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This paper demonstrates the multivariate approach as a tool for the management of initial data uncertainties in 3D reservoir simulation processes. The multivariate approach helps to address several problems, including optimizing the development scenario, determining the well type, and calculating the optimal horizontal well completion system.The method for determining the optimal development scenarios includes performing multiple forecast runs on simulation models with variations of initial data (such as permeability and water/oil contact) for various development scenarios (including well spacing and development plan). Then, the data are systematized, and a statistical analysis is performed with the calculation of economic indicators. The distributions of technical and economic development parameters are built from the results of these processes. The optimal development scenario is selected directly by selecting the realization with the maximum probability of occurrence from the most economically successful realizations. In other words, a development scenario is considered optimal if it has maximum probability of occurrence in the data set and maximum economic indicators (net present value (NPV) and profitability index (PI)).The paper uses two case studies to illustrate the multivariate approach for determining the optimal development scenarios by considering the initial data uncertainties.For gas field A (eastern Caspian, lower Jurassic terrigenous deposits), the task of determining the optimal well type and spacing of the new wells was addressed by using multivariate reservoir simulation. The data uncertainty is attributable to a core test result error in the permeability determination and to a lack of data for the gas/water contact depth in accordance with the well testing and production testing results. A total of 10,000 simulations of the multivariate reservoir and economic model were run to determine the optimal well type and well spacing. In addition, probabilistic values of the development technical and economic indicators P10, P50, and P90 were determined. The results of the calculation enabled the optimal development parameters to be selected and the effect of the initial data uncertainties on the final technical and economic indicators of the field development to be evaluated.The length of horizontal wells, hydraulic fracture spacing, and optimal well spacing were selected based on the multivariate approach for oilfield B (western Siberian oil and gas province, upper Jurassic). For this purpose, 100,000 iterations of the development scenarios forecast were calculated based on the multivariate simulation model. Based on the analysis of the calculations and economic model, the optimal length of the horizontal section and fracture spacing were selected and justified, enabling the optimal design and completion system for horizontal wells, as well as risk mitigation measures, to be selected.

The problem of reservoir engineering and production of coalbed methane (CBM) in Kazakhstan are important subject today. Identification of methane-rich zones from the coal geology side is not always enough. In this article, traditional methods for studying oil and gas basins are applied for identification of methane rich zones in southern part of Karaganda coal basin. Reservoir simulation is used to check the possible production performance of the zones.

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