Density, photoelectric, neutron, and gamma ray logs are key inputs to the evaluation of unconventional resources. Each has a finite spatial resolution, and the properties of beds thinner than this cannot be measured directly but are (in principle) available from inversion if the logs’ response functions are known, and the thickness of each bed is known from an independent high-resolution source. An inversion method is described for beds with apparent dip angles less than about 60 degrees which uses pre-computed response functions from measurement-specific nuclear particle transport code models, combined with bed boundaries picked automatically from high-resolution microresistivity images rendered using a new technique developed for high dynamic range data. The method has application in thinly-bedded formations in general and has particular relevance in coal bed methane reservoirs where multiple thin high-contrast beds are common. Inversion results are known to be sensitive to uncertainty in bed thickness values, and constraining the inversion with information from high-resolution images is found to be highly advantageous in producing reliable results in beds as thin as 0.075m; this compares to the resolution of about 0.6m for standard porosity logs, and 0.2m for the high-resolution field logs. Inverted density logs show good agreement with core density values, and the integrity of inverted photoelectric, neutron porosity and gamma ray logs is judged to be good based on the similarity between field logs and logs reconstructed from inverted results, plus the high degree of agreement with properties of known marker beds. Inverted logs are also shown to provide improved differentiation between litho-types defined from combinations of logs using principal components analysis. The paper addresses an important source of uncertainty in the estimation of reservoir properties - namely finite spatial resolution - and in so doing reduces bias in volumetric calculations and associated net pay calculations.

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