The use of multi-stage fractured horizontal wells has made production from shale gas plays feasible. The production history from these wells is characterized by long transient linear transient flow. The key reservoir (nature) and completion (nurture) properties that impact flow behavior of the well are permeability, Original Hydrocarbon in Place (OHIP), number of hydraulic fractures, fracture area and fracture spacing. Understanding the interrelationship between these parameters is critical for optimal development of shale gas resource plays. The proposed shale gas workflow uses a hybrid analytical model. An analytics based diagnostic process analyzes well performance history and a numerical model validates the feasible history match models for representative forecasts. The model results allow the user to capture the range of uncertainty in estimating individual reservoir or completion properties, such as permeability, fracture area, fracture spacing, etc. The diagnostic process provides the relationship between key factors dictating well performance such as OHIP, effective fracture area, effective reservoir permeability, effective fracture spacing and well spacing. In this paper, wells from the Marcellus play, in Pennsylvania, USA are evaluated using the proposed shale gas workflow. Surveillance is an integral part of this workflow. The paper shows how surveillance can be used for resource management and exception management. Along with data mining, the workflow accelerates the learning curve to evaluate the effectiveness of current field practices. The results help with understanding the effectiveness of proppant pumped, the potential number of contributing clusters and production issues. Continued surveillance reduces the uncertainty surrounding all parameters. This knowledge base can then be used to optimize the asset development strategy, maximizing the return on investment (ROI).

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