油气资源丰度模拟方法研究与应用
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摘要
近些年来,油气资源评价工作逐渐从评价油气资源的规模向定量预测其空间分布、从单一的资源评价向资源与目标一体化评价的方向发展;油气勘探开发领域不断扩大,从传统的寻找构造油气藏为主逐步进入到构造油气藏与岩性地层油气藏并重,从常规资源延伸至非常规资源,从常规单一闭合圈闭油气藏扩展到连续型非常规圈闭油气藏;国内外,尤其是我国油气勘探高丰度的富集区块越来越少,勘探领域日趋转向低孔渗低丰度油气区。传统的资源评价方法已难以满足快速发展的油气勘探需要,发展更多适用、实用的新方法技术成为资源评价领域的研究热点。
本论文的研究目的是形成油气资源丰度模拟的方法技术和实用流程,并研发一套油气资源丰度模拟软件模块。通过方法和软件模块的实际应用,定量预测油气的空间分布位置和规模大小,为资源评价技术的进一步发展与更新换代进行开拓性探索。
预测油气资源的空间分布包含两方面的内容,一是油气可能存在的位置,二是在该位置上油气的聚集量大小。论文从这两点出发,首先统计分析了油气规模、油气资源丰度的分形特征;接着探讨了油气资源在空间展布上的分形特征,以及从成藏机理和空间数据分析进行油气分布位置研究的方法;然后基于油气资源的分形特征和傅立叶变换能实现空间域与频率域互相转换的特性,通过分形模型、傅立叶变换、频谱模拟、条件模拟等模型和技术,研究将油气规模特征与空间位置特征进行综合分析的手段,以及通过勘探风险、经济界限等对资源丰度模拟过程进行约束和修正的方法。最后通过松辽盆地北部古龙凹陷葡萄花致密油层、肇州-朝阳沟地区大面积低丰度分布的扶余油层的应用研究,详细叙述了方法的应用流程和效果。
论文建立了一套油气资源丰度模拟的方法体系和应用流程,填补了国内在油气资源空间分布研究领域的空白;研制出可满足油气勘探实践需要的油气资源丰度模拟软件模块。应用研究表明方法对非常规资源评价及在低丰度区寻找相对高丰度“甜点”具有可行性;针对大面积低丰度分布的非常规储层油气的评价取得了较好的效果。
In recent years, petroleum resource assessment is being developed from the evaluation of resources scale to quantitative prediction of their spatial distribution, and from resource evaluation to integration of resources and target evaluation. Petroleum exploration and development have expanded gradually from just traditional structural reservoirs to lithologic and stratigraphic reservoirs as important as structural reservoirs, from conventional to unconventional resources, and from the conventional closure traps to continuous reservoirs. Blocks with higher abundance are becoming less and less in all around the world, especially in China. Exploration domains are increasingly turning to low porosity, low permeability and lower abundance resources. Traditional methods of resource assessment have been difficult to meet the needs of rapid development of petroleum exploration. Developing more suitable, practical new methods has become the hot topic in the field of petroleum resource assessment.
The purpose of this paper is to develop methods, technologies and practical process of simulation of petroleum resources abundance, and to develop software modules of the simulation. Through the methods and their application, we want to predict quantitatively the spatial distribution of petroleum resource, and to make pioneering research and upgrading for the further development of petroleum resource assessment.
Prediction of petroleum resources spatial distribution contains two parts, one is the position that resource may exist, and the other is accumulation size in the position. Starting from these 2 points, we give statistical analysis of fractal characteristics of the scale of resource and resources abundance firstly. Secondly we discuss fractal characteristics of resources spatial distribution, and methods to study petroleum distribution through accumulation mechanism and spatial data analysis. Thirdly we propose the methods of simulation of petroleum resources abundance based on fractal characteristics of petroleum resources and Fourier Transform, which can convert information from space domain to frequency domain, or the other way round. The methods work through fractal model, Fourier Transform, spectrum simulation, and conditional simulation. We also study on the methods making comprehensive analysis on characteristics of petroleum scale and spatial location, and methods giving constraints and correction for the simulation of process by exploration risk, economic limit, etc. Lastly we demonstrate in details the process of the method and its effects through application on tight reservoirs of Putaohua in Gulong Sag, low abundance reservoirs of Fuyu in Zhaozhou - Chaoyanggou, northern part of Songliao Basin.
The paper establishes methods for and application process for petroleum resources abundance, which has filled domestic gap in the field of petroleum resources spatial distribution. It also develops software modules for simulation of petroleum resources abundance that meet the needs of petroleum exploration practice. The application proves there have possibilities using such method to evaluate unconventional resources and look for "dessert" with relatively high abundance in low-abundance area. The evaluation in unconventional reservoir with low abundance and large-area shows well results.
本论文的研究目的是形成油气资源丰度模拟的方法技术和实用流程,并研发一套油气资源丰度模拟软件模块。通过方法和软件模块的实际应用,定量预测油气的空间分布位置和规模大小,为资源评价技术的进一步发展与更新换代进行开拓性探索。
预测油气资源的空间分布包含两方面的内容,一是油气可能存在的位置,二是在该位置上油气的聚集量大小。论文从这两点出发,首先统计分析了油气规模、油气资源丰度的分形特征;接着探讨了油气资源在空间展布上的分形特征,以及从成藏机理和空间数据分析进行油气分布位置研究的方法;然后基于油气资源的分形特征和傅立叶变换能实现空间域与频率域互相转换的特性,通过分形模型、傅立叶变换、频谱模拟、条件模拟等模型和技术,研究将油气规模特征与空间位置特征进行综合分析的手段,以及通过勘探风险、经济界限等对资源丰度模拟过程进行约束和修正的方法。最后通过松辽盆地北部古龙凹陷葡萄花致密油层、肇州-朝阳沟地区大面积低丰度分布的扶余油层的应用研究,详细叙述了方法的应用流程和效果。
论文建立了一套油气资源丰度模拟的方法体系和应用流程,填补了国内在油气资源空间分布研究领域的空白;研制出可满足油气勘探实践需要的油气资源丰度模拟软件模块。应用研究表明方法对非常规资源评价及在低丰度区寻找相对高丰度“甜点”具有可行性;针对大面积低丰度分布的非常规储层油气的评价取得了较好的效果。
In recent years, petroleum resource assessment is being developed from the evaluation of resources scale to quantitative prediction of their spatial distribution, and from resource evaluation to integration of resources and target evaluation. Petroleum exploration and development have expanded gradually from just traditional structural reservoirs to lithologic and stratigraphic reservoirs as important as structural reservoirs, from conventional to unconventional resources, and from the conventional closure traps to continuous reservoirs. Blocks with higher abundance are becoming less and less in all around the world, especially in China. Exploration domains are increasingly turning to low porosity, low permeability and lower abundance resources. Traditional methods of resource assessment have been difficult to meet the needs of rapid development of petroleum exploration. Developing more suitable, practical new methods has become the hot topic in the field of petroleum resource assessment.
The purpose of this paper is to develop methods, technologies and practical process of simulation of petroleum resources abundance, and to develop software modules of the simulation. Through the methods and their application, we want to predict quantitatively the spatial distribution of petroleum resource, and to make pioneering research and upgrading for the further development of petroleum resource assessment.
Prediction of petroleum resources spatial distribution contains two parts, one is the position that resource may exist, and the other is accumulation size in the position. Starting from these 2 points, we give statistical analysis of fractal characteristics of the scale of resource and resources abundance firstly. Secondly we discuss fractal characteristics of resources spatial distribution, and methods to study petroleum distribution through accumulation mechanism and spatial data analysis. Thirdly we propose the methods of simulation of petroleum resources abundance based on fractal characteristics of petroleum resources and Fourier Transform, which can convert information from space domain to frequency domain, or the other way round. The methods work through fractal model, Fourier Transform, spectrum simulation, and conditional simulation. We also study on the methods making comprehensive analysis on characteristics of petroleum scale and spatial location, and methods giving constraints and correction for the simulation of process by exploration risk, economic limit, etc. Lastly we demonstrate in details the process of the method and its effects through application on tight reservoirs of Putaohua in Gulong Sag, low abundance reservoirs of Fuyu in Zhaozhou - Chaoyanggou, northern part of Songliao Basin.
The paper establishes methods for and application process for petroleum resources abundance, which has filled domestic gap in the field of petroleum resources spatial distribution. It also develops software modules for simulation of petroleum resources abundance that meet the needs of petroleum exploration practice. The application proves there have possibilities using such method to evaluate unconventional resources and look for "dessert" with relatively high abundance in low-abundance area. The evaluation in unconventional reservoir with low abundance and large-area shows well results.
引文
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[2] Barton C C and Scholz C H. The fractal size and spatial distribution of hydrocarbon accumulations. Fractal in petroleum geology and earth processes. New York: Plenum Press. 1995. 13~34
[3] Chen H C, Fang J H. A new method for prospect appraisal. AAPG Bulletin, 1993. 77: 9~18.
[4] Chen Z H and Osadetz K G. Geological risk mapping and prospect evaluation using multivariate and Bayesian methods, western Sverdrup Basin of Canada. AAPG Bulletin. 2006a. 90(6): 859~872
[5] Chen Z H and Osadetz K G. Undiscovered petroleum accumulation mapping using model-based stochastic simulation. Mathematical Geology. 2006b. 38(1): 1~16
[6] Chen Z H, Osadetz K G, and Hannigan P. Simulating the spatial distribution of undiscovered petroleum accumulations. Canadian International Petroleum Conference. 2002. Paper 2002-118, in the proceedings CD
[7] Chen Z H, Osadetz K G, Gao H, et al. Improving exploration success through uncertainty mapping, Keg River reef play, Western Canada Sedimentary Basin. Bulletin of Canadian Petroleum Geology. 2001. 49(3): 367~375
[8] Chen Z, Osadetz K G, Gao H, et al. SuperSD: An object-based stochastic simulation program for modeling locations of undiscovered petroleum accumulations. Computer and Geosciences, 2004, 30:281~290.
[9] Chen, Z., Osadetz, K. Gao, H. and Hannigan, P. An object-based model for predicting locations of undiscovered oil and gas accumulations, western Sverdrup Basin, Canada. Marine and Petroleum Geology, 2004
[10] Chen, Z., Osadetz, K., Embry. A, Gao, H., and Hannigan, P., 2000b, Petroleum potential in western Sverdrup Basin, Canadian Arctic Archipelago, Bulletin of Canadian Petroleum Geology, 48(4): 323~338.
[11] Chen, Z., Osadetz, K., Gao, H., Hannigan, P. and Watson, C. 2000a, Characterizing spatial distribution of the undiscovered hydrocarbon resource, Keg River reef play, the Western Canada Sedimentary Basin, Bulletin of Canadian Petroleum Geology, 48: 150– 161.
[12] Divi R S.. Probabilistic methods in petroleum resource assessment,with some examp les using data from the Arabian region. Journal of Petroleum Science and Engineering, 2004, 42: 95~106.
[13] Guo Q L, Wu N, Kong F Z, et al. Oil and gas exploration risk evaluation and screening offavorable areas for future exploration in Shenxian Sag, Bohai Bay Basin, China. Proceedings of IAMG 2007. 2007. 624~628
[14] Harff J, Davis J C, Olea R A. Quantitative assessment of mineral resources with an application to petroleum geology. Nonrenewable Resources, 1992, 1: 74~84.
[15] Hood, K. C., B. C. South, F. D. Walton, O. D. Baldwin and W.A. Burroughs, 2000, Use of geographic information systems in hydrocarbon resource assessment and opportunity analysis, in Geographic Information Systems in Petroleum Exploration and Development (Timothy C. Coburn and Jeffrey M. Yarus ed.). Tulsa, Ok: American Asociation of Petroleum Geologists, AAPG Computer Applications in Geology, 4: 173~185.
[16] Houghton, J. C. Use of the truncated shifted Pareto distribution in assessing size distribution of oil and gas fields. Mathemat. Geol. 1988, 20:907~937.
[17] Hu S Y, Guo Q L, Chen Z H, et al. Probability mapping of petroleum occurrence with a multivariate-Bayesian approach for risk reduction in exploration, Nanpu Sag of Bohay Bay Basin, China. Geologos. 2009. 15(2): 91~102
[18] Kaufman G M, Balcer Y and Kruyt D. A probabilistic model of oil and gas discovery Estimating the volume of undiscovered oil and gas resources. AAPG Studies in Geology v. 1. 1975. 113~142
[19] Kaufman G M, Lee P J. Are wildcat well outcomes dependent or independent. Nonrenewable Resources, 1992, 1: 201~213.
[20] La Pointe P R. Estimation of undiscovered hydrocarbon potential through fractal geometry. Fractal in petroleum geology and earth processes. New York: Plenum Press. 1995. 35~57
[21] Laherrere J.. Distribution of filed sizes in a petroleum system: parabolic fractal lognormal or stretched expotential?. Marine and Petroleum Geology, 2000, 17: 539~546.
[22] Mandelbrot B. B.,. How long is the coast of Britain? Statistical self-similarity and fractional dimension. Sci-ence, 1967,156(3775):636~638.
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