Amid the ever-increasing urgency to develop oil fields with complex mining and geological conditions and low-efficiency reservoirs, in the process of structurally complex reservoir exploitation a number of problems arise, which are associated with the impact of layer fractures on filtration processes, significant heterogeneity of the structure, variability of stress-strain states of the rock mass, etc. Hence an important task in production engineering of such fields is a comprehensive accounting of their complex geology. In order to solve such problems, the authors suggest a methodological approach, which provides for a more reliable forecast of changes in reservoir pressure when constructing a geological and hydrodynamic model of a multi-layer field. Another relevant issue in the forecasting of performance parameters is accounting of rock compressibility and its impact on absolute permeability, which is the main factor defining the law of fluid filtration in the productive layer. The paper contains analysis of complex geology of a multi-layer formation at the Alpha field, results of compression test for 178 standard core samples, obtained dependencies between compressibility factor and porosity of each layer. By means of multiple regression, dependencies between permeability and a range of parameters (porosity, density, calcite and dolomite content, compressibility) were obtained, which allowed to take into account the impact of secondary processes on the formation of absolute permeability. At the final stage, efficiency of the proposed methodological approach for construction of a geological and hydrodynamic model of an oil field was assessed. An enhancement in the quality of well-by-well adaptation of main performance parameters, as well as an improvement in predictive ability of the adjusted model, was identified.

For highly heterogeneous complex carbonate reef reservoirs, rock typing with respect to depositional conditions, secondary processes, and permeability and porosity relationships is a useful tool to improve reservoir characterization, modeling, prediction of reservoir volume properties, and estimation of reserves. A review of various rock typing methods has been carried out. The basic methods of rock typing were applied to a carbonate reservoir as an example. The advantages and disadvantages of the presented methods are described. A rock typing method based on a combination of hydraulic flow units and the R35 method is proposed. Clustering methods for rock typing are used. The optimum clustering method is identified, and for each rock type, the permeability–porosity relationships are built and proposed for use in the geomodelling stage.

The article describes the original technique of predicting the effectiveness of hydrochloric acid treatment of the bottom hole zone of a carbonate reservoir. The technique consists in determining the technological effectiveness of the oil recovery stimulation procedure at productive wells using hydrodynamic simulation based on the calculated value of skin factor change. In the course of the study, a number of parameters affecting the intensity of flow coefficient decline in the near-wellbore zone during acid treatment have been established. The paper presents a comparison of data on the actual change of the skin factor after acidizing jobs at the fields of Perm Krai (Russian Federation) and the calculated values obtained using the presented technique. This scientific research includes an example of practical application of the proposed technique for the target well of the Kokuyskoye oil field in Perm Krai, its results with a minor deviation coinciding with the actual values of the flow rate. In the conclusion to the study, it is noted that using the proposed technique, recommendations can be provided on the selection of acid composition and technology of its injection into formation for the preliminary evaluation of the cost effectiveness of the designed procedure.

Current methods of oil and gas field development design rely on reservoir simulation modeling. A reservoir simulation model is a tool to reproduce field development processes and forecast production data. Reservoir permeability is one of the basic properties that determines fluid flow. From existing approaches, the porosity and permeability values should be consistent with petrophysical correlations obtained from core sample tests in the course of development of an absolute permeability cube in the reservoir simulation model. For carbonate reservoirs with complex pore space structure and fractures, the petrophysical correlations are often unstable. To factor in the fluid flow in a fractured rock system, dual-medium models are developed, allowing for matrix and fracture components. Yet in this case, the degree of uncertainty only increases with the introduction of a new parameter: a cross-flow index of fluid migration from matrix to fracture, which is only determined indirectly by results of fluid flow studies conducted in the initial development period, and therefore most often is adaptive. Clearly, for well-studied fields there is an extensive data pool drawn on research findings: core studies, well logging, well flow testing, flowmetry, special well-logging methods (FMI, Sonic Scanner, etc.); the dual-medium model development for such reservoirs is fairly well-founded and supported by actual studies. However, at the start of the field development, the data are incomplete, which renders qualitative dual-medium modeling impossible. This paper proposes an approach to factor in the target’s permeability anisotropy at an early development stage through the integration of well, core and 3D seismic surveys. The reservoir was classified into pore space types, to which different petrophysical correlations were assigned to develop a permeability array, and relative phase permeabilities were studied. The fluid flow model was history-matched with allowance for permeability anisotropy and rock types. Comparative calculations were conducted on the resulting model to select the optimum development strategy for the target.

This study presents a methodological approach to forecasting the efficiency of radial drilling technology under various geological and physical conditions. The approach is based upon the integration of mathematical statistical methods and building machine learning models to forecast the liquid production rate increment, as well as to forecast technological indexes using a hydrodynamic model. This paper reviewed the global practice of radial drilling and well intervention efficiency modeling. The efficiency of the technology in question was analyzed on the oil deposits of the Perm Territory. Mathematical statistical methods were used to determine the geological and technological parameters of the efficient technology use. Based on the determined parameters, machine learning models were built, allowing us to forecast the oil and liquid production rate. A script was developed to integrate machine learning methods into a hydrodynamic simulator. When the method was tested, the deviations in the difference between the actual and the forecast cumulative oil production did not exceed 10%, which proves the reliability of the method. At the same time, the hydrodynamic model allows for taking into account the mutual influence of oil wells, the dynamics of water cut, and reservoir pressure.