Temperature Modeling and Analysis of Wells with Advanced Completion

Abstract

Advanced completions using technologies such as Inflow Control Devices or Interval Control Valves are successfully optimising oil and gas production. They are often accompanied by the installation of Distributed Temperature Sensors and Permanent Downhole Gauges, providing continuous, real-time monitoring of the downhole pressure and temperature. Interpretation of such data to locate influxes and to track zonal inflow performance is an important step towards a comprehensive well and field control strategy. Interpretation of these downhole measurements requires accurate modelling of the well's pressure and temperature. Modelling of the pressures associated with the production of wells with advanced completion has been available for sometime. However, the workflow required for temperature modelling is not yet complete. This paper discusses using available theoretical models and software tools to model the temperature distribution in wells with advanced completion. The strengths and weaknesses of the various approaches for data interpretation will be discussed. Several methods for the quantitative interpretation of downhole temperature measurements are proposed. The application of both currently available and novel theoretical models will be discussed. The workflow will be shown to be capable of providing both zonal flow rates and phase compositions. The interpretation and analysis techniques presented here form the basis of a well and/or field monitoring and production control workflow. 1.0 Introduction The installation of advanced well completions is increasing in popularity 1,2 worldwide. One of the main priorities of these technologies is the creation and improvement of hardware for monitoring, managing and controlling the well inflow at the level of an individual zone. The control capabilities of these devices can be subdivided into active {Interval Control Valves (ICVs)} and passive {Inflow Control Devices (ICDs)} while autonomous ICDs combine features from both devices. They are able to solve a wide range of fluid production problems 3,4. ICDs are installed to ensure a uniform production or injection profile along the complete completion length of the well, thus delaying breakthrough, improving clean-up, optimizing injection or steam-assisted gravity drainage, etc. ICVs are being used for recovery optimization in complex reservoirs and/or wells where the completion is required to dynamically respond to changing and uncertain production behaviour 5. Efficient inflow (or outflow) control rests on the availability of an advanced monitoring system which provides real-time values of the phase flow distribution in the well. Modern downhole monitoring devices, installed as part of the advanced completion, provide sufficient information that they, along with the flow control hardware, form the basis of the intelligent field. Advanced monitoring technologies, such as optical fibre based Distributed Temperature or Pressure Sensors (DTS or DPS), Permanently installed Downhole Gauges (PDG), multiphase flow meters, etc., produce large amounts of downhole data in real-time 6,7. Traditional analytical approaches have proved to be insufficient to retrieve useful information from the vast quantities of downhole data provided by the increasing employment of temperature and pressure measurement sensors. The realisation that temperature behaviour is a complex process that has had less research attention than its pressure counterpart resulted in the initiation of research in this area of petroleum data processing and analysis. A significant part of this effort has been directed towards the analysis of temperature data to evaluate flow rates and phase distributions at specific points along the completion's length In this paper we will discuss the success of several available analytical and simulation tools to accurately model steady-state, temperature and pressure profiles in wells. The ability to estimate phase rates in wells completed with ICDs and/or ICVs will be discussed. We will also present several novel analytical solutions on reservoir temperature distribution calculation. Finally a group of calculation methods to estimate inflow and permeability distributions and flow rate profiles will be presented.

Early-time Asymptotic, Analytical Temperature Solution for Linear Non-adiabatic Flow of a Slightly Compressible Fluid in a Porous Layer

“…Temperature changes in the flowing reservoir induced by heat convection are much higher than those induced by heat conduction in the reservoir. This has been discussed and confirmed (Muradov 2010).…”

“…The full derivation can be found in (Muradov 2010). The full solution image in Laplace and fourier spaces for the well-temperature is:…”

Computing flow profiles and total flow rate with temperature surveys in gas wells

“…Over the last few years, DTS has gained significant attention in the context of completion in various settings, including in long-horizontal wells. Some of these contributions include those of Glasbergen et al (2009), Tan et al (2011), Muradov and Davies (2009), Kerem et al (2008), among others.…”

Determining multilayer formation properties from transient temperature and pressure measurements in gas wells with commingled zones

“…In Li's work, streamline simulation technique was used in forward modeling to speed up forward model simulation. Some other researchers focus on perfecting the wellbore/reservoir thermal model to simulate the reality and complexity of well completions (Almutairi and Davies, 2008;Muradov and Davies, 2009). All the models mentioned above are helpful for the industry to interpret downhole temperature measurements, and most of them addressed the usefulness of the distributed temperature data in flow profiling.…”