A Step-by-Step Seismic Facies Prediction Method for Fluvial Reservoirs Based on Geological Information Constraints
A prediction method and technology of seismic facies, applied in seismic survey, seismology, geophysical survey, etc., can solve problems such as slow convergence speed, inaccurate classification, and large calculation time.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Publication Date
- 2018-12-18
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Abstract
Description
technical field
[0001] The invention relates to the field of earthquake prediction, in particular to a step-by-step seismic facies prediction method for fluvial facies reservoirs based on geological information constraints. Background technique
[0002] Today, the oil exploration industry effectively utilizes modern science and technology, thus promoting the rapid development of the oil industry and bringing huge benefits to the national economy. However, with the continuous improvement of oil exploration level, it is more and more difficult to find new oil and gas fields. This requires people to continuously improve their understanding and use scientific methods to understand and grasp the unknown conditions of oil and gas existence. More new information is excavated from data such as , oil reservoir development, etc. to predict oil and gas.
[0003] In this process, the study of sedimentary facies is of great significance. It can not only analyze sedimentary microfacies a...
Examples
Embodiment 1
[0066] A step-by-step seismic facies prediction method for fluvial facies reservoirs based on geological information constraints, comprising the following steps:
[0067] Step 1: Evaluation of geological data; including the evaluation of geological, logging and seismic data; the evaluation of geological data is to understand the geological situation of the fluvial facies work area, and to have an understanding of its sedimentary evolution history and lithology data. After fully evaluating these data After that, the geological information knowledge base can be established; the evaluation of logging data is mainly to understand and count the logging response characteristics and reservoir parameters of each well in the target interval; the evaluation of seismic data is mainly to pick up the signal-to-noise ratio and resolution of the data, To determine the general trend of reservoir characteristics that can be reflected by the subsequent seismic attributes and the minimum stratum ...