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Nowadays there is observed a global trend of ever-increasing complexity and heterogeneity of hydrocarbon reservoirs. More challenging time makes companies take high-risk decisions based on long-term production prediction. As deterministic approach always gives a single result, it loses its relevance when we deal with risks. Generally probabilistic assessment methodology is coming to the forefront. A new approach called RE-Status (Reservoir evaluation status) has been developed in this study. The methodology is based on probabilistic assessment and along with normal uncertainty technique it includes lithofacies modeling. RE-Status is based on six key parameters that allow us to understand reservoir complexity and level of project definition in terms of reservoir engineering. Geological models were created by combining all geological and geophysical data in order to provide the highest-quality 3D representation of heterogeneous carbonate reservoirs. Evaluation of micro-macro heterogeneities and complex analysis of all core studies were used to derive lithofacies. Systematization of stratigraphic analysis, core descriptions and well logging data allowed us to locate facies in reservoir cross-section. It gave us better understanding of the reservoir and nature of filtration processes. The new approach was applied to two gas fields. Impact of reservoir parameters and lithofacies variability on the dynamics of gas production was described. In the first case RE-Status helped to improve history matching by using facies and uncertainty analysis. In the second case (green field) production prediction based on the results of heterogeneity analysis and facies modeling allowed to locate sweet zones, optimize drilling strategy, increase reliability of forecasting and reduce the uncertainty range. Novelty of the described approach is application of facies modeling to reduce key uncertainties, match the reservoir model to historical data and provide the most accurate forecast of production.

Nowadays most of the world's hydrocarbons are extracted from carbonate reservoirs and this trend will continue in the next century. However, despite a significant number of publications and scientific papers, reserves estimation and planning of carbonate reservoir development still involve a significant level of uncertainty. Complexity of the study of carbonate reservoirs is due to the heterogeneity of pore structure media, which reduces the reliability of porosity determination and also explains the ambiguity in predicting permeability. The problem of evaluating the pore structure of carbonate reservoirs is solved by attracting actual measurements on the core. According to the accepted techniques for preparing and examining core samples, only absolute permeability values are estimated and not effective values in reservoir conditions. For gas wells, the only reliable method for estimating the effective permeability is based on analysis of well test data and production logging data (PLT). This article highlights the experience of applying the proposed approach to assessing the permeability and porosity of carbonate reservoirs while gas field development. The purpose of this work is to determine the effective reservoir properties of the investigated deposits and to estimate the amount of gas initially in place. To assess the reservoir quality heterogeneity, the analysis of well test data and production logging data were performed and intervals with effective permeability were identified. For each perforated interval the effective permeability value is determined on the basis of the actual gas production and inflow rate. To calculate the porosity of net pay intervals, the relationship between the core plug permeability and porosity was applied. Thus, to evaluate effective reservoir parameters, well test data and production logging data are used the entire life of the well, and the calculation results represent the range of porosity and permeability variation for each production interval. The practical importance of the work is that this approach to the assessment of effective porosity and permeability allows us to identify and assess the gas reserves that will be effectively involved into the development.

The CSR field is one of the largest gas condensate field located in the Amu-Darya petroleum province. The studied basin situated in the central and eastern parts of Turkmenistan, western part of Uzbekistan, and in the north of Afghanistan and Iran. The main target is Callovian Oxford-carbonate deposits characterized by high heterogeneity and this fact greatly complicates the prediction of reservoir rocks distribution.The object of the study is to improve the methods of constructing a geological model of the CSR field based on the climate stratigraphic method and development of recommendations for gas stimulation depending on the lithofacies features of productive deposits.In order to achieve the intended purpose the following tasks were discussed:• Studying the sedimentation patterns in the Callovian-Oxfordian basin in the north-western part of the Chardjou tectonic stage; • Core analysis and lithofacies/petrotypes identification; • Well correlation based on the climate stratigraphic method; • Reservoir properties analysis of identified lithofacies, evaluation of their productivity; • Production logging (PLT) analysis; • Areal distribution prediction of various lithofacies/petrotypes.The research methodology is based on a climate stratigraphic approach which enables the calculation of the gamma ray and gamma-spectrometry spectral trends sensitive to the conditions of sedimentation.The deposition model of the Upper Jurassic productive deposits of the CSR field constructed according only to lithological and facies core analysis is lack of credibility due to the small amount of core material. The reliability increasing can be achieved through the use of the climate stratigraphic method in order to improve the understanding of the depositional environment in which pay zones were deposited as well as to predict the composition of the sediment facies.This work has allowed the prediction of the areal distribution of pay zones and significantly improves the accuracy of geological and simulation models that are the basis of efficiency for geological exploration and field development.

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