Laser applications provide unique advantages to applications in discovery, recovery, and production of hydrocarbons. A comprehensive numerical model would enable prediction, optimization, increase efficiency, enhance control, and further innovation. This work reviews the modeling methods, discusses key variables and physics, presents results, and introduces innovative solutions that make use of machine learning and artificial intelligence to solve an inherently multi-scale and multi-physics problem. Two possible methods have been explored to model laser-rock interaction: mechanistic and statistical — the former uses as a set of coupled partial differential equations that adequately describe the physics involved. The statistical method uses advanced statistical analysis and supervised-learning to elucidate relations between the experimental settings and observations. The full-physics or mechanistic model was developed using finite-element and finite-difference methods; it incorporates coupled solvers for electromagnetic, thermodynamics, and geomechanics. The statistical model uses advanced statistical analysis and machine learning to characterize the dynamics and build a prediction algorithm. A numerical model of laser-rock interaction must comprise physical dynamics that span over different time and spatial scales. When a laser beam impinges on a rock, a portion of the incident energy is absorbed as thermal energy, and a thermal gradient is created. The result is a distribution of physical and chemical changes such as spallation, melting, dissociation, calcination, or vaporization. The full-physical model can adequately capture the transient process; however, it requires a functional characterization of the dynamic rock properties, environmental conditions, and laser parameters. The statistical approach provides a prediction of the overall outcome of the process departing as a function of known input parameters, yet its precision depends on the availability of experimental data (outcomes and conditions). Key parameters are identified using statistical analysis. The modeling results agreed with experimental tests. Further, they evince that thermal properties and geomechanical stresses configuration have a significant impact on the process’ outcome. These methods can optimize and predict the interaction for multiple applications, ranging from heat treatment to stimulation. Subsurface laser operations could provide the next generation of stimulation and workover tools for Oil and Gas. Numerical models of laser-rock interaction are essential to predict, optimize, adapt, and evaluate subsurface laser applications during development, test, and operation. This work provides a basis for the development of future numerical models and enables the next generation of subsurface photonic tools.
This paper presents the strategy and execution that led to the industry's first successful deployment of a high-power laser in the field. The development encompassed various aspects: administration, technical, lab-to-field transformation, and intensive research. One of the primary success factors was identifying potential technologies and forecasting their evolution. High-power lasers were selected for the upstream applications because of their capabilities and successful use in almost every industry, ranging from medical to the military; it attracted the industry due to its unique features, such as precision, reliability, control, and accuracy. High-power lasers at the early stage (generation) were not applicable for downhole applications due to their relatively lower power levels. However, it has been utilized widely in several applications, such as sensing, measurements, and others. The objective of this program is to utilize the new generations of higher-power lasers in several upstream applications. The program is strategically designed to reduce the risk and increase success. In the initial stage, the work focused on the feasibility and characterization of intervening physics. The goal was to answer fundamental technical questions, such as "can lasers penetrate all types of rocks? What are the limitations? What is the effect of the laser on rocks?" The research spanned the last two decades, culminating in the development of the first field prototype of a high-power laser system. The work proved that near-infrared multi-kilowatt lasers (hereon high-power lasers or HPL) could perforate and process any rock type at different conditions, including in-situ testing and liquid environments. The experimental plan was designed systematically and divided into phases, starting from fundamentals to advance. Prototype tools were designed, tested, and upscale for field deployment. All applications can be performed with the same HPL source -only the optical head needs to be changed. High-power laser technology is an alternative to conventional methods of subsurface energy extraction, such as perforation, descaling, and drilling. It is cost-effective, compact, versatile, waterless, energy-efficient, and environmentally friendly, thus enabling sustainable field operations.
This work examines the physical principles and effects of high-power laser (HPL) descaling of surface equipment. This contactless technique can fully remove sulfide or calcium carbonate scale without compromising the integrity of the substrate. The method is environmentally friendly, waterless, and energy efficient. It could do away with chemical and mechanical methods for descaling, which have shown low efficiency treating fully-plugged deposits and environmental risks due to chemical use. This paper describes the process through an analysis of its efficiency and impact on the substrate material, the environment, and the implications to production reliability. HPL descaling is described by a multiphysics approach that involves thermal and mechanical processes. The laser causes a phase-change on all or some of the constituents of the scale. This interaction results in spallation, dissociation, and at high energy sublimation. Laser-matter interaction is precise. It produces a small heat affected zone (HAZ) that decays exponentially away from the illuminated area. Thus, the effect of the laser on the surrounding material is minimal to none. Ultrasonic, multi-spectral imaging, microscopy, and statistical analysis are used to analyze the effect of the laser on the substrate material. The environmental impact of the HPL process is compared to existing methods; it is calculated via the carbon intensity of each step and supporting equipment involved in the processes, as well as by its impact to material reuse, waste reduction, and recycling. Scaling can be detrimental to oil and gas production because it may hinder the flow of fluids from and to the well. In surface systems, scale deposits reduce the internal diameter of equipment, thus limiting flow-rate capacity and causing pressure drops across the production network. From a physics perspective, the process is effective because the energy can be delivered with extreme precision on the target. The efficiency of the process depends on the coupling of the HPL with the target and the rate of debris evacuation. The physics are complex but can be optimized through machine learning (e.g. reinforcement learning). The results of the comprehensive characterization demonstrate that HPL descaling preserves the integrity of the substrate. HPL descaling could increase the lifetime of surface equipment affected by scale, and hence contribute to reuse and recycling. The adverse effects of scaling make prevention and removal crucial to the energy industry. Existing methods of scale-removal rely on mechanical or chemical scrubbing, which show varying degrees of success and may deteriorate the substrate. HPL descaling is an environmentally-friendly solution for production reliability; it enables complete descaling and the safe reuse or recycling of scaled equipment.
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