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基于层次灰色理论的江西丰城矿区煤层气资源评价
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摘要
丰城矿区位于江西省境内的萍乐含煤区,矿区内B4煤层为主要可采煤层,煤层透气性偏好,煤层结构简单,为发育稳定的中厚煤层。煤层有机组分含量高,平均含量值占81.38%,有机显微组分以镜质组为主,具有很好的生气潜力条件。该区煤层盖层厚度大且顶板岩性组合特征有利于气体保存,区内地质构造条件简单,根据本区煤储层特征分析,主要煤层的煤层气储存性能良好;矿区煤层含气量一般在10-20m3/t,平均含气量在15m3/t左右,煤层含气丰富,具有很好的煤层气利用和开发前景。针对以往丰城矿区煤层气理论系统的定量分析研究薄弱,本文对丰城矿区主要块段通过数学评价定量分析,具有一定的理论意义。
     论文在对丰城矿区曲江、坪湖、建新、八一和石上井田区域煤层气赋存地质条件和煤储层资料研究的基础之上,基于层次灰色理论建立丰城矿区煤层气资源评价体系。根据以往煤层气评价的研究和结合丰城矿区具体煤层气地质条件,对丰城矿区煤层气影响因素进行分析,确定了煤层埋深、顶板岩性、构造条件、煤层含气量、渗透率、孔隙度、煤储层压力、煤层厚度、煤变质程度和镜质组含量这十个因素作为本文的评价指标,并通过这些评价指标构建丰城矿区煤层气资源评价层次模型。在所建立的层次模型中,结合层次分析法和灰聚类分析法的各自优点,通过层次分析确定各因素隶属上一层次某准则下的权重,然后通过灰色系统理论对模型最底层基本影响因素进行灰色分析,二者结合得出最终评价结果。
     论文研究区域共划分出152个评价单元,经过各评价单元参与评价指标的定量化数据处理,运用灰色理论得出各评价单元评价指标的灰色评价系数,并结合层次分析所确定的各层次元素的权重,最终进过矩阵运算计算出各单元评价结果。根据本文灰聚类分析所确定的四个灰类(最有利区、有利区、一般区、不利区),利用各评价单元煤层气评价结果,得出研究区域煤层气资源灰色评价结果有利区、一般区和不利区分布范围。本文通过丰城矿区煤层气富集影响因素分析,采用建立数学模型定量评价的方法对丰城矿区煤层气资源潜在开发与利用的优劣区域进行了具体划分,为丰城矿区未来煤层气资源的开发和利用提供参考依据。
Fengcheng mining area is located in Pingle coal-bearing area of Jiangxi Province. B4Coal seam which has characteristics including the better permeability, simple structure and developing stability belongs to medium-thickness seam as mainly mining coal seam in the mining area. Organic components are a high content which occupy about81.38%in the coal seam. And vitrinite has major part in organic maceral, so coal seam possesses a good potentiality of gas generating. Meanwhile, gas is beneficial storing in the coal seam because of thicker cap rock, roof lithologic character and simple tectonic conditions in the mining area. According to analyzing characteristics of coal reservoir, gas-storing property is good in the mining area. There is a rich gas-bearing in main coal seam where the gas content is10-20m3/t, being average15m3/t. All the analysis shows that the mining area has a good outlook of CBM exploiting and utilizing. The paper was quantitatively analyzed to main blocks through mathematical evaluation in connection with formerly weakness of systematic CBM study about quantitative analysis in Fengcheng mining area, so it has some significance in theory.
     The paper was established evaluating system of CBM resource on the basis of AHP&gray theory based on research to Qujiang, Pinghu, Jianxin, Bayi, and Shishang mine field about data of geological conditions of CBM accumulation and coal reservoir in Fengcheng mining area. According to CBM evaluation of past study and CBM geological conditions of the mining area, the paper was taken these influencing factors that are the burial depth of coal-bed, roof lithologic character, tectonic conditions, coal-bed gas content, permeability, porosity, coal reservoir pressure, coal seam thickness, coal metamorphic degree, vitrinite content as evaluation indexes. And the hierarchical model of CBM evaluation was established through these evaluation indexes. The paper obtains final result of evaluation with the advantages of AHP and gray clustering analysis in the model. To be specific, weights of various indexes are got under previous level through AHP, and the basic indicators are analyzed through gray theory.
     There have been152units of evaluation divided in the study region of the paper. The coefficient of gray assessment and weights of indexes were calculated through gray theory and AHP after indexes of evaluation quantitative data processing in each unit. Finally, result of assessment was obtained with matrix operation in each unit. There are different regions of distribution between favorable zone, general zone and unfavorable zone owing to gray clustering analysis defining four gray classes (the most favorable zone favorable zone, general zone and unfavorable zone) through the each unit's result of CBM assessment in CBM gray assessment of the study region. The paper was set off pros and cons regions to potential CBM resource exploiting and utilizing with adopting quantitative evaluation of mathematical model on the basis of analysis about influencing factors of CBM enrichment in Fengcheng mining area. At the same time, the result perhaps will provide reference for CBM exploitation and utilization of the mining area in the future. Figure [23] table [37] reference [55]
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