In the face of reserves depletion the alternative solution aimed to maintain oil production level is unconventional reservoirs development. Due to increasing percentage of wells targeted to unconventional reserves and on some oil fields to oil rims presented by low permeability (less than 0.0005 mkm2) and low net-to-gross ratio (less than 30%), the investigation of available and development of new approaches to analysis of the geological features of the heterogeneous reservoirs (particularly estimation of the reservoir’s connectivity and effective permeability) and approaches to simulation (matching and forecast) of production profiles for complex geology is required. Adoption of advanced technologies in oil industry as to well stimulation techniques (hydraulic fracturing and horizontal wells drilling with multi-stage hydraulic fracturing) and mathematical modelling of the field development requires application of the knowledges about geological heterogeneity of the reservoir considered as the uncertainty. Most commonly, geological uncertainty is one of the most important factors influencing the field development design. Hydrocarbon reserves, amount and rate of change of oil/gas/water production determine basic types of geological uncertainty: static and dynamic respectively.
The article presents the results of numerical calculations performed on the base of synthetic stochastic 3D geological and simulation models. The method used for geological models creation, based on variation of geological parameters (net-to-gross ratio, vertical and horizontal variogram ranges) is described. Impact of the parameters changes on the results of statistical estimation of the static constituent of geological uncertainty (value of the parameters characterizing geological uncertainty such as reservoir compartmentalization, thickness, length, and portion of connected volumes) and dynamic constituent of geological uncertainty (oil recovery factor) are analyzed. Influence of the geological parameters on geological heterogeneity and influence of geological heterogeneity on forecasted oil recovery factor are revealed. Thus, based on the abovementioned analysis the approach for multivariate optimization of the field development of tight oil reservoirs with low connectivity is provided.
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