Prediction of Injection-Fluid Distributions for Multiple Zones—Intelligent Injection System

Abstract

Injection fluid distributions present a challenge for the applications of multi-zones intelligent well injection systems. This paper presents two approaches to fulfill this need. The first approach is to apply the available downhole real-time data to calculate fluid distribution based on the existing single phase flow modeling and flow coefficient (Cv) test data of down-hole Interval Control Valve (ICV). For this method, a fluid distribution model for a multi-zone intelligent injection system is derived, and an example of the application of the first method is presented. For the second approach method, zonal reservoir pressure/temperature and injectivity data are considered in the fluid distribution calculation. This method is based on a balanced pressure-system approach. In this paper, each of these fluid distribution prediction methods considers the choke setting of the multi-position ICV, the completion string's geometric sizes, injection fluid characteristics, available wellhead pressure/temperature data, and the reservoir pressure/injectivity data (or measured down-hole real-time data) to do the fluid distribution prediction. To demonstrate these methods, a hypothetical example of a two-zone intelligent water injection case is illustrated in this paper. The example shows how to use the wellhead pressure/temperature data, zonal reservoir pressure/injectivity data (or measured down-hole real-time pressure/temperature data), with completion string's geometry sizes and ICV positions to predict injection fluid distributions through each zonal ICV. An intelligent injection system operation analysis has been presented based the theoretical models and illustrated example. The technical contributions of this paper include:Present mathematical models which apply the available downhole real-time data to calculate fluid distribution.Propose a balanced pressure-system search method which applies the zonal reservoir pressure and injectivity to calculate fluid distribution.Present an intelligent injection system operation analysis, which reveals the key roles of changing ICV position and wellhead pressure in the controlling of injection fluid distributions.Present an effective way to handle down-hole real-time data for intelligent injection system. Introduction The use of intelligent completions to control injected fluid distribution in multi-zone wellbores has increased significantly as operators to optimize reservoir management and maximize hydrocarbon recovery1–3. Predicting and controlling injection fluid distribution through zonal ICVs into each reservoir unit presents a challenge for operators of a multi-zone intelligent injection well. However, comparably, little research has been published in this area. A simple and accurate mathematical tool/method has been developed to estimate the amount of injection fluids to each reservoir unit based on available well-bore, fluid and well strings data, including the setting of the zonal ICVs, production strings geometry size, injection fluid properties, wellhead P/T data and zonal reservoir pressure/injectivity data (or measured down-hole real-time data). Typical Two-Zone Intelligent Injection System and Available Real-Time Data A Typical Two-Zone Intelligent Injection System. Fig.1 is an illustration of a typical two-zone intelligent injection system. Two ICVs are installed to control the injection fluid distribution. In Fig.1, the upper ICV is used to control the injection fluid rate to the upper zone; the lower ICV is used to control the injection fluid rate to the lower zone. The lower zone ICV is shrouded to separate the injection fluid of both zones.

Intelligent Well Completion Technology Enables Selective Injection for Pressure Maintenance in Mature Field in the South China Sea

“…Guidelines for design and prediction of water injection using intelligent well completions have been documented (Sun et al, 2006;Allen et al, 2010). A key component for the pre-job planning and design of this completion was the choke trim that would be incorporated into the ICV.…”

MODEL-BASED OPTIMIZATION OF ICVs’ CONTROL FOR PRODUCERS, INJECTORS, AND WAG-CO2 CYCLES SIZE IN A CARBONATE RESERVOIR UNDER UNCERTAINTY

“…This process that combines the injection of CO 2 and natural gas during gas injection cycles is called WAG-CO 2 process (Afzali et al, 2018;Lopes et al, 2022). Several authors report the benefits of WAG, also relating this technique with decisionmaking and optimization processes (Chen et al 2010;Jeong et al, 2014;Valeev & Shevelev, 2017;Pal et al, 2018;Pereira et al, 2021).…”

“…The ICVs, in turn, are part of the so-called intelligent wells, which consist of downhole valves installed in different segments (zones) of the wells, and can be operated remotely (Al-Khelaiwi et al, 2010). These valves act to restrict and control the fluid flow in these separated segments of the wells (Sun & Konopczynski, 2006;Abreu et al, 2015). Though reported as a successful device, the operation of the ICVs aiming to achieve the optimal response of the field performance is not a simple task.…”