The SPE has split the former "Management & Information" technical discipline into two new technical discplines:
- Data Science & Engineering Analytics
The SPE has split the former "Management & Information" technical discipline into two new technical discplines:
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Liang, Guangyue (Research Institute of Petroleum Exploration and Development, CNPC) | Xie, Qian (Research Institute of Petroleum Exploration and Development, CNPC) | Liu, Yang (Research Institute of Petroleum Exploration and Development, CNPC) | Liu, Shangqi (Research Institute of Petroleum Exploration and Development, CNPC) | Xia, Zhaohui (Research Institute of Petroleum Exploration and Development, CNPC) | Bao, Yu (Research Institute of Petroleum Exploration and Development, CNPC) | Zhou, Jiuning (Research Institute of Petroleum Exploration and Development, CNPC)
Abstract It is very difficult to realize good economy returns using conventional SAGD process in many oil sands projects due to large CPF investment, massive steam injection, expensive surface diluent adding and increasing carbon emission tax. By contrast, warm solvent assisted gravity drainage process (WSAGD) is a promising low-carbon technology to deal with these SAGD challenges. This paper conducted feasibility evaluation by combined with Nsolv Best pilot analysis and a series of physical simulations. From 2014 to 2017, WSAGD pilot was successfully carried out by injecting butane at 60℃ in Suncor Dover oil sands. Its reservoir geological characteristics, physical properties, development technology policy and production performance were systematically analyzed. Combined with 4D seismic interpretation, RST and observation well data, the size and growth rate of solvent chamber were monitored and analyzed. Considering great uncertainty in numerical simulations influenced by many factors including grid size, solvent diffusion coefficient, interfacial tension and capillary force, a series of experimental tests and physical simulations were conducted. The behavior of viscosity reduction, interfacial tension reduction and microscopic oil displacement related to different solvents were systematically tested including propane, butane, pentane and hexane. Particularly, the performance of SAGD and WSAGD process were evaluated by 2D and 3D visual physical simulations. In Nsolv Best pilot, the target reservoir is low pressure, thin and shallow buried. The oil rate reached 250-300 barrels per day under 300 m horizontal section, and API degree of produced oil was upgraded to 13-16 from original 8. After 3 years of tests, the width of solvent chamber is 40-60m, lateral and vertical 1.56 m and 0.96 m per month, and horizontal conformance is 67%. The experiments results show that viscosity reduction trend will flatten out when the solvent concentration exceeds 10 vol% due to partial asphaltene precipitation. Both sweep efficiency and displacement efficiency of hot water, steam, gaseous and liquid hexane are increasing with temperature increase. Compared with other medium, sweep efficiency and displacement efficiency of gaseous hexane are higher due to greater dissolving ability and speed in bitumen. Both 2D and 3D experimental results indicate that WSAGD process achieves faster vertical solvent chamber and higher recovery factor than conventional SAGD process. Besides, gaseous pentane has significant upgrading effect considering substantial reduction of asphaltene and resin in the produced oil, which is not available in conventional SAGD process. This paper first systematically compares the mechanisms and performance of warm solvent assisted gravity drainage (WSAGD) process with SAGD process by physical simulations. It presents a promising low-carbon technology to enhance oil recovery, partially upgrade the produced oil and reduce carbon dioxide emissions in developing super-heavy oil or oil sands project.
Completions Optimization and Technology Award The Completions Optimization and Technology Award of the Society of Petroleum Engineers recognizes outstanding achievement or contributions to the advancement of petroleum engineering in the area of completions optimization and technology. This technical discipline covers tubing and casing design, completion equipment, formation isolation, hydraulic fracturing and gravel packing, sand control, acidizing, completions monitoring and optimization, completions evaluation including logging, imaging, and wellbore seismic and fundamental research in completions. Data Science and Engineering Analytics Award The Data Science and Engineering Analytics Award of the Society of Petroleum Engineers recognizes outstanding achievement or contributions to the advancement of petroleum engineering in the area of data science and engineering analytics. Drilling Engineering Award The Drilling Engineering Award of the Society of Petroleum Engineers recognizes outstanding achievement or contributions to the advancement of petroleum engineering in the area of drilling engineering technology. This technical discipline covers drilling equipment, operational environment, downhole operations, site operations, drilling design and analysis, and drilling management.
Abstract Most companies to date have adopted GHG emission targets in an effort to limit global warming well below 2 °C above pre-industrial levels, and 2020 estimations forecast a decrease of about 1/3 of emissions from O&G activities by 2050. It is also foreseen that regulations with economic impact on emissions from hydrocarbon production will be progressively adopted. This is triggering oil and gas (O&G) attention to find faster and economic ways to decarbonize while maintaining operational performance. Several types of initiatives are being considered including the reduction of flaring and venting, mitigation of methane leaks, increasing efficiency in energy use, use of renewable energy, and electrification of processes, in combination with the use of digital tools, and advanced monitoring to optimize performance. In this work we focus on a comparison of different decarbonization pathways for an offshore platform. It is assumed that the platform is already in place and in operation, and that the industry is already taking the required actions to reduce flaring and venting and mitigating methane leaks. The analysis starts by identifying the major contributors to the GHG emissions from the platform, which in this case is the power system, followed by fluid related processes like compression, separation, heating for transportation, and other associated operations. Public data from international energy agencies indicates that approximately 16 TWh/year is used to power offshore oil and gas platforms globally. We analyze the following five decarbonization pathways: a) improved energy use - decreasing the energy demand of the processes running on the platform and associated operations, b) increasing the efficiency of the power generation source, c) changing the nature of power source (renewable – wind, solar, wave, hybrid systems), d) implementing carbon capture units, and e) electrifying the facility (partial/full electrification cases). The analysis includes a comparison of promising concepts under each of the proposed pathways and summarize the challenges and opportunities offshore O&G operators have to implement them. Some of the alternatives are based on technology already used in the oil and gas industry, or in other industries, while in some others the technology is still under development. Reference is made to novel technology with potential to address the identified challenges for the different pathway options. We use a simplified metric system to highlight the most effective solutions according to location of the platform and its distance to shore. A discussion of what we will be needed for such pathways to be feasible is also presented.
In February 2023, the Society of Petroleum Engineers (SPE), together with the American Association of Petroleum Geologists (AAPG) and the Society for Exploration Geophysicists (SEG), conducted a 1-day symposium on the energy transition. The invitation-only event, hosted by the Canadian embassy in Washington, DC, was designed to inform and engage policymakers and the policy community in the US capital from the perspective of the engineers and geoscientists who currently work to supply 60% of the world's energy. "The purpose of this event is to share information so that policymakers can make more informed choices," said Mark Rubin, SPE's chief executive officer. "The members of our professional societies understand the challenges [of the energy transition] and also understand that they have an important role in addressing these challenges." Chaired by Allyson Book of Baker Hughes with co-chair Jim Slutz of the National Petroleum Council, the program's topics ranged from existing to emerging energy sources--the technologies that exist today and those that may be commercialized in the future.
Abstract As the world shifts at fast pace towards new energy scenarios, the offshore environment is attracting extensive new project developments that pose new challenges in the management and the protection of marine ecosystems. In parallel, the recent geopolitical situation has exposed the compelling need to guarantee the integrity of subsea critical energy infrastructure calling for new paradigms to efficiently perform complex periodic inspections and intervention tasks. All these factors are driving a rapid evolution of subsea robotics, enabled by the advancement of emerging technologies, such as artificial intelligence, which have now reached a sufficient maturity level for industrial deployment. Within these innovation scenarios, underwater intervention / inspection drones (UIDs) are rising to offer the most promising answers to the needs of the offshore industry. This new family of underwater robots presenting AUV/ROV hybrid capabilities, enable new attractive operational paradigms that are already being positively recognized by the offshore industry. The use of UIDs, particularly when permanently integrated into fields (topside or as subsea resident) could greatly contribute to reducing the costs and risks normally associated with subsea inspection activities. The scope of this paper is to offer an overview of UIDs and provide the necessary elements to take full advantage of this technology, supporting the environmental sustainability of future offshore projects and activities. The investigation provided, explores conventional applications for oil and gas and then extends to future new energies, deep-sea mining and CO2 capture and storage projects. The analysis starts from UIDs state-of-the-art technology and moves to explore possible application scenarios in the attempt to anticipate possible solutions and related technical gaps.
Abstract Uruguay is at the forefront in the use of renewable energy sources and has almost totally decarbonized its electricity matrix, reducing its dependence on fossil fuels. The country is advancing into a second energy transition, including the development of a green Hydrogen (H2) economy. This work presents the Analogies from the Exploration & Production (E&P) business model applied for green H2 developments offshore Uruguay. Considering the sovereignty Uruguay has in activities such as the production of energy from wind in its Exclusive Economic Zone (EEZ), the Uruguayan NOC has based its vision for a sustainable future on the H2U Offshore Round, for which it will offer offshore areas on bidding rounds for energy companies to carry out feasibility studies and potential installation of infrastructure to produce H2 from offshore renewable energy, at their own cost and risk entirely. In this work, the authors elaborated a probabilistic technical and economic model, including all the relevant considerations for the green H2 development project, which was used for the design of the proposed fiscal regime for the H2U Offshore Round. The Uruguayan NOC is managing and articulating the traditional Oil & Gas (O&G) upstream business and the green H2 offshore program together simultaneously, maximizing the synergies among them. The offshore of Uruguay presents a large technical potential and excellent conditions for wind resource, with high wind speed, capacity factors and the availability of large areas. This paper includes the main features of the H2U Offshore Round bidding terms and the contract model, highlighting the synergies and analogies with the E&P projects. In addition, the results of the abovementioned probabilistic model, such as project profitability measures, breakeven hydrogen price and minimum economic capacity factors are presented. In the recent past, Uruguay was able to attract over a billion of US$ of risk capital from the major O&G companies for exploration of hydrocarbons offshore. Hence, the NOC's innovative approach is to bring several similarities from the E&P business to the H2U Offshore Round, with a sound and fair balance between risk and rewards for the energy companies, leading a responsible transition pathway from fossil fuels to green hydrogen in Uruguay.
As the energy transition becomes more and more crucial to our everyday lives, it is important to create an open dialog connecting the oil and gas industry with policymakers. The Oil and Natural Gas Technology Symposium: Focus on Sustainability, held virtually on 6–7 April 2021, created an opportunity for this open dialog. This event was collaboratively developed by the Society of Petroleum Engineers (SPE), the American Association of Petroleum Geologists (AAPG), and the Society of Exploration Geophysicists (SEG). The purpose of this program was to share innovations that improve efficiency, sustainability, reduce environmental impact, and enhance recovery. Additionally, the speakers addressed the role of oil and natural gas in the coming energy transition.
Abstract In this paper, we present an efficient inverse modeling framework for energy transition applications. The key feature of this framework is a combination of adjoint gradients and Operator-based Linearization (OBL) technique to achieve high efficiency in inverse modeling based on forward simulations. This framework allows conducting the history matching of practical industrial applications using the gradient descent method with considerable model control variables in a reasonable time. Generally, the inverse modeling of industrial applications involves large amounts of gradient calculations in algorithms based on gradient descent. In this study, we analytically compute the gradient using the adjoint gradient method as an alternative to the widely used numerical gradient method where many time-consuming forward simulation runs are needed. In the adjoint gradient approach, the objective function is linearly combined with the governing equation by introducing a Lagrange multiplier. That allows for finding the analytical gradient in a backward manner. The developed adjoint gradient method takes full advantage of the OBL efficiency and flexibility when assembling the Jacobian and some relevant derivatives. We demonstrate the applications of the proposed inverse modeling framework to different energy transition applications, including petroleum production, extraction of geothermal energy, and CO2 storage. We demonstrate various treatments of objective function definitions, well controls, and measurement errors for these industrial applications. For petroleum production, the proposed framework is tested on the multiphase multi-component flow problem, which is illustrated by an example of data-driven Discrete Well Affinity model. For this application, only production data is considered. The geothermal problem involves an additional energy balance equation and various property calculations for water and steam. In this application, together with the production data, additional electromagnetic monitoring is used in the history matching process. The results show that electromagnetic monitoring significantly improves the inversion process. We conclude the description of our framework with an application relevant to CO2 sequestration process. The CO2 storage modeling is complicated due to the complex physical phenomena to be considered. In this application, tracer data are used as an additional observation, which allows considering uncertainties in the dynamics of CO2. In this study, the adjoint gradient method is specially designed and customized for OBL infrastructure of the Delft Advanced Research Terra Simulator (DARTS). This allows us to design the general-purpose inversion module with efficient gradient computation, while most existing simulation platforms lack this capability. Based on the multiphysics simulation engine in DARTS, the various observation information can be combined in the proposed framework. This allows us to solve the general-purpose inverse modeling problems for most energy transition applications.
Abstract Carbon capture and storage (CCS) presents a key solution to reducing emissions especially from stationary power and industrial sites. A major component of CCS is CO2 storage in geologic formations, including saline aquifers, presents a great opportunity for the oil and gas industry to capitalize on their subsurface expertise to ensure that CO2 is stored safely underground over the long term. Saline aquifers are particularly relevant in the Middle East, where hydrocarbon reservoirs may not be at high depletion stages and so may not be available for CO2 storage yet. This paper looks at key geologic formation considerations related to CO2 storage in saline aquifers, highlighting the static and dynamic characteristics of the rock and the fluids that determine how much CO2 can be stored and at what injection rate. It also highlights how these characteristics affect the economics of the subsurface component of a CCS project. This paper shall provide an overview of the key aspects that guide subsurface storage evaluations: containment ability, trapping mechanisms, storage capacity, and injectivity. It will highlight the different storage capacity assessment methods. Then it shall discuss resource classification and categorization, and determination of commerciality as per the SPE CO2 Storage Resources Management System (SRMS). Finally, the paper goes into further considerations that need to be taken into account beyond the initial screening, including the data acquisition program and the impact of CO2 stream impurities on storage potential, geologic formation properties and cap rock integrity. The work illustrates the importance of understanding the physics of CO2 injection into a water-bearing system and lays out considerations for screening potential saline aquifer sites from a reservoir engineering perspective. The screening process should evaluate the anticipated CO2 trapping mechanism, assure its ability to contain the injected fluids over the long term, and estimate its storage capacity and injectivity.
Tariq, Zeeshan (King Abdullah University of Science and Technology) | Yan, Bicheng (King Abdullah University of Science and Technology) | Sun, Shuyu (King Abdullah University of Science and Technology)
Abstract Geological Carbon Sequestration (GCS) in deep geological formations, like saline aquifers and depleted oil and gas reservoirs, brings enormous potential for large-scale storage of carbon dioxide (CO2). The successful implementation of GCS requires a comprehensive risk assessment of the confinement of plumes and storage potential at each storage site. To better understand the integrity of the caprock after injecting CO2, it is necessary to develop robust and fast tools to evaluate the safe CO2 injection duration. This study applied deep learning (DL) techniques, such as fully connected neural networks, to predict the safe injection duration. A physics-based numerical reservoir simulator was used to simulate the movement of CO2 for 170 years following a 30-year CO2 injection period into a deep saline aquifer. The uncertainty variables were utilized, including petrophysical properties such as porosity and permeability, reservoir physical parameters such as temperature, salinity, thickness, and operational decision parameters such as injection rate and perforation depth. As mentioned earlier, the reservoir model was sampled using the Latin-Hypercube sampling approach to account for a wide range of parameters. Seven hundred twenty-two reservoir simulations were performed to create training, testing, and validation datasets. The DNN model was trained, and several executions were performed to arrive at the best model. After multiple realizations and function evaluations, the predicted results revealed that the three-layer FCNN model with thirty neurons in each layer could predict the safe injection duration of CO2 into deep saline formations. The DNN model showed an excellent prediction efficiency with the highest coefficient of determination factor of above 0.98 and AAPE of less than 1%. Also, the trained predictive models showed excellent agreement between the simulated ground truth and predicted trapping index, yet 300 times more computationally efficient than the latter. These findings indicate that the DNN-based model can support the numerical simulation as an alternative to a robust predictive tool for estimating the performance of CO2 in the subsurface and help monitor the storage potential at each part of the GCS project.