Big data intelligent platform and application analysis for oil and gas resource development

In recent years, new terms and concepts have appeared that describe the digital transformation currently in progress. The world image, including in the industrial world, has been changed by the concept of intelligent enterprise (IE) - a set of technological innovations, including artificial intelligence (AI), intelligent automation (IA), deep learning technologies, predictive analytics and cognitive computing. The increasing complexity of the oil and gas business and the decreasing optimization potential from traditional approaches require the use of new, innovative digital technologies to remain competitive. Responding to the market conditions of falling hydrocarbon prices, the oil and gas industry is increasingly mastering Big Data to optimize technological processes and prevent accidents. The emergence of Big Data technologies, predictive analysis and machine learning are changing the general image of many industries, and the oil and gas industry is no exception. New players are quickly emerging throughout the industry, and digitalization will affect the entire value chain throughout in the oil and gas industry. Among the most promising segments for the transition to digital technologies are asset management and infrastructure facilities, field development, geophysical services, pipelines and processing. Digital technology is the most powerful driver for cost reduction. It is expected that implementing these solutions will, by 2030, reduce the costs of E & P projects by up to 30%. Thus, Russia can leverage these new technologies and retain a share in the world energy market for another 50 years. The oil industry has recently passed the most difficult period in the last 30 years. The fall in oil prices since 2014, the reduction of 350 thousand employees worldwide, and fall in production investment are examples of serious challenges that the industry has faced in recent years. These challenges have resulted in new attempts to optimize business through implementing new technologies to improve the efficiency and profitability of companies.

Emerging technologies often bring new opportunities to enhance productivity and safety in the oil and gas industry. New technologies and opportunities often come with the challenges of workforce development to provide entry-level and current professionals with the necessary training and skillset. This paper presents a vertical education enhancement (VEE) model approach to providing emerging skillset needs in the oil and gas industry with emphases on curriculum continuous improvement and lifelong learning. The top new and emerging technologies that are critical to the future of the oil and gas industry in enhancing productivity and safety include Internet of Things (IoT), artificial intelligence, big data analytics, cloud computing, and 3D modeling/visualization. As part of the solution to train the oil and gas industry workforce to meet the challenges of adopting these technologies, the VEE model features a vertical education structure that encompasses outreach to K-12 education, recruitment, tertiary education, professional training, and lifelong learning. It has an interwoven fundamental structure consisting of curriculum and mentorship, partnerships with stakeholders (industry, government, and community), and research and funding. The VEE model has periodic assessment continuous improvement processes for identifying emerging technologies and new skillset needed to improve the workforce. These processes are like those practiced by accreditation bodies such Accreditation Board for Engineering and Technology (ABET), United Kingdom Accreditation Services (UKAS), and Offshore Petroleum Industry Training Organization (OPITO). Diversity to increase the participation of underrepresented minority groups and women in engineering would further increase the workforce. The novelty that the VEE model approach brings is the effectiveness in providing skillset training in new and emerging technologies for the oil and gas industry at all levels of workforce development. These include content infusion in existing courses, special-topic and specialized courses at senior and graduate levels, and professional development education and training through lifelong learning platforms.

ABSTRACTIn December 2010 Ghana pumped its first oil and a local content law was passed in 2013 to promote local participation in the oil and gas industry. This paper examines Ghanaian entrepreneurial activities and the dynamics of local participation in the emerging oil and gas sector. We explore Ghanaian entrepreneurs' strategies of mobilising networks to acquire information, build trust, raise financial capital and reduce risk with the aim to gain entry, win contracts and participate in the oil and gas industry. We argue that the resources and strategies activated by entrepreneurs embedded in the context of the Ghanaian business environment are inadequate and problematic when deployed in the context of the international oil and gas industry. The international oil companies' cost-intensive standard requirements and state officials' informal interventions further limit local firms' prospects for participation in the oil and gas industry.

The relevance of this article is due, on the one hand, to the importance of the oil and gas industry in the development of Iraq and, on the other hand, the inability to enhance the existing capacities of the gas industry due to both serious systemic internal causes and external problems. The objective of this article is to study the prospects of the gas industry in conjunction with the oil industry, and develop a strategy for their development based on the forecasting of future scenarios. In the article, the research methods used included a systematic analysis of economic, social and cultural conditions, considering the history of Iraq, including a review of statistical data and a variety of sources. The article proposes a method for choosing the industry development strategy on the basis of an analytical hierarchy process, based on an algorithm of iterative processes using an analysis of hierarchies. To clarify the actors’ policies and strategic goals and to find the optimal solution, repeated iterations of the choice of strategy have been proposed. The strategies were divided into alternative strategies for future scenarios, which were evaluated in actions as able to achieve the goals by determining the consistency ratio and the consistency index. As a result of the study, we can highlight the analysis of the centralized system of oil and gas resources’ management that has developed in Iraq, which has a complicated “top-down” delegation of decisions and responsibility, with decisions made at the political level and resources distributed from above, which precludes individual industries from performing their functions, and also limits the effective implementation of strategic development priorities. The development factors for the gas industry in Iraq were identified and systematized with a rationale for the direction of the industry’s strategic development. Groups of factors were identified: market-affecting determinants of the development of the gas industry, as well as other considerations that may, to a lesser extent, affect the development of Iraq’s gas industry and the oil and gas complex as a whole. The results, assessing the significance of the actors’ goals, can be taken as a basis for development strategies for the oil and gas industry, to improve the contract system of the gas industry in conjunction with the oil industry.

Although the concept of Industry 4.0 was defined a decade ago, experts have only been talking about the "Oil and Gas 4.0" model in the last few years. Experts in this industry agree that the "Oil and Gas 4.0" model in use, based on the digitalization and intelligence of the oil and gas industry, can bring huge benefits to the company. However, the "Oil and Gas 4.0" model is still in its infancy, but applications in areas such as big data (BDA), industrial Internet of Things (IIoT), or analysis of typical oil and gas industry chain application scenarios through examples, such as an intelligent oil field, an intelligent pipeline, and an intelligent refinery, make today's challenges real. So the essence of the "Oil and Gas 4.0" model is a data-driven intelligence system based on high digitization. This paper provides an overview of the state and development of the Industry 4.0 concept in the Oil and Gas Industry.

Ghana is often cited as one of Africa’s most stable democracies. Since 2004, the country has awarded 18 petroleum agreements to various international oil companies (IOCs) and their local partners to explore for hydrocarbons in its offshore basins. In 2010, Ghana became an oil-producing country following earlier commercial discoveries in 2007. Nevertheless, the likelihood of the Ghanaian State getting its fair share of petrodollar revenues primarily depends on its ability to negotiate good petroleum contracts and effectively regulate the industry. This article examines the legal and political economy factors that influence contract outcomes in Ghana’s oil and gas industry. It sheds light on how the inner workings of the political economy, especially in a competitive clientelist setup involving intense electoral competition between two dominant parties in an emerging oil-producing country, influence contractual outcomes—an area less explored in the literature. We find that the country's emerging oil and gas industry has become deeply intertwined with the pervasive, entrenched and clientelist multi-party politics of the day. As such, entrenched rentier social groups—business and political elites—have sometimes sabotaged institutional reform to create conditions that favour rent capture. This is evident, for example, in the award of oil and gas licensing and other supply chain contracts. Ghana’s post-1992 ‘winner takes all’ political mindset and the perceived big financial bonanzas the oil industry offers, resulted in suspicions of impropriety regarding the award of some oil acreages. We argue that if the laws were allowed to work, as they should in practice, Ghana’s oil and gas industry would be better regulated, and better outcomes would arise from the contracting process. Discretionary power should be limited as much as possible and, where granted, subject to a high level of scrutiny.

The management of risk is one of the most important issues facing the oil and gas industry today. This paper will focus on the need for risk management in the oil and gas industry. A typical project from a major oil and gas producer has been selected and its typical risks identified. The risks are analysed and modelled in the CASPAR (Computer Aided Simulation for Project Appraisal and Review) program. The paper distinguishes between pure risk and spread risk for forecasting the economic parameters of different risk scenarios. The increasing pace of change, customer demands and market globalisation all put risk management high on the agenda for forward thinking companies. It is necessary today to have a comprehensive risk management strategy. Having a process in place to identify, analyse and manage risks is paramount. The oil and gas industry is fraught with risk and it is necessary for these risks to be assessed continuously. In this paper, the authors examine the downstream risks inherent in the oil and gas industry and differentiate between the more manageable/quantifiable pure risks such as construction, health and safety and project management and the less manageable spread risks associated with war, terrorism and market demand which affect the price of oil and gas.

The research presented in this thesis is rooted within the existing decision theory and oil industry literatures. It contributes to one of the current debates in these literatures by providing evidence that in the operators in the U.K. upstream oil and gas industry there is a link between the use of decision analysis in investment appraisal decision making by organisations and good business performance. It is commonly acknowledged that decision analysis is not as widely used by organisations as was predicted at its conception (for example, Schuyler, 1997). One reason for this is that no study to date has shown that use of decision analysis techniques and concepts can actually help individuals or organisations to fulfil their objectives. Despite over four decades of research undertaken developing decision analysis tools, understanding the behavioural and psychological aspects of decision making, and applying decision analysis in practice, no research has been able to show conclusively what works and what does not (Clemen, 1999). The current study begins to fill this gap by using qualitative methods to establish the following. Firstly, the research identifies which decision analysis techniques are applicable for investment decision-making in the oil industry, and thereby produces a description of current capability. Secondly, the study ascertains which decision analysis tools oil and gas companies actually choose to use for investment appraisal, and through this develops a model of current practice of capital investment decision making. Lastly, using statistical analysis, it provides evidence that there is an association between the use of decision analysis in investment decision-making by companies and good organisational performance in the upstream oil and gas industry. Such research not only contributes to the current theoretical debate in the oil industry and decision theory literatures but also provides valuable insights to practitioners.

The aim of the present study is to explore the risks and benefits of mergers compared to those of strategic alliances and test the classic agency theory in relation to firm’s and shareholders interest. Using the case study methodology, the study examines the recent announced merger of Halliburton and Baker Hughes exploring the possible risks the merger itself may open up for the two firms, reviewing a possible alternative strategic alliance and the effects it may have. The paper applies a qualitative analysis based on empirical data of similar case studies projecting past experiences on future events. The study concludes that the merger was in the best interest of both companies, a merger though filled with the risk of specialisation within a shrinking market still poses the best rate of survival for firms in the gas and oil industry. The paper includes implications for strategic decision making and risk management policy in the oil & gas industry.

In the last few years the oil and gas industry has been turned around with respect to gas production and availability. Clean burning and abundant natural gas resources have caused high demand, and because of the tax incentives, coalbed methane is a popular gas source. Coalbed reservoirs are much different from conventional natural gas reservoirs because drilling and completion considerations are not the same due to the rock properties. Horizontal wellbores are considered to be very effective in reservoirs that are relatively thin, naturally fractured, and anisotropic with regard to permeability. Coalbed reservoirs have all of these features. The concern today is how to get the gas out of the coalbeds in an economic manner. Coalbed cleat systems are made up of natural fractures, hence vertical wells drilled in the reservoir must be fractured. Horizontal well drilling and completion is an alternative technique to overcome low production as well as reservoir heterogeneities in coalbed reservoirs. Some authors have shown that a properly drilled and completed horizontal well can increase production by about seventy-five percent over that of a fractured vertical well. This paper discusses coalbed properties essential to the application of horizontal drilling and completion. Several techniques used to drill and complete horizontal wells in coalbed reservoirs are discussed and compared with each other to distinguish their application. Introduction The US Bureau of Mines has demonstrated that methane drainage by horizontal and directional boreholes is a safe and effective method of removing methane in advance of mining and of controlling methane emissions during mining. Horizontal holes were found to have the advantages of relatively low drilling costs and the ability to intersect the coalbed cleat or fracture system, thus increasing permeability to gas flow. Hydraulically stimulated vertical holes on the other hand had the disadvantages of requiring large numbers of surface sites, higher costs, and production and maintenance problems. The concept of directionally drilled degasification holes was originally considered by the Bureau of Mines as a means of combining the best elements of the surface vertical borehole and underground horizontal drilling techniques. In the past few years the oil and gas industry has been turned around to be called the gas and oil industry. The clean burning, easily accessible, and overly abundant natural gas resource has created a high demand. For many years, coal mines were degasified and most operators thought little of the value of the gas. But recent demand and tax incentives have made coalbed methane gas a popular item. It is believed there is a large amount of gas stored in coalbeds throughout the United States with current estimates of 400 trillion cubic feet of gas being stored in coalbeds (Fig. 1, Table 1). Today's concern is how to get the gas out of the coalbeds in an economical manner. Recovery of gas from coalbeds occurs in the presence of the low porosity and very low permeability inherent to these beds. The permeability is made up of natural fractures which are arranged in a cleat system. There are two cleat systems: the face cleat and the butt cleat. The face cleat is continuous throughout the reservoir and provides the largest permeability. Vertical wells drilled in the reservoir must be fractured to be in contact with the cleat system and maximize recovery. Coalbeds are much different than conventional natural gas reservoirs in that drilling and completion considerations are not the same due to the unique coalbed properties.

This report examines the potential for Big Data and analytics in the upstream and midstream sectors of the oil and gas industry. IDC Energy Insights provides insight on areas where Big Data and analytics has the potential to provide business value. This report covers newer technologies, such as Hadoop/MapReduce and streaming analytics, rather than the more traditional high-performance computing. The survey data is provided from oil and gas respondents based in the United States. Guidance is provided to CIOs, enterprise architects, IT strategists, and business executives on the potential of this new technology for the oil and gas industry. Just like other industries, the oil and gas industry is experiencing an increase in the number of sensing devices in the oil fields or pipelines. Of course, the industry has always been plagued with too much data and the inability to make productive use of that data. What has changed in the past few years is the availability of new technology based on commodity hardware – Big Data and analytics – pioneered by firms like Facebook and Google. This new technology can process high volumes of various types of data at relatively quicker speeds than conventional technology. Now, oil and gas CIOs are considering whether to invest in a Big Data and analytics infrastructure. This report reviews the current attitudes toward Big Data and analytics in the oil and gas industry and explores potential applications of the technology with an eye toward speeding time to first oil, reducing costs and increasing the safety of drilling, and enhancing production.

The inherent complexity of the processes and the volatile nature of petroleum products compel the petroleum industry to continually seek and develop tools and techniques to identify, evaluate, and mitigate potential risks that can negatively impact their process operations. Additionally, government agencies and nonprofit professional societies guide the petroleum industry with regulatory guidelines, standards, and recommended best practices. The industry and these agencies and societies work to improve operational management, to ensure safe working conditions, and to minimize risk of all kinds, so that if failures occur, damage is contained within tolerable limits. This paper defines the establishment of "Health, Safety and Environment Risk Management System in the Oil Industry" course in Kuwait's Academic institutes. Not only it is designed to cover the technical aspects of HSE in the oil and gas industry, but it also enhances soft skills many students tend to overlook such as communications skills, safety awareness, ethical responsibilities, and most importantly, creating safety culture by exposing HSE awareness and knowledge to cater to the oil and gas industry. In a vision to invest in the human capital, this course will be a starting point to bridge academic gaps between academia and the oil industry throughout different disciplines, as well.

The oil and gas industry is known for its strong commitment to safety which often focuses on process safety, physical safety and behaviour, with little attention to mental health. Mental health is a growing issue. It impacts decision making, increases the likelihood of human error which can result in the loss of lives and environmental destruction. If not addressed properly, it can cause excessive stress, anxiety, depression, trauma or even suicide. Mental health is one of the biggest risks to the oil and gas industry today. Research shows that one in five workers suffer from a mental health issue at some point in time during their lives. Experts believe these statistics are higher for workers in the oil and gas industry due to the nature of the work – long working hours, isolation, being away from friends and family, feeling under high pressure to avoid mistakes due to the potentially devastating consequences and being a male dominated industry. Investment in mental health is currently often limited to Employee Assist Programs, RUOK days or wellbeing initiatives. What is needed is a total strategic and integrated approach which organisations can customise to their specific needs, distinct from a series of individual initiatives. By learning from leading practices, other industries and extending experience from building effective safety cultures within the oil and gas industry to mental health, a total strategic approach is presented which will enable organisations build their own customised blueprint and smash the stigma surrounding mental health.

Artificial Intelligence (AI) is increasingly transforming the regulatory compliance landscape in the oil and gas industry. This paper examines the profound impact of AI on ensuring adherence to complex regulatory frameworks governing this sector. Regulatory compliance in the oil and gas industry involves adhering to a myriad of environmental, safety, and operational regulations, often posing significant challenges due to the volume and complexity of data involved. AI technologies, including machine learning, natural language processing, and predictive analytics, offer innovative solutions to these challenges. AI enhances data management and analysis by automating data collection, processing, and reporting, thereby increasing accuracy and efficiency. Predictive maintenance and risk assessment tools powered by AI can identify potential compliance issues before they arise, allowing for proactive measures. Moreover, AI-driven compliance monitoring systems enable real-time tracking of regulatory adherence, reducing the risk of non-compliance and associated penalties. Automated auditing and inspection processes further streamline compliance checks, ensuring thorough and consistent evaluations. Case studies demonstrate successful AI implementations in regulatory compliance, such as automated reporting systems in offshore drilling and predictive maintenance in pipeline management, which have resulted in improved compliance rates and reduced operational risks. However, the adoption of AI is not without challenges. Issues related to data quality and integration, cybersecurity, and regulatory acceptance pose significant hurdles. Additionally, ethical and legal considerations surrounding AI deployment must be addressed to ensure responsible use. AI holds substantial potential to revolutionize regulatory compliance in the oil and gas industry by enhancing efficiency, accuracy, and proactive risk management. As AI technologies continue to evolve, their integration into compliance processes will likely become more sophisticated, offering greater benefits and addressing current limitations. The future of regulatory compliance in the oil and gas sector will be increasingly shaped by the advancements in AI, driving both operational excellence and adherence to stringent regulatory standards.

Artificial intelligence (AI) has captivated the imagination of science-fiction movie audiences for many years and has been used in the upstream oil and gas industry for more than a decade (Mohaghegh 2005, 2011). But few industries evolve more quickly than those from Silicon Valley, and it accordingly follows that the technology has grown and changed considerably since this discussion began. The oil and gas industry, therefore, is at a point where it would be prudent to take stock of what has been achieved with AI in the sector, to provide a sober assessment of what has delivered value and what has not among the myriad implementations made so far, and to figure out how best to leverage this technology in the future in light of these learnings. When one looks at the long arc of AI in the oil and gas industry, a few important truths emerge. First among these is the fact that not all AI is the same. There is a spectrum of technological sophistication. Hollywood and the media have always been fascinated by the idea of artificial superintelligence and general intelligence systems capable of mimicking the actions and behaviors of real people. Those kinds of systems would have the ability to learn, perceive, understand, and function in human-like ways (Joshi 2019). As alluring as these types of AI are, however, they bear little resemblance to what actually has been delivered to the upstream industry. Instead, we mostly have seen much less ambitious “narrow AI” applications that very capably handle a specific task, such as quickly digesting thousands of pages of historical reports (Kimbleton and Matson 2018), detecting potential failures in progressive cavity pumps (Jacobs 2018), predicting oil and gas exports (Windarto et al. 2017), offering improvements for reservoir models (Mohaghegh 2011), or estimating oil-recovery factors (Mahmoud et al. 2019). But let’s face it: As impressive and commendable as these applications have been, they fall far short of the ambitious vision of highly autonomous systems that are capable of thinking about things outside of the narrow range of tasks explicitly handed to them. What is more, many of these narrow AI applications have tended to be modified versions of fairly generic solutions that were originally designed for other industries and that were then usefully extended to the oil and gas industry with a modest amount of tailoring. In other words, relatively little AI has been occurring in a way that had the oil and gas sector in mind from the outset. The second important truth is that human judgment still matters. What some technology vendors have referred to as “augmented intelligence” (Kimbleton and Matson 2018), whereby AI supplements human judgment rather than sup-plants it, is not merely an alternative way of approaching AI; rather, it is coming into focus that this is probably the most sensible way forward for this technology.