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Volcanic lithofacies prediction method

A prediction method and technology of volcanic rocks, applied in the geophysical field of petroleum exploration and development, can solve the problems of large drilling plane distribution restrictions, unclear distribution of volcanic rock facies belts, and difficulty in distinguishing changes in volcanic rock lithofacies belts, etc., to improve pertinence , improved prediction accuracy, good effect

Inactive Publication Date: 2020-06-05
LIAONING TECHNICAL UNIVERSITY
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Problems solved by technology

[0005] When the volcanic lithofacies change rapidly, the seismic reflection characteristics of different volcanic lithofacies are similar, and conventional seismic attributes are not clear about the distribution of volcanic lithofacies. The distribution prediction of volcanic rocks is mainly based on geology, drilling, logging, mud logging, etc Therefore, the prediction of the spatial distribution of volcanic rocks also requires the use of seismic prediction methods. Seismic attribute prediction is one of the methods. However, conventional single-seismic attribute analysis is difficult to distinguish volcanic rocks. Therefore, there is an urgent need for a well-seismic combination prediction method for volcanic lithofacies

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Embodiment 1

[0043] as attached figure 1As shown, firstly, according to the logging data of typical wells, the velocity of volcanic rock is 3330-4167 m / s, and the thickness is 30-85 meters. The forward modeling models of several typical wells were established according to the thickness and velocity of volcanic rocks in all typical wells and the drilling conditions of overlying and underlying surrounding rock formations. The Ricker wavelet of 20 Hz is selected to simulate the seismic reflection records through forward modeling. By comparing with the seismic reflection records of the actual shaft bypass, and combining the amplitude and frequency attributes calculated by the model, the seismic reflection characteristics of different volcanic lithofacies belts can be analyzed Through comparison, it can be found that the seismic reflection characteristics of high-quality thick-bed effusive facies volcanic rocks such as Well Z1508 are strong peaks, high frequencies, complex wave troughs, and lon...

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Abstract

The invention relates to the technical field of petroleum exploration and development geophysics, in particular to a volcanic lithofacies prediction method. The method comprises the following steps: (1) model forward modeling; (2) seismic attribute extraction; (3) attribute optimization; (4) volcanic rock facies classification; (5) recognizing a multi-attribute neural network mode; and (6) lithofacies prediction. The method has the advantages that the defect that single seismic attributes can only partially reflect lithologic combination differences is overcome, and the spatial distribution ofvolcanic facies can be effectively predicted.

Description

[0001] (1) Technical field [0002] The invention relates to the technical field of petroleum exploration and development geophysics, in particular to a prediction method of volcanic rock facies. [0003] (2) Background technology [0004] In recent years, with the gradual deepening of oil and gas exploration in unconventional reservoirs, volcanic rocks have gradually become a new research hotspot in reservoir prediction; volcanic rock oil and gas reservoirs are very complicated. Volcanic rock oil and gas reservoirs were first discovered in the United States in 1987. So far, volcanic rock oil and gas reserves in the world Mainly concentrated in the United States, Russia, Cuba and some countries in Eastern Europe. In recent years, China has begun to pay attention to volcanic oil and gas reservoirs, and some reserves have been explored successively; Dagang Oilfield has also been discovered, but the overall exploration and development and related research are still in the preparat...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01V1/30
CPCG01V1/306
Inventor 邢杰
Owner LIAONING TECHNICAL UNIVERSITY
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