Risk-constrained oil and gas resource spatial distribution forecasting method

A resource space and distribution prediction technology, applied in the field of risk-constrained oil and gas resource spatial distribution prediction

Active Publication Date: 2010-06-09
PETROCHINA CO LTD
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AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a risk-constrained method for predicting the spatial distribution of oil and gas resources, to solve the proble

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  • Risk-constrained oil and gas resource spatial distribution forecasting method
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  • Risk-constrained oil and gas resource spatial distribution forecasting method

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Embodiment Construction

[0047] Embodiments of the present invention will be further described in detail below in conjunction with application examples.

[0048] The application example area is Xujiaweizi Sag in Songliao Basin. The Xujiaweizi sag is divided into multiple positive structural units such as the western fault-step belt, the Xuzhong volcanic uplift belt, the eastern slope belt, the Fengle low uplift, and the Songzhan low uplift. After several years of rapid exploration, the Xujiaweizi Sag has become the sag with the highest degree of deep exploration and the most natural gas discovered in the Songliao Basin. The deep exploration area of ​​the sag is 5350km 2 , and basically realize the 3D seismic coverage of the whole region. As of 2007, 86 wells have been drilled, including 35 industrial gas flow wells and 28 low-yield gas flow wells. The proven geological reserves are 2663×10 8 m 3 . 16 gas reservoirs have been discovered, mainly distributed in Anda sub-sag in the north, Xudong slop...

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Abstract

The invention relates to a risk-constrained oil and gas resource spatial distribution forecasting method which comprises the following steps of: (1) integrating seismic information and geologic information; (2) forecasting the exploration risk probability of a entire region; (3) establishing a resource abundance diagram of the discovered oil and gas accumulation; (4) establishing a resource abundance amplitude diagram and a resource abundance phase diagram; (5) establishing a modified resource abundance amplitude diagram; (6) establishing a risk probability amplitude diagram and a risk probability phase diagram; (7) establishing a forecast oil and gas resource abundance distribution diagram of the entire region; and (8) calculating the resource quantities of different risk regions: excluding the oil and gas accumulation with low abundance; excluding grid data points with high exploration risk; and verifying and modifying according to the data of the explored wells. The method can forecast the resource quantities in different risk regions and the spatial distribution positions of the remained oil and gas resources. A forecasting model and the method have strong operability. The invention can enhance the drilling decision level and the oil and gas exploration efficiency.

Description

technical field [0001] The invention relates to a method for predicting the scale of oil and gas resources and its spatial distribution by using the probability of containing oil and gas and the abundance of oil and gas resources. Background technique [0002] Oil and gas resource scale assessment and spatial distribution prediction are the two core contents of oil and gas resource evaluation. Among them, in terms of scale assessment, the analogy method, the statistical method and the genetic method have all been developed and can be really put into application. In contrast, the research methods on the prediction of the spatial distribution of oil and gas resources are still immature, and there are few methods that can be put into practical use. At home and abroad, the oil and gas accumulation favorable analysis method is mainly used to qualitatively predict the spatial distribution of oil and gas in the play, and the quantitative prediction method is only the oil and gas s...

Claims

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Application Information

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IPC IPC(8): G01V11/00
Inventor 胡素云郭秋麟谢红兵米石云谌卓恒
Owner PETROCHINA CO LTD
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