Production logging and well testing are a source of key information for the design and control of field development. The relevance, reliability and completeness of these researches depend on how effective decisions are made at all stages of field development. Reliable results of field researches: production logging and well testing are important source of information on well and reservoir characteristics, bottom-hole area, inter-well interaction etc.
Within the framework of continuous improvement of the efficiency of process control and optimization, Gazprom Neft develops a number of projects in the field of production logging and well testing to develop tools and technologies aimed at solving the number of challenges. Increasing the complexity of the resource base, the development of low-permeability reservoirs, oil rims and fractured reservoirs requires the development of new approaches in the planning and processing of field researches. An increase in the number of oil assets and an increase in the number of wells with high-precision downhole telemetry lead to an increase in the number of field researches. This circumstance, coupled with the current preservation of the volume of labor resources at the current level, leads to the need to create automated systems for preparing and processing data. High resource consumption of well operations and complex geological structure of new assets of the Company raises the price of a possible error, which is associated with incorrect decisions, based on incomplete or unreliable results of field research. In this regard, comprehensive measures are needed to increase the reliability of the results of processing production logging and well testing, as well as assessing the reliability of all estimated parameters.
The article briefly describes completed and ongoing projects aimed at developing technologies and tools for production logging and well testing researches in the following areas: centralization and verification of field research data, automation of well-testing interpretation, development of a methodological and software system for optimal well testing planning, optimal well planning based on the value of information (VOI), generating of reservoir pressure maps based on proxy modeling, implemented of new production logging technologies and the development of a temperature simulator.
