Production Data Analysis of Smart Well Completion Revealed the Unknowns of Water Injection in a Heavily Faulted Multi-Stacked Reservoir
Authors: Ezabadi Mehdi Ghane , Chiew Kwang Chian , Chandrakant Ashvin Avalani , Raffik Raja Zuhaili Aimran Raja Zainal 
Published: October 2023

Production analytical approaches specially in presence of smart well completion equipped with several PDGs, if applied appropriately, can overcome many challenges in study of complex reservoirs with comingled production that numerical modelling alone is not capable of. The objective of this work was to firstly utilize automation and programming to compile the massive amount of PDG data in smart completion and offer a workflow to overcome the missing data and challenges for analysis. Secondly this work customs a blend of different analytical approaches such as PTA, RTA, Material Balance combined with Teager-Keiser Energy Method to understand the many unknowns and uncertainties of water injection effectiveness in one of the heavily faulted multi-stack reservoirs in East Malaysia.

For a proper reservoir characterization, knowing of accurate rate is a must, yet an accurate allocation itself is a function of formation properties, mainly permeability and skin. With the help of scripting, data from PDG is compiled. Preprocessing has been done to identify the fluid type produced from each layer. A workflow has been introduced to tackle the back allocation issue with FCV variation while allowing the luxury of full dynamic characterization of multi-stack reservoirs producing from single string. While every analytical approach has its own limitations and strengths, this work showcased how to apply different methods depends on the situation to squeeze the maximum information whether is to understand the injector-benefiter pairing, fault sealing and compartmentalization, connected volume, or fine migration and loss of injectivity.

Processing of PDG big data made it possible for a dynamic interpretation of whole production period rather than selective time span. This work made us able to answer some of the last longing question such as the cause for injectivity deterioration, proper reservoir characterization aligned with geological understanding, and proper allocation suggested by new workflow. PTA results have been validated along other analytical methods such as RTA and material balance to understand connected volume, fault transmissibility and infill well potential. Teager-Keiser showed extremely helpful when combined with previous methods to recognize benefiter-injector pairing before any lagging evidence such as GOR and pressure trend, water production and salinity test can confirm the connectivity.

Apart from the workflow to interpret the PDG of smart well completion producing commingled from multi-stack reservoirs, the work has been benefited from digitalization using open-source programming. The idea of dynamic data interpretation, how to deal with missing production data to enhance the accuracy of PTA analysis, and cross-validation through different approaches to shed light on the unknown of reservoir complexities to revisit and optimize water injection scheme, are the other highlights of this study.