Mobile Wellsite Compressors: New Lease on Life for Mature Gas Field

These days more and more gas and gas condensate fields are reaching the late stage of development, which characterized with an increasing amount of challenges impeding recovery of reserves. In order to solve the problems, oil and gas companies employ different solutions which have certain conditions of practical application and different efficiency. Gas distributed compression solutions based on mobile wellsite compressors can be considered as one of the most modern and efficient solution. This technology has already established an excellent reputation in CIS countries and overseas by demonstrating the high result of implementation. However, in order to decide whether to implement this technology or not, it is required to elaborate a good feasibility study. The low level of the elaboration can easily overestimate the efficiency of the project as well as underestimate it thereby ensuing refusal of potentially efficient project. Since each project of technology implementation is unique it is not enough just utilize a common approach of project implementation to prepare an excellent feasibility study. Currently, it is quite difficult to find a methodology to prepare a decent feasibility study for mobile wellsite compressor implementation. The author while working on mobile wellsite compressor project has obtained solid experience which is reflected in this paper. Based on a dozen of integrated asset modeling simulations system of criteria for candidate selection for wellsite compressor installation was elaborated. In order to improve the efficiency and flexibility of the wellsite compressor operation an optimized approach to well hookup was advised. With the intention of improving the economic efficiency of mobile wellsite implementation set of recommendations was provided. The paper can be used as a basis for creating a solid feasibility study for wellsite compressor implementation. Recommendations provided in the article will enable not only improve the feasibility study but also minimize time and computational power allocated on the project.