Horizontal Steam Injection Flow Profiling Using Fiber Optics

Abstract

Steam conformance control in horizontal injectors is important for efficient reservoir heat management in heavy oil fields. Suboptimal conformance and non-uniform heating of the reservoir can substantially impact the economics of the field development, oil production response and result in non-uniform steam breakthrough. In order to achieve the required control, it is essential to have an appropriate well completion architecture and robust surveillance. Five fiber optic systems, each utilizing a unique steam conformance control completion configuration, have been installed in two horizontal steam injectors to help mature steam injection flow profiling and conformance control solutions. These fiber optic systems have utilized custom designed fiber optic bundles of multimode and single mode fibers, for distributed temperature sensing (DTS) and distributed acoustic sensing (DAS) respectively. Fiber optic systems were also installed in a steam injection test flow loop. All the optical fibers successfully acquired data in the wells and flow loop, measuring temperature and acoustic energy. A portfolio of algorithms and signal processing techniques were developed to interpret the DTS and DAS data for quantitative steam injection flow profiling. The heavily instrumented flow loop environment was utilized to characterize DTS and DAS response in a design of experiment matrix to improve the flow profiling algorithms. These algorithms are based on independent physical principles derived from multiphase flow, thermal hydraulic models, acoustic effects, large data array processing, and combinations of the foregoing methods for both transient and steady state steam flow. A high-confidence flow profile is computed based upon convergence of the algorithms. The flow profiling algorithm results were further validated utilizing a dozen short-offset, injector observation wells in the reservoir that confirmed steam movement near the injectors.

A Survey on Distributed Fibre Optic Sensor Data Modelling Techniques and Machine Learning Algorithms for Multiphase Fluid Flow Estimation

“…Using the DTS trace, the identification of the annular-fluid interfaces (brine/gas, gas/flowing gas) was possible, as well as the depths of active lifting points. Shirdel et al [ 89 ] employed several signal processing algorithms, including DAS spectrogram, DTS and DAS waterfall analysis, and steady-state injection, to interpret the DTS and DAS data to provide a quantitative step-injection-flow profiling. It shows that those algorithms are tied together with an independent physical principle related to multiphase flow, acoustic effects, data array, and others.…”

Integrating Fiber Optic Data in Numerical Reservoir Simulation Using Intelligent Optimization Workflow

“…DTS has been employed for reservoir monitoring since the 1990s for a variety of applications including SAGD [13,14] water and gas injection [15], horizontal well production [16], oil and gas flow profiling [17], steam breakthrough identification [18], and determination of flow contribution of each zone in a multi-zone reservoir [19]. Some of the common techniques for measuring and interpreting the injection profile with DTS are summarized by [20][21][22][23]. DTS was also used for a steam injection project to identify steam zone development and numerical approach was used to estimate flowrate profile from the temperature profile [24,25].…”

Injection profiling in horizontal wells using temperature warmback analysis

“…Different analysis techniques are introduced for both qualitative and quantitative analyses of temperature data to investigate the uniformity of injection rate along horizontal wells. Storage analysis is a temperature data-based qualitative analysis in which the temperature data acquired during injection and shut-in periods are plotted in space-time plot, called the "waterfall" chart [18]. During non-isothermal fluid injection (i.e., water flooding), the temperature of the swept region cools down due to the temperature contrast between the initial reservoir temperature and the injected fluid temperature.…”