We present a novel, data-driven approach to integrated well/reservoir performance analysis and opportunity identification for mid-to late-life pattern waterfloods.The Salym group of oilfields is located onshore in Western Siberia, Russia's prime oil producing province, and is operated by Salym Petroleum Development (SPD), a 50-50 joint venture between Shell and Gazprom Neft. The main productive formation, comprising strongly layered, deltaic/fluviatile sandstones, has been developed as a pattern waterflood, with over 950 deviated wells drilled since 2004. Overall watercut is currently around 82% and with oil production declining at 6-7% year on year, waterflood management is an absolute strategic priority.The operator has responded to this challenge by investing heavily in waterflood management and performance evaluation. Particularly, a dedicated effort was made to develop the company's enterprise information architecture and create a purpose-built online waterflood management tool (WMT). All Salym geological, completion, production and well status data is automatically quality-checked, stored and updated in an integrated waterflood database and made accessible through the WMT. The WMT provides a wide range of functionality for data visualization, performance diagnostics and analysis. Furthermore, it is coupled to a full-field surveillance simulation model, which auto-updates with new oilfield data as it becomes available and outputs streamlines, well allocation factors, maps of remaining oil distribution and pattern-and block-level calculated properties.These technologies have enabled the development and implementation of a structured methodology for waterflood performance evaluation that involves systematic assessment of blocks of 20-50 wells in the form of an Annual Field Review (AFR) followed by a series of deep-dive Integrated Block Reviews (IBRs). During the AFR, each block is assessed against a set of KPIs and scored and prioritised in terms of its health status and projected recovery shortfall. Based on this prioritisation, blocks are scheduled for review in an IBR during the course of the year. The IBRs focus on individual wells, patterns and reservoirs and during the reviews concrete well, reservoir and facilities management (WRFM) opportunities are identified to address performance gaps and sweep or accelerate remaining oil. These opportunities are captured in an online opportunity register coupled to an online database for workover strategy preparation.The framework of technologies and processes presented in this paper was instrumental in planning and executing over 260 WRFM activities (not including simple pump change-outs) across the Salym fields in 2014, delivering in excess of 3.2 Mln bbls of in-year oil production.

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The main purpose of this project became a creation of the reservoir complexity index calculation method. This index should integrate the whole complex of geological characteristics which work on the reservoir engineering complexity in one value. The article describes the approach to calculation the reservoir complexity index based on the Gaspromneft Company's assets using simplified simulation. This index allows you to conduct an express assessment of the field potential and is useful in the process of benchmarking the fields of the Company or the region. We analyzed widespread available approaches of figuring the complexity index (RCI) in which RCI acts as a function of a number of parameters affecting the Recovery Factor (RF). Then based on results of analysis a new advanced approach was submitted that takes into account, in addition to the main geological characteristics of the formation, the indices of layered and lateral inhomogeneity expressed in numerical form During the next stage was realized the multivariate statistical modelling with 2D-simulator on the stream-line that is necessary for obtaining real function connection RF=f(RCI). For the simulation, statistical data of the fields of Western Siberia (Gazprom Neft Company) were used. Then with use of gradient method were matched weighing coefficients of equation linear regression expressing RCI as a function of its parameters. As a result, a set of equations (linear regressions) with a different number of variables and different weight coefficients was obtained. These equations make it possible to calculate the field complexity factor for different sets of input data, as well as for different methods and development systems, operating conditions for the deposit, well completion types, field development periods, etc. RCI for the company's fields was evaluated and noted the high convergence of project RF data with theoretical dependence found out earlier. At the same time, it was noted that for a number of Company's fields with a high index of complexity, the values of project RF could be unjustly uprate. This approach was used for the benchmarking of the Company's fields and proved to be a good express method for assessing the field potential. The aspects considered in the article are related to the new and quite unknown area in Russian speaking segment of OnePetro library. The novelty of the approach is to use a set of simplified simulation models to obtain the linear regression equation, and also to take into account in this equation the indices of reservoir heterogeneity in numerical form. It is also a point of interest to apply this approach in conditions of deposits in Western Siberia.

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