Seismic Attribute Analysis Technology In The Application Of Ld Turbidite Fan In Recognition

LD region is located at the end of the Liaodong structural salient, which is also at the south part of the Middle Liaozhong concave. The trending of palaeogeomorphology of LD region is high at Northeast and low at Southwest under the affection of the Liaodong structural salient. The sedimentary process was controlled by the conformation system, contributing to building thick sedimentary rock in the concave. The growing of LD structural zone was mainly controlled by the ancient river system of Changxing island, developed to bathyal-deep sea sedimentary system. Under the control of the sedimentary break, along with the river system, massive depositions were fast accumulated and landslide on the break result in formation of the turbidite fan. In the strata of Tertiary syetem named Dongying formation, there exist multi kinds of underwater turbidite fan. Generally, these multi kinds of turbidite fans are close to the hydrocarbon source rocks in group. They are usually considered as potential exploration areas with their advantage environment for reservoir-cap, especially when the turbidite fan in deep sea and the landsliding is the crucial place for the subtle reservoir. Due to the deep depth of the reservoir-cap and few available exploration wells, the study of these multi turbidite fan could only study through the seismic data. By research on the seismic data of LD region, two turbidites with different geometric shape were found on the direction of the cross line. One shape is lentiform, another is cuneal. This article study the geologic feature and the distinction on the seismic profile of these turbidite fan. However, the direction of the internal waterway and the border of the turbidite fan still uncertain. After extract multi kinds of seismic attribute on LD region, this article do a preprocessing on the seismic attribute in order to eliminate the abnormal phenomenon causing by the nongeologic factors. Combining with the abnormal area on the attribute map,12kinds of sensitive attributes have been selected and studied in both the physical and geologic way which are corresponded to the identification of Hackberry. First, the sensitive attributes are classified through the fuzzy self-organizing neural network way in order to group the seismic faces. Second, it utilizes the K_L conversion for extract the principal component of the sensitive attributes group. The Last part, the principal component will be process by the mixing the RGB together and the results coming from the fuzzy self-organizing neural network in order to interfusion with the main component of the K_L conversion. These results could be help to confirm the border, the internal waterway and the direction of the original resouces of the turbidite fan. The study could be play a fundamental and guidance role in the future studies and analysis on the deep turbidite fan reservoir rocks in the other part of this area.