Estimating effective shale area distributions from subsurface data
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文摘
Estimation of shale bed continuity is needed in reservoir modeling and simulation as these constitute permeability barriers and baffles. However, efforts to characterize continuity of shale beds from 2D outcrop or well log sections lack critical 3D geometry and areal dimensions. A different approach is to estimate shale bed continuity by measuring the 鈥渆ffective shale area鈥? While it is a more indirect measure of shale bed continuity as it relies upon the sealing capacity of shales in selected, well-documented field examples, it eliminates the problem of the unknown but critical third dimension. Analyses of effective shale area distributions are made within structurally simple fields where hydrocarbon contacts were directly controlled by the sealing shales being measured, and faulting is limited. Datasets are exclusive to siliciclastic reservoirs formed in paleoenvironments ranging from non-marine to shallow water marine.

Results show that effective shale areas are separated into two distinct distributions of fully marine versus non-marine/marginal marine origin. Shales deposited in non-marine to marginal marine paleoenvironments display smaller areas where effective sealing capacity is reduced by channel body incision. In fields where hydrocarbon columns are sealed by fully marine shale, larger areas are supported, often but not always, approaching structural spill points. In the case of reservoirs capped by these marine flooding shales, one can logically infer an abrupt decrease in channelization and resulting sizeable increase in continuity of shale bed seals.

Similar shale types in traps formed in different structural regimes (e.g. extensional versus contractional domains) show comparable areal distributions, supporting use of data from different locations where the controls on hydrocarbon seal areas are well known. All shales measured here are areally large and would probably be accommodated in reservoir simulation deterministically, but use of the dimensions provided here would clearly be an aid in situations where a limited number of field appraisal wells are available. Discriminating between deterministic shales and stochastic shales, which are several orders of magnitude smaller in size, is also important for reservoir modeling and simulation. Results shown here should also be of great utility as input into discovery appraisal and field development scenario construction.

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