The article covers the features of reservoir identification in the volcanogenic-sedimentary deposits of the central zone of the northeastern frame of the Krasnoleninsky arch. The porosity cut-off values used for reservoirs identification based on standard well logging complex data have been clarified. Porosity ratio analysis in the intervals with formation fluid inflow allowed identifying two predominant reservoir types: fractured-cavern and fractured-cavernous-granular. Reservoirs of the fractured-cavern type are characterized by low porosity and permeability properties. The presence of macrocracks and caverns causes a decrease in core recovery and increased production rates of formation fluids during testing do not correspond to the reduced filtration properties of core samples characterizing an impermeable matrix. The reservoirs of this type are mainly effusive. The void space of reservoirs with increased porosity and permeability properties is represented by cracks, cavities and intergranular voids of both primary and post-magmatic origin. The reservoirs of this type are confined to effusive, volcanoclastic, volcanogenic-sedimentary rocks with different intensity of secondary alterations. For fractured-cavernous-granular reservoirs, boundary values were determined using the results of oil displacement experiments by comparing dynamic coefficients, effective and total porosity of core samples, as well as using the porosity values calculated from the well logging data based on inflow and non-inflow intervals. The range of ambiguity of distributions reaches 5-25%, which significantly reduces the accuracy of reservoir intervals identification in wells by the value of the porosity boundary value. The boundary porosity value was obtained by constructing cumulative distributions of porosity values of core samples divided into reservoirs and non-reservoirs and cumulative distributions of porosity values of inflow and non-inflow intervals calculated from well logs. There is a tendency to increase the ranges of ambiguity and decrease the efficiency of separating the rocks of the studied sequence into reservoirs and non- reservoirs from volcanoclastic, volcanogenic-sedimentary rocks to effusives with voids, transformed volcanogenic rocks, weathering crust deposits, which is probably due to the complication structure of the void space and an increase of secondary minerals. An example of reservoir intervals identification using a complex of qualitative and quantitative features is shown. The use of updated boundary porosity values allowed a significant increase of the reservoir identification accuracy in studied deposits.
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