness distribution of the invaded rock.
2. The method of claim 1, wherein: the separation process comprises the following steps: and searching seismic data wave fields of different scales by combining the characteristics of the invaded rock reflection wave field, selecting one or more scales of seismic wave field data reflecting the information of the invaded rock wave field to obtain seismic data bodies reflecting the characteristics of the thin-layer invaded rock wave field in the reservoir, and further reconstructing the seismic data bodies.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810895651.XA CN108761535B (en) | 2018-08-08 | 2018-08-08 | Method for identifying distribution of invaded rocks |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810895651.XA CN108761535B (en) | 2018-08-08 | 2018-08-08 | Method for identifying distribution of invaded rocks |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108761535A CN108761535A (en) | 2018-11-06 |
| CN108761535B true CN108761535B (en) | 2020-04-07 |
Family
ID=63969302
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810895651.XA Active CN108761535B (en) | 2018-08-08 | 2018-08-08 | Method for identifying distribution of invaded rocks |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108761535B (en) |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002369933A (en) * | 2001-06-13 | 2002-12-24 | Takao:Kk | Pachinko game machine |
| CN1595107A (en) * | 2004-06-29 | 2005-03-16 | 中国国土资源航空物探遥感中心 | Multiple optical spectrum alteration zoning method based on wavelet packet variation |
| US20080232193A1 (en) * | 2007-03-20 | 2008-09-25 | Geocyber Solutions, Inc. | Methods for Noise Removal and/or Attenuation from Seismic Data by Wavelet Selection |
| CN104280770B (en) * | 2014-09-28 | 2017-01-11 | 中国石油大港油田勘探开发研究院 | Prediction method of compact transition rock reservoir stratum |
| CN108226999A (en) * | 2018-01-19 | 2018-06-29 | 中国石油化工股份有限公司 | The processing method of the small scale fracture hole body information of carbonate rock |
-
2018
- 2018-08-08 CN CN201810895651.XA patent/CN108761535B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN108761535A (en) | 2018-11-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Huang et al. | Mathematical morphological filtering for linear noise attenuation of seismic data | |
| US9348056B2 (en) | Image-based direct numerical simulation of petrophysical properties under simulated stress and strain conditions | |
| Bekara et al. | Random and coherent noise attenuation by empirical mode decomposition | |
| Lu et al. | Seismic spectral decomposition using deconvolutive short-time Fourier transform spectrogram | |
| US9261613B2 (en) | Passive monitoring method for seismic events | |
| EP3631523B1 (en) | System and method for predicting fault seal from seismic data | |
| US10436924B2 (en) | Denoising seismic data | |
| CN104237945B (en) | A kind of seismic data self adaptation high resolution processing method | |
| EP3158368B1 (en) | Instantaneous isochron attribute-based geobody identification for reservoir modeling | |
| EP3631524B1 (en) | System and method for predicting fault seal from seismic data | |
| WO2017136133A1 (en) | Efficient seismic attribute gather generation with data synthesis and expectation method | |
| CN106291682A (en) | A kind of poststack sound impedance inversion method based on base method for tracing | |
| Hernandez-Martinez et al. | Facies recognition using multifractal Hurst analysis: Applications to well-log data | |
| Li et al. | Automatic fracture–vug identification and extraction from electric imaging logging data based on path morphology | |
| CN108254785B (en) | Reservoir determination method and device | |
| US20220120933A1 (en) | Method of detection of hydrocarbon horizontal slippage passages | |
| RU2746691C1 (en) | System for intelligent identification of tectonic faults with the help of seismic data on the basis of convolutional neural networks | |
| CN112711068B (en) | Method and device for predicting effective reservoir of oil gas in sandstone | |
| CN111257933B (en) | Novel method for predicting oil and gas reservoir based on low-frequency shadow phenomenon | |
| CN108761535B (en) | Method for identifying distribution of invaded rocks | |
| Lomask | Seismic volumetric flattening and segmentation | |
| CN111239823A (en) | Method for identifying distribution of invaded rocks | |
| CN116027454A (en) | Method for imaging contour map of sandstone thickness and intelligent drawing device | |
| CN113589365B (en) | Reservoir pinch-out line description method based on time-frequency domain information | |
| Ye et al. | Rapid and Consistent Identification of Stratigraphic Boundaries and Stacking Patterns in Well Logs-An Automated Process Utilizing Wavelet Transforms and Beta Distributions |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |