Research status and application of artificial intelligence large models in the oil and gas industry

This article elucidates the concept of large model technology,summarizes the research status of large model technology both domestically and internationally,provides an overview of the application status of large models in vertical industries,outlines the challenges and issues confronted in applying large models in the oil and gas sector,and offers prospects for the application of large models in the oil and gas industry.The existing large models can be briefly divided into three categories:large language models,visual large models,and multimodal large models.The application of large models in the oil and gas industry is still in its infancy.Based on open-source large language models,some oil and gas enterprises have released large language model products using methods like fine-tuning and retrieval augmented generation.Scholars have attempted to develop scenario-specific models for oil and gas operations by using visual/multimodal foundation models.A few researchers have constructed pre-trained foundation models for seismic data processing and interpretation,as well as core analysis.The application of large models in the oil and gas industry faces challenges such as current data quantity and quality being difficult to support the training of large models,high research and development costs,and poor algorithm autonomy and control.The application of large models should be guided by the needs of oil and gas business,taking the application of large models as an opportunity to improve data lifecycle management,enhance data governance capabilities,promote the construction of computing power,strengthen the construction of“artificial intelligence+energy”composite teams,and boost the autonomy and control of large model technology.

Review on the challenges and strategies in oil and gas industry's transition towards carbon neutrality in China

In light of carbon-neutral pledge, the oil and gas industry has been facing several critical new challenges in China. The current status and new challenges in terms of market mechanism reform, supply-consumption balance and key technology innovation in China's oil and gas industry are reviewed in the present study, and new strategies and roadmaps are proposed to cope with the challenges. The study found that (i) the oil and gas market faces challenges such as incomplete pricing mechanisms, unclear subject rights, and the lack of recognition and trading of carbon assets. (ii) the trade-off between short-term supply security and long-term low-carbon supply is the most critical issue. (iii) in addition to typical challenges such as immature technology and lack of funding support, the unclear multiple technology coupling development mode also poses problems for the low-carbon transformation of the oil and gas industry. To address these new challenges, comprehensive strategies and roadmaps for China's oil and gas industry towards carbon neutrality are proposed and discussed in the aspects of participating in market transactions, restructuring production and consumption, deploying key technology innovations, and planning enterprise strategies. The present study is expected to provide a blueprint for the future development of China's oil and gas industry towards carbon neutrality.

Opportunities and Challenges of Robotics and Automation in Offshore Oil &Gas Industry

The oil and gas industry will continue to boom in the coming few decades. Obtaining oil and gas from conventional and non-conventional resources will become more and more challenging. This intensifying need will impose very considerable demands on work force, financial and technology capabilities. Since the future supplies of oil and gas are to expand, advanced technology will become increasingly necessary to obtain access to more challenging conventional and non-conventional resources. Therefore oil and gas technologies will be very costly to operate in the coming future due to hostile, hard-to-reach environments. The offshore oil industry will become a complicated myriad of advanced equipment, structures, and work force. Our objectives are to identify potential applications and research directions of robotics and automation in the oil & gas field and explore the obstacles and challenges of robotic and automation applications to this area. This study performs the necessary survey and investigation about the work conditions of robotics and automation equipment in the oil and gas industry, especially offshore oil rigs. The oil & gas industry processes are first investigated. The personals and tasks are then explored. Furthermore, this paper reviews the current robotic automation technology. The challenges and requirements are identified for robotics and automation equipment in the oil and gas industry. The requirements of robotics and automation in the oil & gas industry are presented. Future research opportunities are discussed from a technical perspective.

Environmental Policies and Strategies in Nigeria Oil and Gas Industry: Gains, Challenges and Prospects

The paper reviews environmental policies and strategies in the Nigerian oil and gas industry sector, assessing its efficiency, challenges and prospects. Essentially, the study established that the Environmental Policies and Strategies of Nigeria Oil and Gas Industry have impacted positively on the Nigerian environment over the years, especially in the area of awareness creation for all stake-holders. In terms of challenges, inefficiency of the regulators due to inadequacy of logistics, poor environmental data base, duplication and overlaps of regulators functions are some of the challenges identified. The prospect of environmental policies and strategies in Nigeria is generally considered to be bright, considering the fact that the industry is still evolving. Relevant recommendations were made on how to achieve improvements.

Risk Matrix as a Tool for Risk Analysis in Underwater Operations in the Oil and Gas Industry

The study is a cross-sectional design assessment of the likelihood, frequency and severity of hazards associated with underwater operations in the Niger Delta. Five oil and gas companies were used for this study selected by a purposive method given that they had the highest number of workers involved in underwater operations. A sample size of 418 was computed to which the questionnaires were administered with response rate of 95.93%. Data analyses were carried out to cover descriptive statistics, analysis of variance and Pearsonal correlation coefficients. The 4 by 4 risk assessment matrix for the likelihood and consequences showed that 8 out of 20 underwater hazards were categorized as having very high risk according to their risk ratings. The eight hazards categorized based on their risk IDs were H01, H03, H04, H08, H10, H11, H12, and H15. The 4 by 4 risk matrix for frequency and consequences revealed that two hazards (Piracy & bandit attack/kidnapping (H01) and Other main vessels/heavy object dropping or falling load/collision (H08)) were identified to be of very high risk.

Contract Labor and the Right to Freedom of Association in the Oil and Gas Industry in Nigeria

Contract labor is one of several terms, which are widely used to describe work arrangements, which do not fall within the traditional definition of employment. Contracting out services and getting employees through contractors have become widespread practice by many employers because it helps them to cut cost since these contractors could often supply these workers more cheaply and efficiently. Labor rights and standards are sometimes seen as sacrificial lambs on the altar of competitive edge by companies due to the perception that they constitute ＂costs＂ which if eliminated or reduced to the barest minimum, will impact positively on the ability of companies to compete favorably in the global market and consequent improvement of their balance sheets, to the joy of shareholders. Contract work is increasingly becoming the norm in Nigeria＇s oil and gas industry as companies undergo restructuring, concentration on core activities and modifications in work organization and technology. These factors certainly affect traditional employment relations and the exercise of freedom of association and collective bargaining rights inherent in them. Contract workers now make up about 60% of the workforce in the industry and they are denied the right to organize into Unions. The denial of this right has resulted in exploitation of these workers. This paper seeks to examine the adequacy of labor law governing trade unionism in Nigeria in ensuring the right of contract workers to freedom of association, as well as its conformity to international labor standards. It is argued that Nigerian labor laws need to be enforced to ensure that this category of workers benefits from this right. In addition a proposal is made for a law reform which will define contract labor and provide a legal framework for the regulation and protection of contract workers in Nigeria in order to guarantee their right to unionize and enable them to improve their rights at work.

Fuzzy logic applied to value of information assessment in oil and gas projects

The concept of value of information(VOI)has been widely used in the oil industry when making decisions on the acquisition of new data sets for the development and operation of oil fields.The classical approach to VOI assumes that the outcome of the data acquisition process produces crisp values,which are uniquely mapped onto one of the deterministic reservoir models representing the subsurface variability.However,subsurface reservoir data are not always crisp;it can also be fuzzy and may correspond to various reservoir models to different degrees.The classical approach to VOI may not,therefore,lead to the best decision with regard to the need to acquire new data.Fuzzy logic,introduced in the 1960 s as an alternative to the classical logic,is able to manage the uncertainty associated with the fuzziness of the data.In this paper,both classical and fuzzy theoretical formulations for VOI are developed and contrasted using inherently vague data.A case study,which is consistent with the future development of an oil reservoir,is used to compare the application of both approaches to the estimation of VOI.The results of the VOI process show that when the fuzzy nature of the data is included in the assessment,the value of the data decreases.In this case study,the results of the assessment using crisp data and fuzzy data change the decision from"acquire"the additional data(in the former)to"do not acquire"the additional data(in the latter).In general,different decisions are reached,depending on whether the fuzzy nature of the data is considered during the evaluation.The implications of these results are significant in a domain such as the oil and gas industry(where investments are huge).This work strongly suggests the need to define the data as crisp or fuzzy for use in VOI,prior to implementing the assessment to select and define the right approach.

Bioremediation Technology Potential for Management of Soil and Water Pollution from Anticipated Rapid Industrialization and Planned Oil and Gas Sector in Uganda: A Review

Oil exploitation in many African countries is associated with litigation and conflicts to water and soil pollution. It is because of inadequate planning for management of oil spills and industrial effluents in environmentally sustainable manner. Uganda’s natural resources such as soils and water bodies are threatened by contamination due to rapid industrialization and rural-urban migration in established Industrial Business Parks and planned oil and gas production at Albertine Graben Region. The low level of compliance to industrial effluents discharge standards relevant to specific environmental receptors and activities within oil and gas sector development pose a big question of how to sustain the biodiversity and natural resource management. Experiences from elsewhere have shown bioremediation as a viable and proven option to provide potentially manageable solutions to resulting pollution as a substitute to modern well-known remediation methods, for it is relatively cheaper, more efficient and minimal toxic byproducts after treatment. The most used bioremediation agents in different studies reviewed are bacterial species especially Pseudomonas and Bacillus, followed by Aspergillus a fungi species, microalgae and aquatic plants such as duckweed, macrophytes and pteridophytes. Regardless of the waste produced in either oil and gas sector or industries, these agents have shown greater biodegradation rates. Pseudomonas sp. has a degradation efficiency of oil compounds ranging from 90% - 100%, and Aspergillus sp. 75% - 95%. Some aquatic plants can thrive in created wetlands with relatively still water such as Phragmites australis which can degrade hydrocarbons especially Aromatic compounds with benzene ring up to 95%. It can thrive in salty water with high pH range of 4.8 - 8.2. With industrial wastewater, algae is the most dominant with the degradation rates varying from 65% -100% and bacteria at 70% - 90%. Most of the reported results are in the developed country context. In developing countries, duckweed is reported as the commonest aquatic plant in wastewater treatment for removal of heavy metals because it is more tolerant to a wide range of environmental conditions and produce biomass faster. It has a removal rate of heavy metals between 90% and 100%. Basing on literature data analysis, bacteria are more suitable for treating water from oil pollution using Pseudomonas sp. Phragmites australis is suited for cleaning up oil in both water and soil. Duckweed is the best in treating water polluted with industrial effluents. This paper presents the different bioremediation methods that Uganda can potentially apply to mitigate the increased risk of environmental pollutions from planned industrialization and oil and gas development in the Albertine Graben Region.

Empirical Investigation of Treatment of Sour Gas by Novel Technology: Energy Optimization

The sour gas sweetening is one of the main processes in gas industries. Gas sweetening is done through chemical processes. Therefore, it requires high cost and energy. The results show that increasing the operating temperature increases the mass transfer coefficient and increases the mass transfer rate. Theoretical and experimental data show that sulfur removal in 4.5 W magnetic field is desirable. The increase in sulfur removal percentage in the magnetic field of 4.5 W and 6.75 W is about 16.4% and 15.2%, respectively. According to the obtained results, the effect of temperature increase from 18.8°C to 23.4°C is more evident than the effect of temperature change from 23.4°C to 32.2°C. Because more thermal energy is needed to provide higher temperatures. Therefore, the temperature of 23.4°C is reported as the optimal temperature. The results of this research show that the percentage of sulfur removal is also high at this temperature.

Natural Resource Governance in Unrecognized Settings: What Are Emerging Political, Legal and Fiscal Issues Affecting “Somaliland”?

Somaliland declared independence after the fall of the Central Government of Somalia in 1991. Early peace settlements and state-building efforts led to transitional government and early democratic contestations including presidential elections in a hybrid state framework. This emerging democracy in a conflict-torn region is challenged by weak accountability and power imbalances between the three government branches. Over the past few years, the current ruling party started to engage with foreign companies to carry out exploration activities in onshore blocks utilizing existing information on the distribution of natural resources of oil, and gas and to lesser extent mining. Following an informal auction of selling licenses for resource exploration among various companies, Genel Energy amongst others;Somaliland has no competent institutions in managing revenues for long-term development due to two distinctive factors: 1) absence of strong legal and political frameworks specific to governance of extractive industry;2) weak fiscal regimes across spectrum of extractive companies, the state and investors.

Science and Technology of China Onshore Petroleum Industry Towards 21st Century（Part 4）

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Gazprom Neft will jointly develop West Siberian oilfields with Mubadala Petroleum and RDIF

According to the World Oil report from Moscow on September 5,Gazprom Neft,Russia's third-largest oil company,Mubadala Petroleum and Russian Direct Investment Fund (RDIF)announced on the 5th that they had completed a deal to set up a joint venture to develop oilfields in the Tomsk and Omsk regions of west Siberian. After the deal,Gazprom Neft now has a 51% stake in the joint venture,compared to 44% for Mubadala Petroleum and 5% for RDIF.Gazprom's Vostok LLC,which remains a subsidiary of Gazprom Neft,will continue to operate the oil fields.Gazprom's Vostok LLC joint venture is the Mubadala Petroleum's first investment in Russia's oil and gas industry.

The Accounting and Economic Effects of Currency Translation Standards： AASB 1012 vs. AASB 121

This paper1 empirically examines the accounting and the economic effects of foreign exchange rate fluctuations on the oil and gas industry under the former and the current translation accounting standards in Australia. Due to the unique features of the oil and gas industry and based on an analysis of the former standard-Australian Accounting Standards Board （AASB） 1012, the authors predict that a positive translation adjustment （the accounting effect） is associated with a loss, instead of a creation of the firm value （the economic effect） under AASB 1012. The authors also predict that the new standard AASB 121, adapted from the International Accounting Standard （IAS） 21 with modifications, will report translation adjustments that are consistent with the economic effects. By using Australia-based multinational oil and gas firms, the authors find that translation adjustments under AASB 1012 are inversely associated with firm value and that the relationship changes to a positive one under AASB 121. This study concludes that the new standard has the potential to improve the quality of the translation accounting information.

Geographical Space Distribution of China's Oil and Gas Industry:Characteristics and Drivers

Here, the geographical space distribution of the oil and gas industry in China is comprehensively investigated using the overal Moran’s I index and local Moran’s I index. We found that China’s oil and gas industry development from 2000 to 2010 has a differentiated geographical space distribution upstream （extractive industry） but not downstream （reifning industry）. To analyze upstream and downstream states a spatial econometrics model （SEM） was used to identify inlfuential factors resulting from the spatial concentration of the oil and gas industry. An external effect is the key factor promoting the spatial concentration of the upstream industry in China;governmental economic policy is another important factor.

Relevance of Marketing Strategies for Gas Stations in China - An Analysis Using SPSS

This study aims to find out the relevance of marketing strategies for gas stations in China.According to IBISWorld,the companies holding the largest market shares in China’s gas station industry include China Petrochemical Corporation,China National Petroleum Corporation,Sinochem Corporation,China National Offshore Oil Corporation,and BP(China)Holdings Limited.Marketing has changed over the past several years.Similarly,gas station marketing is all about more customers,greater sales,and higher profits.Technology provides many different marketing tools to see more fresh faces at the door,increase repeat sales,and improve profits.Word-of-mouth advertising should be encouraged,especially when contests are being held.The prizes from these contests may include car essentials,free coffee,free car wash,or coupons to be used at convenience stores.Customers who have won these contests would surely go around advertising the particular gas station,ultimately bringing in more customers.Other than that,managers can boost the sales volume through radio promotions as well.This study also aims to give future businessmen and women some ideas on how to deal with different kinds of strategies when it comes to marketing,especially in China in hope to cater and prove to the people of China the possibility of promoting businesses,such as the oil industry.

Big Data analytics in oil and gas industry: An emerging trend

This paper reviews the utilization of Big Data analytics,as an emerging trend,in the upstream and downstream oil and gas industry.Big Data or Big Data analytics refers to a new technology which can be employed to handle large datasets which include six main characteristics of volume,variety,velocity,veracity,value,and complexity.With the recent advent of data recording sensors in exploration,drilling,and production operations,oil and gas industry has become a massive data intensive industry.Analyzing seismic and micro-seismic data,improving reservoir characterization and simulation,reducing drilling time and increasing drilling safety,optimization of the performance of production pumps,improved petrochemical asset management,improved shipping and transportation,and improved occupational safety are among some of the applications of Big Data in oil and gas industry.Although the oil and gas industry has become more interested in utilizing Big Data analytics recently,but,there are still challenges mainly due to lack of business support and awareness about the Big Data within the industry.Furthermore,quality of the data and understanding the complexity of the problem are also among the challenging parameters facing the application of Big Data.

Advances in the application of biomimetic surface engineering in the oil and gas industry

Friction is widespread in almost every field in the oil and gas industry,and it is accompanied by huge energy losses and potential safety hazards.To deal with a series of questions in this regard,biomimetic surfaces have been developed over the past decades to significantly reduce economic losses.Presently,biomimetic surface engineering on different scales has been successfully introduced into related fields of the oil and gas industry,such as drill bits and the inner surfaces of pipes.In this review,we focused on the most recent and promising efforts reported toward the application of a biomimetic surface in oil and gas fields,indicating the necessity and importance of establishing this disciplinary study.Regarding the oil and gas industry,we mainly analyzed and summarized some important research results into the following three aspects:(i)applications in reducing the wear of exploration production equipment and its components,(ii)separation and drag release technologies in oil/gas storage and transportation,and(iii)functional coatings used in oil and gas development in oceans and polar regions.Finally,based on an in‐depth analysis of the development of biomimetic surface engineering in the fields of oil and gas,some conclusions and perspectives are also discussed.It is expected that biomimetic surface engineering can be used in oil and gas fields more widely and systematically,providing important contributions to green development in the near future.

Application of machine learning and artificial intelligence in oil and gas industry

Oil and gas industries are facing several challenges and issues in data processing and handling.Large amount of data bank is generated with various techniques and processes.The proper technical analysis of this database is to be carried out to improve performance of oil and gas industries.This paper provides a comprehensive state-of-art review in the field of machine learning and artificial intelligence to solve oil and gas industry problems.It also narrates the various types of machine learning and artificial intelligence techniques which can be used for data processing and interpretation in different sectors of upstream oil and gas industries.The achievements and developments promise the benefits of machine learning and artificial intelligence techniques towards large data storage capabilities and high efficiency of numerical calculations.In this paper a summary of various researchers work on machine learning and artificial intelligence applications and limitations is showcased for upstream and sectors of oil and gas industry.The existence of this extensive intelligent system could really eliminate the risk factor and cost of maintenance.The development and progress using this emerging technologies have become smart and makes the judgement procedure easy and straightforward.The study is useful to access intelligence of different machine learning methods to declare its application for distinct task in oil and gas sector.