Radio Frequency Heating Simulation Using A Reservoir Simulator Coupled with Electromagnetic Solver for Soil Remediation

2021 ◽  
Author(s):  
Xiaoyue Guan ◽  
Gary Li ◽  
Hanming Wang ◽  
Shubo Shang ◽  
Timothy Tokar ◽  
...  

Abstract Radio frequency (RF) heating is recognized as a technique having the potential to thermally enhance remediation of hydrocarbon-impacted soil. RF heating delivers electromagnetic (EM) power to a targeted body of soil, resulting in an increased soil temperature that enhances the in-situ remediation processes such as biodegradation. Antennas are placed either on the ground or installed in the soil near the ground surface. The antennas operate in the hundreds of kHz to MHz range. To model the RF heating process, we successfully coupled a reservoir simulator with a 3-dimensional (3D) EM solver to evaluate the ability of RF technology to heat soil in situ. The coupled reservoir/EM simulator solves the EM fields and associated heating for a heterogeneous reservoir or soil volume in the presence of multiple antennas. The coupling was accomplished through a flexible interface in the reservoir simulator that allows the runtime loading of third-party software libraries with additional physics. This coupled workflow had been previously used for studying RF heating for heavy oil recovery (Li 2019). An RF heating simulation case study was performed in support of a soil remediation field test designed to demonstrate the ability to heat soils using EM energy. The study included field test data analysis, simulation model building, and history matching the model to test data. Results indicate, on average, the soil was heated ∼2-3°C above the initial formation temperature after approximately two days (52 hours) of RF heating. We found that the RF heating was local, and our simulation model, after tuning input parameters, was able to predict a temperature profile consistent with the field test observations. With properly designed RF heating field pilots and tuning of EM and reservoir parameters in simulation models, the coupled reservoir/EM simulator is a powerful tool for the calibration, evaluation, and optimization of RF heating operations.

1999 ◽  
Vol 33 (7) ◽  
pp. 1092-1099 ◽  
Author(s):  
Sa V. Ho ◽  
Christopher Athmer ◽  
P. Wayne Sheridan ◽  
B. Mason Hughes ◽  
Robert Orth ◽  
...  

SPE Journal ◽  
2020 ◽  
Vol 25 (03) ◽  
pp. 1443-1461
Author(s):  
Travis Ramsay

Summary In-situ pyrolysis provides an enhanced oil recovery (EOR) technique for exploiting oil and gas from oil shale by converting in-place solid kerogen into liquid oil and gas. Radio-frequency (RF) heating of the in-place oil shale has previously been proposed as a method by which the electromagnetic energy gets converted to thermal energy, thereby heating in-situ kerogen so that it converts to oil and gas. In order to numerically model the RF heating of the in-situ oil shale, a novel explicitly coupled thermal, phase field, mechanical, and electromagnetic (TPME) framework is devised using the finite element method in a 2D domain. Contemporaneous efforts in the commercial development of oil shale by in-situ pyrolysis have largely focused on pilot methodologies intended to validate specific corporate or esoteric EOR strategies. This work focuses on addressing efficient epistemic uncertainty quantification (UQ) of select thermal, oil shale distribution, electromagnetic, and mechanical characteristics of oil shale in the RF heating process, comparing a spectral methodology to a Monte Carlo (MC) simulation for validation. Attempts were made to parameterize the stochastic simulation models using the characteristic properties of Green River oil shale. The geologic environment being investigated is devised as a kerogen-poor under- and overburden separated by a layer of heterogeneous yet kerogen-rich oil shale in a target formation. The objective of this work is the quantification of plausible oil shale conversion using TPME simulation under parametric uncertainty; this, while considering a referenced conversion timeline of 1.0 × 107 seconds. Nonintrusive polynomial chaos (NIPC) and MC simulation were used to evaluate complex stochastically driven TPME simulations of RF heating. The least angle regression (LAR) method was specifically used to determine a sparse set of polynomial chaos coefficients leading to the determination of summary statistics that describe the TPME results. Given the existing broad use of MC simulation methods for UQ in the oil and gas industry, the combined LAR and NIPC is suggested to provide a distinguishable performance improvement to UQ compared to MC methods.


Author(s):  
Feng Zhang ◽  
◽  
Fang He ◽  
Xiaojin Zhou ◽  
Wei Zhao ◽  
...  

Microbial contamination is currently a major safety issue in low moisture foods. Current sterilization and pasteurization practices, such as conventional thermal processing involving conductive heat transfer to inactivate pathogens, appear inadequate to address the contamination problem in low-moisture foods, which require long time heating, leading to quality deterioration with significant loss of colour and flavour. Radio Frequency (RF) heating has great potential in pasteurization of low moisture foods and offers the possibility to rapidly inactivate microorganisms while maintaining the food quality. Aniseed powder as one of typical low moisture foods possesses significant risk of microbial contamination. This study was to develop RF heating process to inactivate microorganisms in aniseed powder. The dielectric properties (i.e. dielectric constant (ε') and dielectric loss factor (ε'')) of aniseed powder, the influences of processing conditions on heating properties and the inactivation of microorganisms in aniseed powder were all studied in this research. Results showed that ε' and ε'' of aniseed powder decreased with an increase in frequency from 6.78 MHz to 47.46 MHz but then fluctuated between 300 and 2745 MHz. The overall change of ε' and ε'' ultimately exhibited a downward trend. Under a constant frequency treatment, ε' and ε'' of aniseed powder increased with an increase in moisture content, whereas the penetration depth decreased. Particle size showed no significant effects on the dielectric properties, heating rate and penetration depth. With an increase in RF processing time, the heating rate of the sample increased and adding the rolling-over operation step helped to improve the uniformity of RF heating. After processing for 100 s, the temperature of aniseed powder could increase to 60 °C, and the number of microorganism in aniseed powder was reduced by 6.18 logs when time extended to 150 s.


1999 ◽  
Vol 33 (7) ◽  
pp. 1086-1091 ◽  
Author(s):  
Sa V. Ho ◽  
Christopher Athmer ◽  
P. Wayne Sheridan ◽  
B. Mason Hughes ◽  
Robert Orth ◽  
...  

2019 ◽  
Author(s):  
Lyndsay B. Ball ◽  
◽  
Andrew H. Manning ◽  
Jeffrey L. Mauk ◽  
Bradley J. Carr ◽  
...  
Keyword(s):  

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