Vertical integration approach for the intelligent Oil & Gas field

2018 ◽  
Vol 66 (10) ◽  
pp. 859-874 ◽  
Author(s):  
Marcelo V. García ◽  
Aintzane Armentia ◽  
Federico Pérez ◽  
Elisabet Estévez ◽  
Marga Marcos
Keyword(s):  
Vertical Integration ◽  
Flexible Manufacturing ◽  
Oil And Gas ◽  
Production Systems ◽  
Oil And Gas Industry ◽  
Oil Field ◽  
Remote Access ◽  
Production Costs ◽  
Gas Field ◽  
Cyber Physical Production Systems

Abstract The oil and gas industry envisions a smarter way of running their business where they can visualize their entire operation, call and retrieve production data effortlessly and seamlessly, collaborating across the entire enterprise to decrease production costs while increasing recovery. The so-called Intelligent Oil Field (IOF) promotes reference architectures and development approaches that improve the flexibility and efficiency of upstream and downstream process. In this sense, OPC UA provides local and remote access to plant information, allowing horizontal and vertical integration in a reliable, safe and efficient way. This article contributes an open IOF architecture for vertical integration based on cyber-physical production systems, configured under IEC 61499 and using OPC UA. Therefore, the proposal is suitable to achieve flexible manufacturing.

Alaska’s North Slope May Yet See Its Renaissance in Arctic Exploration

2021 ◽  
Vol 73 (10) ◽  
pp. 17-22
Author(s):  
Pat Davis Szymczak
Keyword(s):  
Oil And Gas ◽  
Barents Sea ◽  
Oil And Gas Industry ◽  
Gas Production ◽  
Oil Field ◽  
The Arctic ◽  
Energy Information Administration ◽  
Gas Field ◽  
The Us ◽  
Arctic Exploration

It wasn’t too long ago that Arctic oil and gas exploration enjoyed celebrity status as the industry’s last frontier, chock full of gigantic unexplored hydrocarbon deposits just waiting to be developed. Fast forward and less than a decade later, the same climate change that made Arctic oil and gas more accessible has caused an about-face as governments and the world’s supranational energy companies rebrand and target control of greenhouse gases (GHG) to achieve carbon neutrality by 2050. Among countries with Arctic coastlines, Canada has focused its hydrocarbon production on its oil sands which sit well below the Arctic Circle; Greenland has decided to not issue any new offshore exploration licenses (https://jpt.spe.org/greenland-says-no-to-oil-but-yes-to-mining-metals-for-evs), and while Norway is offering licenses in its “High North,” the country can’t find many takers. The Norwegian Petroleum Directorate (NPD) reported that while 26 companies applied for licenses in 2013, this year’s bid round attracted only seven participants. Norway is Europe’s largest oil producer after Russia with half of its recoverable resources still undeveloped and most of that found in the Barents Sea where the NPD says only one oil field and one gas field are producing. That leaves Russia and the US—geopolitical rivals which are each blessed with large Arctic reserves and the infrastructure to develop those riches—but whose oil and gas industries play different roles in each nation’s economy and domestic political intrigues. Russia sees its Arctic reserves, particularly gas reserves, as vital to its national security, considering that oil and gas accounts for 60% of Russian exports and from 15 to 20% of the country’s gross domestic product (GDP), according to Russia’s Skolkovo Energy Centre. With navigation now possible year­round along the Northern Sea Route, Russia’s LNG champion and its largest independent gas producer, Novatek, is moving forward with exploration to expand its resource base and build infrastructure to ship product east to Asia and west to Europe. https://jpt.spe.org/russian­lng­aims­high­leveraging­big­reserves­and­logistical­advantages As a result, Russia’s state­owned majors—Rosneft, Gazprom, and Gazprom Neft—are lining up behind their IOC colleague as new investment in Arctic exploration and development is encouraged and rewarded by the Kremlin. In contrast, the American Petroleum Institute reports that the US oil and gas industry contributes 8% to US GDP, a statistic that enables the US to have a more diverse discussion than Russia about the role that oil and gas may play in any future energy mix. That is unless you happen to be from the state of Alaska where US Arctic oil and gas is synonymous with Alaskan oil and gas, and where the US Geological Survey estimates 27% of global unex­plored oil reserves may lie. Though Alaska is responsible for only 4% of US oil and gas production, those revenues covered two-thirds of Alaska’s state budget in 2020 despite the state’s decline in crude production in 28 of the past 32 years since it peaked at 2 million B/D in 1988, according to the US Energy Information Administration (EIA).

Smart upstream to LNG

2018 ◽  
Vol 58 (2) ◽  
pp. 508
Author(s):  
Russell Byfield
Keyword(s):  
Supply Chain ◽  
Enterprise Resource Planning ◽  
Oil And Gas ◽  
Big Data Analytics ◽  
Resource Planning ◽  
Oil And Gas Industry ◽  
Oil Field ◽  
Gas Field ◽  
Gas Industry ◽  
Supply Chain Optimisation

With today’s current technologies, it is possible to answer the question, ‘What is the most profitable mode of operation for the next few hours, for the rest of today, tomorrow and beyond?’ With ‘lower for longer’ oil prices, the need for enterprise wide optimisation in the upstream and midstream oil and gas industry is greater than ever. The terms ‘Digital Oil Field’, ‘Digital Gas Field’, ‘Digital Twin’ are being utilised to extol the virtue and value of big data analytics and model-based asset optimisation and supply chain optimisation by enabling this in efficient ways not previously possible with multiple unintegrated systems, processes and procedures. Multiple different point solutions rolled out across multiple sites become difficult to integrate horizontally for management of safe and optimised operations and vertically up to business enterprise resource planning level to give useful and timely business insights. With careful planning, coupled with deep operational technology and operations knowledge, an integrated enterprise wide supply chain and asset operations and management system can unlock significant hidden value. This is enabled by the correct and efficient integration of many systems and the efficient collection, management and use of huge amounts of data. As the industry needs to ‘do more with less’, getting this integration right is critical to enable desired outcomes and functionality. This paper summarises the current state-of-the-art solutions that enable optimised well to liquefied natural gas plant process, asset and business management to deliver desired functionality and outcomes.

Study the effect of casting temperature on details from thermo-plastic materials

2020 ◽  
pp. 42-45
Author(s):  
J.A. Kerimov ◽  
Keyword(s):  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Mold Temperature ◽  
Quality Parameters ◽  
Oil Field ◽  
Casting Temperature ◽  
Gas Industry ◽  
Field Equipment ◽  
Wide Range ◽  
The Impact

The implementation of plastic details in various constructions enables to reduce the prime cost and labor intensity of machine and device manufacturing, decrease the weight of design and improve their quality and reliability at the same time. The studies were carried out with the aim of labor productivity increase and substitution of colored and black metals with plastic masses. For this purpose, the details with certain characteristics were selected for further implementation of developed technological process in oil-gas industry. The paper investigates the impact of cylinder and compression mold temperature on the quality parameters (shrinkage and hardness) of plastic details in oil-field equipment. The accessible boundaries of quality indicators of the details operated in the equipment of exploration, drilling and exploitation of oil and gas industry are studied in a wide range of mode parameters. The mathematic dependences between quality parameters (shrinkage and hardness) of the details on casting temperature are specified.

scholarly journals Application of the CL-systems technology for water injection wells at an oil and gas field

2021 ◽  
Vol 19 (3) ◽  
pp. 848-853
Author(s):  
Liliya Saychenko ◽  
Radharkrishnan Karantharath
Keyword(s):  
Oil And Gas ◽  
Water Injection ◽  
Oil And Gas Industry ◽  
Field Studies ◽  
High Water ◽  
Injection Wells ◽  
Gas Field ◽  
Water Breakthrough ◽  
Oil And Gas Field ◽  
High Water Cut

To date, the development of the oil and gas industry can be characterized by a decline in the efficiency of the development of hydrocarbon deposits. High water cut-off is often caused by water breaking through a highly permeable reservoir interval, which often leads to the shutdown of wells due to the unprofitability of their further operation. In this paper, the application of straightening the profile log technology for injection wells of the Muravlenkovsky oil and gas field is justified. In the course of this work, the results of field studies are systematized. The reasons for water breakthrough were determined, and the main ways of filtration of the injected water were identified using tracer surveys. The use of CL-systems technology based on polyacrylamide and chromium acetate is recommended. The forecast of the estimated additional oil produced was made.

Utilizing Pseudo Well Connections to Simulate Multi-Stage Hydraulic Fracturing - Example Based On the Study of a Tight Gas Asset

2021 ◽  
Author(s):  
Aamir Lokhandwala ◽  
Vaibhav Joshi ◽  
Ankit Dutt
Keyword(s):  
Hydraulic Fracturing ◽  
Oil And Gas ◽  
Flow Simulation ◽  
Oil And Gas Industry ◽  
Development Plan ◽  
Hydraulic Fractures ◽  
Tight Gas ◽  
Gas Field ◽  
Field Development ◽  
Fracture Modeling

Abstract Hydraulic fracturing is a widespread well stimulation treatment in the oil and gas industry. It is particularly prevalent in shale gas fields, where virtually all production can be attributed to the practice of fracturing. It is also used in the context of tight oil and gas reservoirs, for example in deep-water scenarios where the cost of drilling and completion is very high; well productivity, which is dictated by hydraulic fractures, is vital. The correct modeling in reservoir simulation can be critical in such settings because hydraulic fracturing can dramatically change the flow dynamics of a reservoir. What presents a challenge in flow simulation due to hydraulic fractures is that they introduce effects that operate on a different length and time scale than the usual dynamics of a reservoir. Capturing these effects and utilizing them to advantage can be critical for any operator in context of a field development plan for any unconventional or tight field. This paper focuses on a study that was undertaken to compare different methods of simulating hydraulic fractures to formulate a field development plan for a tight gas field. To maintaing the confidentiality of data and to showcase only the technical aspect of the workflow, we will refer to the asset as Field A in subsequent sections of this paper. Field A is a low permeability (0.01md-0.1md), tight (8% to 12% porosity) gas-condensate (API ~51deg and CGR~65 stb/mmscf) reservoir at ~3000m depth. Being structurally complex, it has a large number of erosional features and pinch-outs. The study involved comparing analytical fracture modeling, explicit modeling using local grid refinements, tartan gridding, pseudo-well connection approach and full-field unconventional fracture modeling. The result of the study was to use, for the first time for Field A, a system of generating pseudo well connections to simulate hydraulic fractures. The approach was found to be efficient both terms of replicating field data for a 10 year period while drastically reducing simulation runtime for the subsequent 10 year-period too. It helped the subsurface team to test multiple scenarios in a limited time-frame leading to improved project management.

Technology Focus: Offshore Drilling and Completion (October 2021)

2021 ◽  
Vol 73 (10) ◽  
pp. 45-45
Author(s):  
Martin Rylance
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Oil And Gas ◽  
Hybrid Approach ◽  
Data Communication ◽  
Oil And Gas Industry ◽  
Oil Field ◽  
Real Time Processing ◽  
National University ◽  
Seoul National University

Communication and prediction are symmetrical. Communication, in effect, is prediction about what has happened. And prediction is communication about what is going to happen. Few industries contain as many phases, steps, and levels of interface between the start and end product as the oil and gas industry—field, office, offshore, plant, subsea, downhole, not to mention the disciplinary, functional, managerial, logistics handovers, and boundaries that exist. It therefore is hardly surprising that communication, in all its varied forms, is at the very heart of our business. The papers selected this month demonstrate how improved communication can deliver the prediction required for a variety of reasons, including safety, efficiency, and informational purposes. The application of new and exciting ways of working, partially accelerated by recent events, is leading to breakthrough improvements on all levels. Real-time processing, improved visualization, and predictive and machine-learning methods, as well as improvements in all forms of data communication, are all contributing to incremental enhancements across the board. This month, I encourage the reader to review the selected articles and determine where and how the communication and prediction are occurring and what they are delivering. Then perhaps consider performing an exercise wherein your own day-to-day roles—your own areas of communication, interfacing, and cooperation—are reviewed to see what enhancements you can make as an individual. You may be pleasantly surprised that some simple tweaks to your communication style, frequency, and format can deliver quick wins. In an era of remote working for many individuals, it is an exercise that has some value. Recommended additional reading at OnePetro: www.onepetro.org. OTC 30184 - Augmented Machine-Learning Approach of Rate-of-Penetration Prediction for North Sea Oil Field by Youngjun Hong, Seoul National University, et al. OTC 31278 - A Digital Twin for Real-Time Drilling Hydraulics Simulation Using a Hybrid Approach of Physics and Machine Learning by Prasanna Amur Varadarajan, Schlumberger, et al. OTC 31092 - Integrated Underreamer Technology With Real-Time Communication Helped Eliminate Rathole in Exploratory Operation Offshore Nigeria by Raphael Chidiogo Ozioko, Baker Hughes, et al.

Digital Oil Field; The NPDC Experience

2021 ◽  
Author(s):  
Henry Ijomanta ◽  
Lukman Lawal ◽  
Onyekachi Ike ◽  
Raymond Olugbade ◽  
Fanen Gbuku ◽  
...  
Keyword(s):  
Real Time ◽  
Oil And Gas ◽  
Data Gathering ◽  
Oil And Gas Industry ◽  
Oil Field ◽  
Battery Life ◽  
Gas Industry ◽  
Field Management ◽  
Digital Oilfield ◽  
Data Analytic

Abstract This paper presents an overview of the implementation of a Digital Oilfield (DOF) system for the real-time management of the Oredo field in OML 111. The Oredo field is predominantly a retrograde condensate field with a few relatively small oil reservoirs. The field operating philosophy involves the dual objective of maximizing condensate production and meeting the daily contractual gas quantities which requires wells to be controlled and routed such that the dual objectives are met. An Integrated Asset Model (IAM) (or an Integrated Production System Model) was built with the objective of providing a mathematical basis for meeting the field's objective. The IAM, combined with a Model Management and version control tool, a workflow orchestration and automation engine, A robust data-management module, an advanced visualization and collaboration environment and an analytics library and engine created the Oredo Digital Oil Field (DOF). The Digital Oilfield is a real-time digital representation of a field on a computer which replicates the behavior of the field. This virtual field gives the engineer all the information required to make quick, sound and rational field management decisions with models, workflows, and intelligently filtered data within a multi-disciplinary organization of diverse capabilities and engineering skill sets. The creation of the DOF involved 4 major steps; DATA GATHERING considered as the most critical in such engineering projects as it helps to set the limits of what the model can achieve and cut expectations. ENGINEERING MODEL REVIEW, UPDATE AND BENCHMARKING; Majorly involved engineering models review and update, real-time data historian deployment etc. SYSTEM PRECONFIGURATION AND DEPLOYMENT; Developed the DOF system architecture and the engineering workflow setup. POST DEPLOYMENT REVIEW AND UPDATE; Currently ongoing till date, this involves after action reviews, updates and resolution of challenges of the DOF, capability development by the operator and optimizing the system for improved performance. The DOF system in the Oredo field has made it possible to integrate, automate and streamline the execution of field management tasks and has significantly reduced the decision-making turnaround time. Operational and field management decisions can now be made within minutes rather than weeks or months. The gains and benefits cuts across the entire production value chain from improved operational safety to operational efficiency and cost savings, real-time production surveillance, optimized production, early problem detection, improved Safety, Organizational/Cross-discipline collaboration, data Centralization and Efficiency. The DOF system did not come without its peculiar challenges observed both at the planning, execution and post evaluation stages which includes selection of an appropriate Data Gathering & acquisition system, Parts interchangeability and device integration with existing field devices, high data latency due to bandwidth, signal strength etc., damage of sensors and transmitters on wellheads during operations such as slickline & WHM activities, short battery life, maintenance, and replacement frequency etc. The challenges impacted on the project schedule and cost but created great lessons learnt and improved the DOF learning curve for the company. The Oredo Digital Oil Field represents a future of the oil and gas industry in tandem with the industry 4.0 attributes of using digital technology to drive efficiency, reduce operating expenses and apply surveillance best practices which is required for the survival of the Oil and Gas industry. The advent of the 5G technology with its attendant influence on data transmission, latency and bandwidth has the potential to drive down the cost of automated data transmission and improve the performance of data gathering further increasing the efficiency of the DOF system. Improvements in digital integration technologies, computing power, cloud computing and sensing technologies will further strengthen the future of the DOF. There is need for synergy between the engineering team, IT, and instrumentation engineers to fully manage the system to avoid failures that may arise from interface management issues. Battery life status should always be monitored to ensure continuous streaming of real field data. New set of competencies which revolves around a marriage of traditional Petro-technical skills with data analytic skills is required to further maximize benefit from the DOF system. NPDC needs to groom and encourage staff to venture into these data analytic skill pools to develop knowledge-intelligence required to maximize benefit for the Oredo Digital Oil Field and transfer this knowledge to other NPDC Asset.

Quantifying Economic Uncertainties and Risks in the Oil and Gas Industry

2021 ◽  
pp. 154-184
Author(s):  
Sorin Alexandru Gheorghiu ◽  
Cătălin Popescu
Keyword(s):  
Business Performance ◽  
Oil And Gas ◽  
Water Injection ◽  
Oil And Gas Industry ◽  
Oil Field ◽  
Gas Industry ◽  
Field Development ◽  
Drilling Rig ◽  
Oil Field Development ◽  
Oil Gas

The present economic model is intended to provide an example of how to take into consideration risks and uncertainties in the case of a field that is developed with water injection. The risks and uncertainties are related, on one hand to field operations (drilling time, delays due to drilling problems, rig failures and materials supply, electric submersible pump [ESP] installations failures with the consequences of losing the well), and on the other hand, the second set of uncertainties are related to costs (operational expenditures-OPEX and capital expenditures-CAPEX, daily drilling rig costs), prices (oil, gas, separation, and water injection preparation), production profiles, and discount factor. All the calculations are probabilistic. The authors are intending to provide a comprehensive solution for assessing the business performance of an oil field development.

Financing Requirements for the Oil and Gas Industry - North America

1988 ◽  
Vol 6 (4-5) ◽  
pp. 317-322
Author(s):  
A.F. Grove
Keyword(s):  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Gas Field ◽  
Gas Industry ◽  
Field Development ◽  
Energy Company ◽  
Corporate Credit ◽  
Oil And Gas Field ◽  
Good Energy ◽  
Business Acumen

The characteristics of good energy company borrowers are strong management, integrity, diversification, flexibility, a sound financial basis and business acumen. Acceptable reasons for borrowing include requirements for working capital, plant expansion, modernisation, oil and gas field development and the manufacturing of oil tools and related products. Security for loans is based on the company's reserves, the duration of the debt and priority over other indebtedness. Most loans are evaluated on the grounds of general corporate credit, that is, the overall credit standing of the borrower.

scholarly journals The contribution of cyber-physical production systems to activity-based costing in manufacturing. An interventionist research approach

2020 ◽  
Vol 12 ◽  
pp. 184797902096230
Author(s):  
Giancarlo Nota ◽  
Gaetano Matonti ◽  
Marco Bisogno ◽  
Stefania Nastasia
Keyword(s):  
Production Systems ◽  
Production Costs ◽  
Research Approach ◽  
Activity Based Costing ◽  
Improve Performance ◽  
Real Time Measurement ◽  
Abc Method ◽  
Cyber Physical Production Systems ◽  
Manufacturing Problems ◽  
Managerial Perspective

This study aims to investigate how the use of cyber-physical production systems (CPPS) in small manufacturing firms can facilitate the implementation of the activity-based costing (ABC) method in calculating production costs, thereby increasing the reliability of costing information for decision-making purposes. The collaboration between the research team and managers allowed an in-depth knowledge of the manufacturing problems at the investigated firm, facilitating the analysis of the manufacturing process through both a costing and a managerial perspective. Findings show that the integration of CPPS investments with the ABC method, through real-time measurement of resources by sensors, apps and part programs, leads to useful information about operations, allowing firms to improve performance and reduce resource consumption. As a result, a model of integration between the factory control system, communication network and production system is proposed.

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