DESC0024807

The liquid/vapor fraction, which is used to calculate production rate, is one of the most important parameters to monitor in real-time yet facing technological challenges. None of the state-of-the-art technologies can precisely measure the water/steam fraction in real time for an individual well at a relatively low cost. The geothermal system itself is hard to control precisely in terms of fluid flow rate and heat transfer, and homogeneity, which adds more complexity to the water/steam two- phase flow generated from a geothermal production well. This Phase 1 program will develop and test a real-time sensor to measure the flow rate and the water/steam fraction from geothermal wells. Sensor technology to measure density, pressure, temperature, and velocity have been well advanced in the past a few decades. Two-phase flow homogenization devices have been investigated and applied in other chemical processing industries. If the advanced sensor technology and the two-phase flow homogenization technology can be combined, we shall be able to develop a water/steam fraction sensor and install it in a homogeneous non-steady two-phase flow environment to measure flow data of each individual production well in real-time. Here, Reaction Engineering International (REI) is teaming up with Energy & Geoscience Institute (EGI) at the University of Utah to develop a novel approach to accurately measure the water/steam fraction in a geothermal production well in real-time, where an accurate measurement of the density of the mixture is critical yet challenging due to the non-homogeneous and non-steady two-phase flow feature of the fluid coming out the production well. To address this challenge, we propose two combined approaches to assure the accuracy of the system to be developed: 1) we will develop, design, and engineer a homogenization device, which is to produce a homogeneous water/steam two-phase flow. The sensor system will be installed at a proper location downstream of the homogenization device, where the properties of a uniform stream can be obtained; 2) we will develop an effective data processing strategy (software) to process the raw data, where proper averaging scheme will be developed and verified. In the Phase 1 program, we will design and develop the sensor system, verify it in bench-scale and field tests, and complete preliminary economic and marketing evaluations. The results of this research will have immediate application to geothermal power plants, and will provide critical information that will be used for power plant optimization. The large datasets that will be produced from real-time measurements from multiple wells can be leveraged within machine-learning based optimization software to optimize strategies for selection of injection vs. production wells as well as other approaches to improve overall well production and power plant performance. It will also have direct application to other processes that involve steam/water mixtures.