Improving the Efficiency of Managing the Development of the West Siberian Oil and Gas Province Fields on the Basis of Differentiation and Grouping

Using image recognition methods (principal component method (PCM) and discriminant analysis) made it possible to group and identify more than 500 research objects developed in five oil and gas areas of the West Siberian oil and gas province (WSOGP), which are confined to 13 large tectonic structures and 10 productive horizons. The grouping was made according to 19 parameters characterizing the mode of oil and gas occurrence and the geologic-physical and physicochemical properties of the reservoirs and hosted fluids exerting a prevailing influence on the recovery of oil reserves and used on projecting the development of research objects. The performed study has identified 19 relatively homogeneous groups of objects, each having a specific set of geologic-physical properties. It is shown that the parameters reflecting the geologic-physical and physicochemical properties of the reservoirs and fluids within the identified groups of objects exert different effects on the recovery of oil reserves. This requires differentiation and grouping of the objects during the solution of various development problems. It has been established that the specific features of groups of objects are determined primarily by areal, tectonic, and stratigraphic factors and that grouping must be performed separately in each stratigraphic system. Algorithms are proposed for grouping the developed oil and gas fields and for searching for groups of analogous objects in fields out of exploration that are most similar to the developed ones. The performed grouping and the results obtained provide the necessary information about the research objects and increase its reliability, thus making it possible to improve the efficiency of managing the oil company assets, i.e., the WSOGP oil fields.