This paper presents an analysis of the Corrib field surveillance dynamic pressure and rate data. The Corrib field, on production since December 2015, is a gas reservoir developed with six wells. The field static gas initially in place (GIIP) is around 1.2 Tcf of dry gas and the reservoir is comprised of a complex heterogeneous sandstone consisting of a high net to gross sequence of low sinuosity braided fluvial channel, sheet sand, playa and sandflat facies of varying reservoir quality (from single to hundreds of millidarcys) with an abundance of mapped faults. The dynamic reservoir analysis approach used in this study is based on a form of pressure-rate deconvolution that has been presented in an earlier paper SPE-195441 for the Tamar field, Israel. The pressure transient analysis (PTA) software that implements this analysis capability handles both singlewell and multi-well analysis problems. From a preliminary review of Corrib field dynamic behavior, it was concluded that this field data can be analyzed using single-well pressure-rate deconvolution applied to the data of each reservoir well separately. This contrasts with the Tamar field that required a true multiwell deconvolution analysis approach. Different approaches in these cases are dictated by the differences in reservoir architecture, geology, offtake strategy and the character of connectivity across these two fields. There are several pressure-rate deconvolution algorithms implemented in different PTA software tools used in the industry. All these algorithms implement a form of automatic regression and are sensitive to the quality of pressure and rate data that serve as input into the deconvolution algorithm. These automatic algorithms are often not robust enough to be used with surveillance type data acquired during long term production operations. The deconvolution approach used in this work is not automatic and, as a result, the deconvolution results are not as sensitive to the data quality. Rather, it relies on specialized software that facilitates manual reconstruction of constant rate drawdown responses. This human approach in combination with specialized software allows an engineer not to just reconstruct a drawdown response but to "explore" the pressure and rate data to develop significant insights of the dynamic reservoir behavior. This deeper understanding is an additional advantage over automated techniques and is the purpose of reservoir analysis. The Corrib field analysis discussed in this paper is a demonstration of what can be achieved using this combination of human intelligence and specialized software tools. Demonstration of the workflow used for manual reconstruction of deconvolved response functions and the role of the specialized software used that implements this workflow is explained. In the course of this reconstruction, an "exploration" process of trying to reconstruct the transient pressure behavior reflected in the data is engaged/utilized. Once reconstructed, this response is interpreted in terms of reservoir and well properties. The end result of this investigation is a deep understanding of the Corrib gas field dynamic behavior not easily obtained from conventional PTA methods. For example, it shows that early production data clearly exhibit signs of interference between wells. However, once the field production drops off the plateau period and the well production starts to decline, the six producing wells dynamically divide the reservoir into separate drainage areas and the well interference in a way "disappears" - the wells behave as if each of them produces from its own drainage compartment. This allows pressure rate deconvolution on a single-well basis, based on each compartment instead of using multi-well deconvolution on the field as a whole. The pore volume of each such compartment is reflected in the late time pressure behavior of the respective drawdown response associated with the well data. The sum of these individual pore volumes per well in the field yields the total pore volume connected to the wells that is supported by the reservoir dynamic behavior. These insights are reinforced by the use of synthetic models to provide clarity and understanding of the drainage compartment theory used during Corrib analysis.

Reservoir appraisal programs prior to field development sanction typically do not fully assess the entire reservoir in terms of properties, connectivity, and architecture. The well tests performed on appraisal wells are relatively short and the dynamic data acquired during these tests reflect reservoir properties in the near well region. The properties on the scale of the entire reservoir are reflected in the dynamic pressure and rate data acquired on a much longer time scale and for practical and environmental reasons such data can only be obtained during production operations after the field is in production. It has become a routine practice in new field developments to equip development wells with permanent downhole pressure gauges. Analysis of this pressure data with the well rate early in the field life creates an opportunity to adjust the development plan based on the understanding of reservoir properties, its connectivity, and architecture. This paper presents a methodology for reservoir dynamic analysis that incorporates the information from surveillance pressure and rate data and integrates this analysis with geological and seismic data interpretation reflected in reservoir maps. This is a generalization of pressure transient analysis technology to the analysis of dynamic data on a much longer time scale and to the multi-well environment. This is not a straightforward generalization because these longer temporal and spatial scales bring into focus additional physical factors that must be accounted for in the analysis. This paper demonstrates the application of this analysis approach and of the entire workflow to real surveillance data from a gas reservoir. The technique presented does not impose any special requirements on data quality. The analysis approach and the entire workflow yield a much clearer picture of the reservoir and allow engineers to develop profound insights and draw important conclusions which guide and influence decision-making processes. The limitations of this workflow are also discussed, and advice is provided as to when the approach presented can be used and when the underlying principles associated with PTA break down.