Structure oriented filter seismic rokdoc

The structure of the strike-slip fault zone in Tarim Basin is complex, with large differences in the activities of main faults, development of branch faults, and distribution of cracks and cavities, resulting in poor identification of the fault zone by the original seismic data. The application results of real seismic data demonstrate the effectiveness of our method. This study proposed a new high-precision fault identification method for marine seismic data, which combines bin centralization, structure-oriented filtering, structure cube and image enhancement techniques based on LOG edge detection to suppress all kinds of interference and noise that affect fault identification, and finally improves the accuracy of fault identification. The traditional fault identification methods, such as coherence and curvature, are often difficult to meet the research needs. However, in Bohai Oilfield, with the research targets becoming more and more complicated, it is more and more difficult to identify the faults accurately. Location: 210A (Anaheim Convention Center)ДЄBSTRACT Accurate fault identification is a very important part of seismic data interpretation, which directly affects the result of structural interpretation.

Presentation Date: Wednesday, October 17, 2018 We obtain results that are comparable to more time-intensive interpreter picked faults and superior to results obtained using swarm intelligence algorithms We validate our fault attribute by using it as input to a commercial automatic fault extraction software. Since seismic data exhibits not only structural reflectors but also seismic noise, we propose a fault attribute workflow which contains footprint suppression, structure-oriented filtering, attribute computation, 'unconformity' suppression, and our new proposed iterative energy-weighted directional Laplacian of a Gaussian (LoG) operator. Seismic amplitude data exhibiting good resolution and a high signal-to-noise ratio are key to identifying structural discontinuities using coherence or other edge-detection attributes, which in turn serve as input for automatic fault extraction using image processing or machine learning techniques. Significant effort has been invested in accelerating seismic fault interpretation over the last three decades. That alignment requires prior estimates of east of Penglai 19-3 oilfield, achieved very good results.ДЄlong with horizon picking, fault identification and interpretation is one of the key components of successful seismic data interpretation. Thus, we can achieve some subtle strike-slip In contrast with conventional coherence, which detects faults and micro faults which cannot identified by discontinuities without distinction,this method to identify conventional methods.We use the proposed approach in the faults only.

combine structure oriented filtering with fault likelihood attribute. Therefore, the fault relatively poor in the region with inferior seismic data.We detection can be designed to detect the section surface propose a novel subtle strike-slip faults identification that element(Donias,2007).

The surface element corresponds to the most severe areas.The recognition effect of subtle strike-slip faults are surface of the gradient vector field. Additionally, interpreters can easily understand the trends of fault surfaces and automatically extract fault patches instead of creating fault surfaces individually and manually-significantly reducing conventional interpretation time.There are lots of methods to identify faults in seismic data, including If fault is a three-dimensional structure composed of coherence,variance, curvature,etc.These methods can meet multiple facets, each facet is approximate plane.The fault is the needs of faults identification in the early or relatively divided into several surface elements, and the integrity of simple areas of exploration, and the faults recognition effect the fault can be improved by the integration of the cross is poor in the late exploration and the complex structure section. Advanced edge detection and illumination attribute workflows (including ant tracking) can be used for enhanced structural delineation or as input to fracture modeling.

Structure oriented filter seismic rokdoc