【摘 要】
：
煤岩力学参数是煤与煤层气开采的重要指导参数。常规测井方法能够直接获取地层信息,是进行煤力学性质研究的重要数据来源。本次处理鄂尔多斯盆地SSL-03和SSL-06号井350组常规
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煤岩力学参数是煤与煤层气开采的重要指导参数。常规测井方法能够直接获取地层信息,是进行煤力学性质研究的重要数据来源。本次处理鄂尔多斯盆地SSL-03和SSL-06号井350组常规测井数据,通过使用模糊神经网络算法进行非线性系统建模,建立了常规测井数据(声波时差、自然伽马、密度、泥质含量、自然电位等)与煤岩力学参数(弹性模量、泊松比、剪切模量、拉梅系数、抗拉强度、单轴抗压强度、内聚力等)之间的对应关系。本模型具有广泛的应用前景,可以用于煤岩力学性质的快速评价。
Coal and rock mechanics parameters are important guiding parameters for coal and coalbed methane exploration. Conventional logging methods can directly obtain formation information, which is an important data source for the study on the properties of coal mechanics. This time, 350 sets of conventional well logging data of SSL-03 and SSL-06 wells in Ordos Basin were processed. By using the fuzzy neural network algorithm for nonlinear system modeling, conventional well logging data (acoustic time lag, natural gamma, density, Muddy content, natural potential, etc.) and the mechanical parameters of coal and rock (elastic modulus, Poisson’s ratio, shear modulus, Lame coefficient, tensile strength, uniaxial compressive strength, cohesion, etc.) The model has a wide range of applications, can be used for rapid evaluation of the mechanical properties of coal and rock.
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