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Pioneer Natural Resources announced this week new greenhouse-gas (GHG) emissions-reduction targets across its Permian Basin operations. The plan, rolled out in the company’s new sustainability report, calls for a 25% reduction of GHG emissions by 2030 and a 40% reduction in methane emissions by 2030. The Irving, Texas-based shale producer has also committed to flaring less than 1% of its associated gas and aims to eliminate routine flaring by 2030, and possibly as soon as 2025. By 2022, the new flaring limit will apply to the assets Pioneer is acquiring through its purchase of Parsley Energy. Pioneer announced it was buying the smaller Permian player in a deal valued at $4.5 billion in October.
Despite having many of the technologies enabled by advanced connectivity already at its disposal, the oil and gas sector has yet to realize much of connectivity’s potential—and the potential is significant. According to McKinsey's estimates, making use of advanced connectivity to optimize drilling and production throughput and improve maintenance and field operations could add up to $250 billion of value to the industry’s upstream operations by 2030. Of that value, between $160 billion and $180 billion could be realized with existing infrastructure, while an additional $70 billion could be unlocked with low-Earth orbit satellites and next-generation 5G technologies. McKinsey’s work with the oil and gas sector suggests offshore operators can reduce costs, including operational and capital expenditures, by 20 to 25% per barrel by relying on connectivity to deploy digital tools and analytics. Such a dramatic technological lift can’t come soon enough.
Produced water is water that is brought to surface during oil and natural-gas production. It includes formation, flowback, and condensation water. Produced water varies in composition and volume from one formation to another and is often managed as a waste material requiring disposal. In recent years, increased demand for, and regional variability of, available water resources, along with sustainable water-supply planning, have driven interest in reusing produced water with or without treatment to meet requirements within the industry or by external users. Reuse of produced water can provide important economic, social, and environmental benefits, particularly in water-scarce regions. It can be used for hydraulic fracturing, waterflooding, and enhanced oil recovery, decreasing the demand for other sources of water.
He, Zechen (The State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology ) | Ning, Dezhi (The State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology ) | Gou, Ying (The State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology )
An optimization model of buoy dimension of wave energy converter is established by using differential evolution algorithm. The linear potential flow method is used in hydrodynamic calculation. Taking the vertical oscillating cylindrical buoy as the research object, the radius and draft of the buoy are optimized under each specified volume. Through the comparison of different volume optimization results, it is found that there is an optimal buoy volume for a specific wave condition. With the increase of the volume, the optimal draft tends to a fixed value, and the optimal radius tends to be an asymptote. In addition, the influence of different damping of power take-off systems on the optimization results is also studied.
Wave energy is a kind of renewable and clean energy. The development and utilization of wave energy is attracting the attention of many scholars and research institutions around the world, which may make a significant contribution to the world' power consumption. For the commercial feasibility of wave energy, it is very important to improve the production efficiency of wave energy device and reduce its construction, installation and operation costs. Obviously, the volume of the Wave Energy Converter (WEC) is a key factor affecting both the efficiency and the cost. De Andres et al. (2015) discussed that small equipment is usually more economical due to reduced material costs and deployment. Göteman et al. (2014) and Göteman (2017) showed that the total power production can be improved if the wave energy array consists of devices of different dimensions that are similar to the WECs that have been developed at Uppsala University since 2006 (Leijon et al.,2009). Most previous optimal studies focus on the buoy dimensions instead of the buoy volume. For example, Giassi and Göteman (2017) optimized the parameters of the single wave energy converter by parameter sweep optimization of the variables and genetic algorithm, in which the radius, draft and damping of the Power Take Off (PTO) systems are optimized simultaneously in discrete parameter space. Because there are many combinations of radius and draft under a certain volume even for a truncated cylinder buoy, it' difficult to get the relationship between the volume and the efficiency directly. That means the designer couldn't balance the cost and the efficiency with the optimal dimensions.
Shen, Wenjun (Tianjin Research Institute for Water Transport engineering, M.O.T) | Chen, Hanbao (Tianjin Research Institute for Water Transport engineering, M.O.T) | Jiang, Yunpeng (Tianjin Research Institute for Water Transport engineering, M.O.T) | Gao, Feng (Tianjin Research Institute for Water Transport engineering, M.O.T)
The ship to ship operation system of FSRU and LNG is taken as the research object in this paper. Based on the three-dimensional frequency-domain potential flow theory, numerical analysis of the resonance characteristics of wave surface elevation in the gap between FSRU and LNG. The effect of potential flow was modified by adding artificial damping, and the influence of wave period (wave frequency), incident direction and other parameters on the wave surface elevation was discussed. Furthermore, the problem of the resonance of the intermediate water body was further explored and analyzed based on the different distances between the two ships and different draughts.
Floating LNG storage and regasification unit (FSRU), which integrates LNG receiving, storage, transfer, regasification and export and other functions, it can used as LNG receiving terminal while it is moored at the dock and can also be used for the transportation of LNG. As the emergence of FSRU, it has become an important option for the receiving of LNG, and adopted by more and more countries and regions. According to statistics, up to now, there are 30 projects in operation and another 8 projects area being under construction.
In the loading and unloading operation period, ship to ship operation mode between FSRU and LNG is usually used, as shown in Figure 1. While this mode is used, the hydrodynamic interference and coupled motion between them are more complex. Especially when the two ships are very close to each other, the disturbance between the two ships is aggravated, which brings great safety risks to the loading and unloading operation. Therefore, it is necessary to consider the interaction of the hydrodynamic forces between the two ships, and know well about the hydrodynamic characteristics of the two ships in different conditions and the wave surface rise between the two ships.
Methane (CH4), the primary constituent of natural gas and is the second-most abundant greenhouse gas after carbon dioxide (CO2), accounts for 16% of global emissions. The lifetime of methane in the atmosphere is much shorter than CO2, but CH4 is more efficient at trapping radiation than CO2. Pound for pound, the comparative effect of CH4 is more than 25 times greater than CO2 over a 100-year period. Natural-gas emissions from oil and gas facilities such as well sites, refineries, and compressor stations can have significant safety, economic, and regulatory effects. Continuous emission detection systems enable rapid identification and response to unintended emission events.
The Abu Dhabi National Oil Company (ADNOC) announced that it has completed the first phase of its large-scale multiyear predictive maintenance project, which aims to maximize asset efficiency and integrity across its upstream and downstream operations. ADNOC says its predictive maintenance platform uses artificial intelligence (AI) technologies such as machine learning and digital twins, ADNOC’s to help predict equipment stoppages, reduce unplanned equipment maintenance and downtime, and increase reliability and safety. The company said it expects use of the platform to result in maintenance savings of up to 20%. The predictive maintenance project, which was announced in November 2019, is being implemented over four phases. ADNOC’s predictive maintenance project is part of the company’s digital acceleration program, which focuses on embedding advanced digital technologies across the company’s operations.
SPE’s A Peer Apart award recognizes those dedicated individuals involved in the review of 100 or more papers for SPE’s peer-reviewed journals. Peer review is an essential part of scientific publishing and helps to ensure the information contained in a journal is well supported and clearly articulated. Volunteers who commit their time to review papers make substantial contributions to the technical excellence of our industry’s literature. Each year SPE typically has more than 1,400 individual reviewers submitting more than 3,500 reviews for SPE’s various journals. These committed volunteers come from a variety of backgrounds, including academia, service and operator companies, and consultancies from around the world.
Supply-chain solutions provider Würth Industry North America (WINA) and Baker Hughes created a joint service offering for their design, digital inventory, and customized 3D printing services to expand into different industrial sectors. The companies will work on design and additive manufacturing opportunities in the oil and gas, renewables, power generation, maritime, automotive, and aerospace industrial sectors. The collaboration improves WINA’s automation with no infrastructure change, allowing it to take customer prototype ideas to small-batch production and mass production at accelerated rates. Würth will offer Baker Hughes’ additive manufacturing services, and Baker Hughes gains access to Würth’s global customer base of 80,000 clients. The expanded service includes access to Baker Hughes’ digital inventory capabilities.
Al Gharbi, Salem (King Fahd University of Petroleum & Minerals) | Al-Majed, Abdulaziz (King Fahd University of Petroleum & Minerals) | Abdulraheem, Abdulazeez (King Fahd University of Petroleum & Minerals) | Patil, Shirish (King Fahd University of Petroleum & Minerals) | Elkatatny, Salaheldin (King Fahd University of Petroleum & Minerals)
Drilling is considered one of the most challenging and costly operations in the oil and gas industry. Several initiatives were applied to reduce the cost and increase the effectiveness of drilling operations. One of the frequent difficulties that faces these operations is unexpected drilling troubles that take place and stops the operation, resulting in losing a lot of time and money, and could lead to safety issues culminating in a fatality situation. For that, the industry is in continues efforts to prevent drilling troubles. Part of these efforts is utilizing the artificial intelligence (AI) technologies to identify troubles in advance and prevent them before maturing to a serious situation. Multiple approaches were tried; however, errors and significant deviation were observed when comparing the prediction results to the actual drilling data. This could be due to the improper design of the artificial intelligent technology or inappropriate data processing. Therefore, searching for dynamic and adequate artificial intelligent technology and encapsulated data processing model is very essential.
This paper presents an effective data-mining methodology to determine the most efficient artificial intelligent technology and the applicable data processing techniques, to identify the early symptoms of drilling troubles in real-time. This methodology is CRISP-DM that stands for Cross Industry Standard Process for Data Mining. This methodology consists of the following phases: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation and Deployment. During these phases, multiple data-quality techniques were applied to improve the reliability of the real-time data.
The developed model presented a significant improvement in identifying the drilling troubles in advance, compared to the current practice. Parameters such as hook-load and bit-depth, were studied. Actual data from several oil fields were used to develop and validate this smart model. This model provided the drilling engineers and operation crew with bigger window to mitigate the situation and resolve it, prevent the occurrence of several drilling troubles, result in big time and cost savings. In addition to the time and cost savings, CRISP-DM provided the artificial intelligent experts and the drilling domain experts with a framework to exchange knowledge and sharply increase the synergy between the two domains, which lead to a common and clear understanding, and long-term successful drilling and AI teams collaboration.
The novelty of this paper is the introduction of data-mining CRIPS methodology for the first time in the prediction of drilling troubles. It enabled the development of a successful artificial intelligence model that outperformed other drilling troubles prediction practices.