Optimization of Conformance Decisions Using a New Well-Intervention Simulator

Abstract

Abstract For many years, operators and service companies have applied conformance treatments without adequate methods to verify treatment efficiency, since complexities of the treatment and reservoir systems have made attempts to quantify the effects of these conformance solutions with available tools unreliable. A comprehensive database had been developed with help of several operating companies of conformance treatments that were performed by several service companies over 30+ years. This database shows that in the absence of proper diagnostics and analysis, the success of a conformance treatment usually hovers around 50% even in well established areas. Application in new areas usually fares significantly worse, with a success ratio of 30% or less. An important reason for this unacceptable situation is the tendency to design a conformance treatment without adequately considering reservoir effect. In this paper, we present a methodology and a numerical simulation approach that are aimed at improving the success ratio of conformance treatments. Optimum conformance treatments must consider:placement techniques,treatment size,reservoir temperature and pressure effects, andtracking of conformance fluid-property changes with time and temperature. To adequately design a conformance treatment, it is important to predict both pressure and temperature profiles inside the wellbore and the reservoir. Using a numerical simulator that couples the wellbore with the reservoir provides a very efficient means for developing a methodology to optimize conformance treatments. Simulated examples are given to shed insight into basic conformance phenomena such as coning and channeling. Most importantly, two field cases are presented to demonstrate practical application of the developed methodology for designing an optimum conformance solution. This new methodology reduces operational and economic risks associated with conformance treatments. It also allows for optimization of these treatments through more accurate prediction of water and hydrocarbon production. Introduction Conformance technologies, which in a broader sense involves techniques for controlling the amount of unwanted water and/or gas production in a field, have been in practice for at least half a century.[1,2] During this period, a variety of approaches have been applied to improve recovery of petroleum reserves, including the use of sealants and relative permeability modifiers (RPM), as well as application of different chemical systems - polymers, monomers, cement, etc. There are two key components, among others, of an effective conformance control technology:proper chemical (polymer gel) selectionproper placement of the selected chemical system The industry is replete with all kinds of chemical systems for conformance control. However, proper placement of these chemicals at the right places inside the reservoir for effective control of unwanted water or gas production has remained elusive for a long time, due in part to the lack of better design tools for diagnosing the actual conformance problem in any specific situation. Many authors have described the need for proper diagnostics in order to ensure optimal conformance control.[3–5] Dependence of the success of any conformance treatment on the accurate determination of types and locations of reservoir fluids was also emphasized in Reference [6]. Soliman et. al., in that paper, noted that determining the accurate locations of mobile water or unwanted formation gas is essential to the success of any effective conformance control process, and the fact that this goal could only be achieved through early integration of multiple technologies. One could roughly divide the stages involved in a traditional conformance treatment into the following four categories:Pre-diagnostic evaluation, which consists of candidate selection and the gathering of a complete data set including production history, economic analysis, logs, production tests, and a decline history.Diagnostic evaluation, which includes the gathering of data from reservoir monitor logs, water flow logs, production logs, cement evaluation logs, pipe inspection logs, and video.Analytical and numerical evaluation, which can include multi-rate injection with profile analysis, pump-in testing, laboratory analysis/evaluation, and placement design and evaluation using analytical and/or numerical tools - including the new well-intervention simulator proposed in this paper.Treatment, which might include application of sodium silicates, in-situ polymerized monomers, polyfood solutions, polyacrylamide gels, organic gels, combinations of gel/cementing solutions, cements, micro matrix slurries, diesel based micro matrix slurries, foam cement, in-situ polymerized and preformed relative permeability modifiers.