Production Data Analysis for Reservoir Characterization in Conventional Gas Fields: A New Workflow and Case Study
Authors: Ezabadi Mehdi Ghane , Ataei Abdolrahim , Liang Tan Kok , Motaei Eghbal , Othman Tg Rasidi 
Published: October 2017

Production Data Analysis (PDA) has been widely accepted as a valuable analytical tool for well performance evaluation, production forecasting and reservoir characterization. It is fast, practical, and inexpensiveand it can answer many questions about the connected volume to the well, flow regime, average permeability and skin, as well as any boundary within the radius of investigation of the well. It becomes even more important in the case of complex systems such as finely laminated sand reservoirs, or highly heterogeneous multi-stacked reservoirs where sometimes numerical simulation model miscarries in predicting the reservoir performance.

Analytical approaches for PDA are variants and require different levels of details in the input. Each is established based on certain assumptions and concepts, and comes with specific limitations. Despite overlap amongst the various methods, each has an advantage in particular application over the others. Therefore, one must be vigilant to use each method for the right purposes in addition to confirm the results and unveil possible uncertainties through using several different methods.

This paper integrates basic production and reservoir data through different platforms and methods. Diagnostic plots, General Material Balance (GMB), Pressure Transient Analysis (PTA), deconvolution, nodal analysis, Rate Transient Analysis (RTA), and Flowing Material Balance (FMB) are extensively used to explain the reservoir behavior through PDA. It validates RTA and FMB as an approach for reservoir characterization and reserve estimation without the need to shut-in the well, and defer the production. The benefit of continuously monitoring Flowing Bottom Hole Pressure (FBHP) using Permanent Downhole Gauge (PDG) and applying deconvolution to detect well interference and reservoir boundaries is also discussed. We have also looked at the limitation and advantage of each method and how the integration of those can provide a full picture and enhance the results.

We have studied several gas fields. The results of analysis provided an accurate perception and understanding of reservoir behavior and characteristics, well interaction and interference, potential for infill wells, production issues and well constraints, estimation of the connected volume, and eventually led to generation of a reliable analytical reservoir model for the production forecast. The estimated connected volume was tested and proved to be reliable based on infill drilling. The workflow focuses on examining the data quality, confirming the validity of work, and achieving the maximum possible insight through integration of different analytical methods.

An integrated workflow is introduced for PDAand successfully applied on different cases of highly heterogeneous conventional gas reservoirs with huge complexities. The paper demonstrates one of the case study as example.

The proposed workflow shows to be very powerful particularly when large volume of data from pressure downhole gauges (PDG) is available. It saves significant time for the study team in determining the potential value of a project.