Volcanic Rock Identification Technique Based On Local Seismic Attributes

With the deepening of oil and gas exploration and development, unconventionaloil and gas resources is becoming an important part of the national oil and gasstrategy, the volcanic reservoirs in China has great potential for oil generation,especially in the northeast of Songliao Basin, volcanic rocks are widely developed,and how effective to identify the volcanic reservoir is significant. Volcanic reservoirexploration and development began in the1970s, the rapid development appeared inthe late1990s. At present, most major oil and gas basin interior show the reservoir ofvolcanic rocks or volcanic rocks.In today’s oil and gas exploration process, the description of the volcanic rockreservoirs is aiming at the favorable reservoir and gas-bearing properties forecasts.Describing on the volcanic rock reservoir is based on the identification of the volcanicrocks, volcanic strata of recognition is an important research focus. Therefore,according to the volcanic rock reservoir, using a variety of geophysical methods tocarry out the volcanic reservoir identification and prediction has important practicalmeaning. Because the volcanic reservoir lithology and inherent reservoir space isextremely complex, the prediction of volcanic rock reservoirs is very difficult.Seismic attribute is an effective reservoir characterization tool and is the keyparameter for study of the spatial distribution of volcanic rocks. The local seismicfrequency, local seismic dip, local curvature of event, and other properties aresensitive features to identify the volcanic rocks in seismic data.In this study, the author proposes to use local seismic attributes for theidentification of volcanic rocks. First of all, I consider the instantaneous frequencywhich always shows a large number of negative frequency values in the section, it isobviously unreasonable. Thus I introduce the local frequency. Local frequencydetermine the smoothing radius by shaping regularization, smooth radius is only oneparameter that can constrain the underdetermined problem.I used plane-wave destruction filters (PWD) to calculate local dip and deducedthe approximate local curvature of event by using local dip. Numerical tests show thatthe local curvature of event can be a good approximation of the true value and has high accuracy.By computing the local frequency of the actual seismic profiles, I draw thelow-frequency region from the body of the local frequency data. I also calculated thecurvature of the same profile and get the high curvature region. The two attributes byusing overlay display can identify the distribution of volcanic body and furtherprovided the guidance for the identification of the volcanic reservoir.Cross plot between the different seismic attributes, including the instantaneousamplitude, the local frequency, local phase, and local dip, was developed to find therelationship between two different attributes. However, the results show that, in thecrossplot map, there is no clear trend for guidance of the volcanic reservoir prediction.