Reservoir Value-Engineering for West Siberian Oil Fields

Abstract

A new reservoir engineering analytic tool is presented that provides express oil residual reserves estimation, classification and following express waterflooding optimization for large West Siberian brownfields. Results are compared with full field 3d simulation models, and field pilot approbations. The approach is based on residual reserves estimation and classification. Reserves classification is done with author's approach for reservoir complexity index (RCI) evaluation. The complexity of reservoir depends on three main parameters: permeability (1), fluid and rock properties: wettability, relative permeability, saturation and viscosity (2), and reservoir heterogeneity, calculated as a function of sweep efficiency and pumped pore volumes (3). All reserves are divided by RCI into several classes with the most economical way of development: sidetracks, re' hydraulic fracturing, treatments and flooding optimization. Waterflooding optimization using capacitance and resistivity model (CRM) considered more carefully as the main way to involve the largest scope of remaining reserves. The implementation of the new approach based on reserves estimation and classification helps to identify the most attractive zones and to select the most suitable way for development. It also shows values of profitable and unprofitable current remaining reserves. Based on simple capacitance resistive analogue and economic models instrument for waterflooding optimization solves the problems of OPEX reduction, NPV or production maximization in express way. Combined capacitance and OPEX optimization models demonstrate good results on some West Siberian fields and find wells with unproductive injection, unprofitable oil production (due to high watercut and low liquid rate), show zones with high production potential, help to reallocate injection volumes and to involve into development additional amount of oil coupled with economic profit. The injection wells work regime optimization is solved using genetic algorithms based on differential evolution. Results of instrument implementation correspond with 3d simulation model and show nice additional oil production on real field. To summarize, the described approach gives an opportunity to minimize operational expenditures and to improve project economic performance without additional capital expenditures or investments in the terms of low oil prices. The novelty of the work is in the using of new approach of reservoir complexity index estimation for STOIIP classification and best development methods selection. The novelty is also in integration of RCI, semi analytical physical based waterflooding management methods with hybrid data engineering methods and optimization algorithms. Using of new methods together with economic model provides a responsible tool for solving reservoir cost-engineering problems and increasing of project's value.