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Most history matching (HM) tools consider only the minimum and maximum geological constraints during their calculations. As a result, after several iterations, the link between petrophysics and SCAL data is often lost. The iteratively created model suffers from certain geological inconsistency, as for example porosity/permeability relations are not honouring their petrophysical constraints. In this paper the relation between model parameters is coupled to rock types which are iteratively updated as a part of the history match process.

An adjoint history match method is used to predict permeability updates for all individual grid blocks. Whenever the permeability (or other property) value of a grid block falls outside the typical range or violates the geological consistency limits, the rock type of the related grid block is moved to a better fitting class. This approach coupled with the adjoint method will provide an improved history match workflow. The workflow is presented for synthetic simulation models and the results are compared against benchmarks.

The modification of rock types driven by areal permeability improves the HM workflow. The rock types have different permeability ranges, relative permeability curves with different connate water and residual oil saturations. Based on the areal permeability, the rock type is changed with corresponding parameters at grid block level. The extended workflow of HM allows parameters to be modified co-dependently according to the rock type definition, after the permeability adjustment suggested by adjoint based algorithm. The results show obvious improvements in HM quality in terms of geological consistency with less iterations. This workflow is an efficient extension for HM of oil and gas fields. Potential challenges can arise in this approach. The rock type distribution may change compared to the initial setting. Since the initial volume calculation is based on rock type dependent properties, it can cause small changes in initial hydrocarbon volumes (STOIIP). Conflicting indicators (different model parameters suggest different rock types) must be handled, which requires prioritizing in order to avoid inconsistency. Properly including the porosity-permeability correlations, priorities and model specific details, the rock type can bind all the geological properties together, which allows consistent parameter changes for an improved HM process.

This paper investigates a new workflow that improves the geological consistency of the process of assisted HM with a strong consideration of different geological constraints with respect to the different rock type definitions. The new workflow is provided as an external tool that can be applied as an extension for existing assisted HM workflows.


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Document ID: SPE-203231-MS

Roman M.
Post by Roman M.
February 8, 2021