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Traditional Classical Fault Identification (Ⅱ) —— Mutation and Ant Tracking (with software)

The basis of seismic variance volume attribute is error analysis, which mainly describes geological structure data through the similarity attribute of adjacent seismic signals. It has achieved good application results in seismic trace feature description and reservoir distribution. Therefore, the seismic variance volume attribute can be applied to structural interpretation. Because the accuracy of structural interpretation is getting higher and higher, the discontinuous relationship between faults and folds between geological structures can be expressed based on seismic variance volume attributes.

Cracks in the actual stratum will lead to abnormal amplitude characteristics between the sampling points in the corresponding position in the seismic data volume and the sampling points in the surrounding area. At this time, the crack points are highlighted by calculating the variance between sampling points in a certain range to identify cracks. As shown in the figure, there are n seismic data in the window, with the sampling point in the middle of the window as the seed point. The specific steps to calculate the variance of this point are as follows: 1) Take half of the sampling points in the upper and lower parts of the window, and first calculate the average amplitude values of all sampling points in each of the N seismic data in the window; 2) simultaneously calculating the sum of the variance of the amplitude value and the amplitude average value of each sampling point and n paths of data; 3) Multiply by the weighting coefficient and normalize to get the variance value of this point. Move the window and iterate steps 1, 2, 3 to get the variance value of each sampling point in the whole work area data volume and get the variance volume.

From the figure, we can get the formula for calculating the volume property of variance:

Commonly used volume attributes include coherent volume, variance volume and curvature volume attributes. The utilization of various body attributes is mainly based on their horizon attributes along the stratum. The algorithm of each software is inconsistent, and the result of the same attribute is also different. As can be seen from the following figure, the variance attribute of Geoframe software, the variance attribute and the coherence attribute of VVA software are all effective, and the collapse column anomalies are clearly reflected, with large and small ones, showing circular or semi-circular traps on stratigraphic slices. The curvature attribute effect of VVA software is poor. Although the collapse column is shown above, it is very disturbing and not as obvious and intuitive as other attributes.

Ant body tracking technology is based on ant colony algorithm to track and identify fractures. The principle of the algorithm is to simulate ants looking for the shortest path between food and their nests according to the pheromone concentration that can attract ants. In seismic data, "ants" move along possible faults and cracks according to the differences in amplitude and phase to describe them.

At the beginning of 2 1 century, ant tracking technology began to be widely used in fault system interpretation. At present, this technology has been successfully applied to the fine interpretation of petroleum seismic data and achieved good results. Ant tracking interpretation technology has the advantages of rapidity, intuition, high accuracy and objectivity. In order to make the seismic attribute identification of small faults more obvious and the interpretation accuracy higher. On the basis of constructing directional filtering, ant tracking calculation is carried out on the data, and finally sensitive attributes are extracted according to attribute optimization. That is, through "ant"+attribute fusion (including "ant"+variance attribute, "ant"+coherence attribute, "ant"+Lambert reflection attribute, "ant"+inclination attribute, "ant"+instantaneous amplitude attribute and "ant"+instantaneous frequency attribute), then the sensitive attributes are optimized for fine structural interpretation.

Compared with the coherent attribute (as shown in the figure), the advantage of ant body attribute is that it highlights the linear structural characteristics of faults, removes information unrelated to faults, and improves the accuracy of fault interpretation. The disadvantage is that the plane prediction results are often too chaotic and irregular. One of the reasons is that there are too many parameters to control the tracking results of ants, which are difficult to adjust.

Ant tracking technology is based on post-stack seismic data. Although its accuracy is higher than coherence, it is only suitable for predicting small faults and large-scale fractures. The fracture development direction can be predicted, but it is difficult to quantitatively characterize the fracture development density.

Next, we use real data to demonstrate the operation methods of variance body and ant tracking.

Let me talk about the selection of data first. This time, we used the 1996 prestack data of Taranaki basin in New Zealand. This data appears in many experts' papers. The data is summarized as follows:

The data size is 287*735* 1252.

Next, we use the software Petrel for processing.

1. Create new project and import data

Select New Project, and then in the Home Folder column, select New Earthquake Home Folder.

Right-click-create a new seismic survey in the tree structure, and the project is completed.

Right-click Survey 1, select Import (on selection), select data volume Kerry3D.segy, and click OK directly in the pop-up parameter box to load data.

By creating a new 3D window, you can view an overview of the data.

2. Variance body

(1) is implemented.

Right-click the seismic signal and select Implemented ... Click Implemented in the dialog box to close the window, which simplifies the original data and reduces some details.

(2) Variance body

Click the realized data volume, and click the volume attribute in seismic interpretation to configure:

The result is this:

If you feel that there is more interference, you can smooth the data volume first, and then do the variance. Smoothing is to choose such parameters:

The final processing result is as follows:

3. Ant tracking

Select the variance volume data just processed, and click the "Volume Attribute" button in seismic interpretation to configure:

The result after processing is like this. Compared with variance volume, the resolution of fault identification is further improved.

Ant tracking can also be processed on different data volume results, so you can try it yourself.

There are many parameter configuration methods for ant tracking.

First of all, in parameter configuration, you can choose active or passive. Generally, major faults are passively identified, while minor faults are actively identified. You can also take the initiative first and then superimpose the passivity. This can remove many invalid recognition results.

The second is to filter signals that are not tracked. Where the circle represents the azimuth of the fault, the dip angle is the dip angle, and the azimuth angle is the azimuth angle. The blackened part is a fault that is not traced. For example, the innermost layer represents a horizontal fault and is generally not traced.

You can choose not to trace the fault according to the actual situation of the work area.

For example, faults mainly look at the north-south direction, so the east-west direction is blackened, and generally the outer layer is not blackened (because of the large dip angle in the north-south direction). As shown in the figure below:

or

This is today's lesson. This lesson explains two commonly used automatic fault identification methods, including principle and actual case operation. If you are interested in the software or have any questions, you can contact me to communicate. Goodbye.

Extended reading:

How to easily introduce seismic exploration research: first, start with seismic data processing.

How to open the road of earthquake depth learning and scientific research from 0