Although production analysis (PA) for reservoir characterization is approaching the popularity of pressure transient analysis (PTA), there are few consistent diagnostic methods in practice for the analysis of production data. Many of the "diagnostic" methods for production data analysis are little more than observation-based approaches and some are essentially "rules of thumb."
In this work we provide guidelines for the analysis of production data, as well as identify common pitfalls and challenges. Although pressure transient and production data analyses have the same governing theory (and solutions), we must recognize that pressure transient data are acquired as part of a controlled "experiment," performed as a specific event [e.g., a pressure buildup (or PBU) test]. In contrast, production data are generally considered to be surveillance/monitoring data with little control and considerable variance occurring during the acquisition of the production data.
This paper attempts to provide a "state-of-the-technology" review of current production data analysis techniques/tools particularly tools to diagnose the reservoir model and assess the reservoir condition. This work also identifies the challenges and pitfalls of production analysis and we try to provide guidance towards best practices and best tools. To compliment this mission, we use relevant field examples to address specific issues, and we illustrate the value and function of production data analysis for a wide range of reservoir types and properties.