Managing Uncertainty in Large-Scale Inversions for the Oil and Gas Industry with Big Data

Author(s):  
Jiefu Chen ◽  
Yueqin Huang ◽  
Tommy L. Binford ◽  
Xuqing Wu
2021 ◽  
Author(s):  
Nouf AlJabri ◽  
Nan Shi

Abstract Nanoemulsions (NEs) are kinetically stable emulsions with droplet size on the order of 100 nm. Many unique properties of NEs, such as stability and rheology, have attracted considerable attention in the oil industry. Here, we review applications and studies of NEs for major upstream operations, highlighting useful properties of NEs, synthesis to render these properties, and techniques to characterize them. We identify specific challenges associated with large-scale applications of NEs and directions for future studies. We first summarize useful and unique properties of NEs, mostly arising from the small droplet size. Then, we compare different methods to prepare NEs based on the magnitude of input energy, i.e., low-energy and high-energy methods. In addition, we review techniques to characterize properties of NEs, such as droplet size, volume fraction of the dispersed phase, and viscosity. Furthermore, we discuss specific applications of NEs in four areas of upstream operations, i.e., enhanced oil recovery, drilling/completion, flow assurance, and stimulation. Finally, we identify challenges to economically tailor NEs with desired properties for large-scale upstream applications and propose possible solutions to some of these challenges. NEs are kinetically stable due to their small droplet size (submicron to 100 nm). Within this size range, the rate of major destabilizing mechanisms, such as coalescence, flocculation, and Ostwald ripening, is considerably slowed down. In addition, small droplet size yields large surface-to-volume ratio, optical transparency, high diffusivity, and controllable rheology. Similar to applications in other fields (food industry, pharmaceuticals, cosmetics, etc.), the oil and gas industry can also benefit from these useful properties of NEs. Proposed functions of NEs include delivering chemicals, conditioning wellbore/reservoir conditions, and improve chemical compatibility. Therefore, we envision NEs as a versatile technology that can be applied in a variety of upstream operations. Upstream operations often target a wide range of physical and chemical conditions and are operated at different time scales. More importantly, these operations typically consume a large amount of materials. These facts not only suggest efforts to rationally engineer properties of NEs in upstream applications, but also manifest the importance to economically optimize such efforts for large-scale operations. We summarize studies and applications of NEs in upstream operations in the oil and gas industry. We review useful properties of NEs that benefit upstream applications as well as techniques to synthesize and characterize NEs. More importantly, we identify challenges and opportunities in engineering NEs for large-scale operations in different upstream applications. This work not only focuses on scientific aspects of synthesizing NEs with desired properties but also emphasizes engineering and economic consideration that is important in the oil industry.


The distinctive feature of petroleum businesses is its wide scope. After crude oil or gas extraction, resulting semi-products undergo dozens of transformation stages in supply chains to reach the final customer. Combination of quantity and quality multiplied by external market factors produce price fluctuations that are challenging for world economics. In this regard process management might be carried out to improve supply chain performance and assure the maximum business predictability. However, for such large-scale organizations it requires big effort in operational analysis, process enhancement and process control via information systems which successfully support traditional management in function-oriented organizational structures. This chapter explores the developed engineering matrix that embraces potential methods and tools applicable for oil and gas industry. Additionally, it reveals industrial peculiarities and delivers case studies about Iranian and Hungarian petroleum companies.


2014 ◽  
Vol 32 (4) ◽  
pp. 687-697 ◽  
Author(s):  
Martine B. Hannevik ◽  
Jon Anders Lone ◽  
Roald Bjørklund ◽  
Cato Alexander Bjørkli ◽  
Thomas Hoff

2017 ◽  
Vol 08 (1) ◽  
pp. 3-13
Author(s):  
Ramiz Aliguliyev ◽  
◽  
Yadigar Imamverdiyev ◽  

2011 ◽  
Vol 51 (2) ◽  
pp. 736
Author(s):  
Allan Drake-Brockman ◽  
Daniel White

Since the commencement of the Fair Work Act 2009 (Cth) (FW Act) on 1 July 2009, there has been a significant increase in union activity in Australia’s oil and gas industry. Recent case examples concerning the Pluto Project and various other disputes flag the importance of project managing industrial relations to ensure project delivery dates are met. Due to the contract interdependencies on large scale oil and gas projects, industrial action taken by a union in relation to a single sub-contractor can have ripple effects—causing budget blow-outs. Emerging union influence is such a concern that some of Australia’s leading companies operating in the oil and gas industry now identify industrial activity as a key project risk. Furthermore, many Australian leading financial institutions now assess a company’s potential exposure to industrial action as part of their key lending criteria. New innovative industrial relations strategies are now part of the weaponry Australian unions use when representing their members—this includes global union strategies. Moreover, there is already evidence that the FW Act can promote the occurrence of demarcation disputes between unions. This type of industrial activity leads to poor outcomes for employers and can prove to be very costly—especially in a multi-million dollar a day industry. Providing insight into the recent union activities in the industry are the following cases: Heath v Gravity Crane Services Pty Ltd Boskalis Australia Pty Ltd v Maritime Union of Australia CFMEU v Woodside Burrup Pty Ltd Offshore Marine Services Pty Ltd v Maritime Union of Australia There are a number of strategies oil and gas companies and sub-contractors can use to mitigate the effects of union influence in the workplace.


2021 ◽  
Author(s):  
Iraj Ershaghi ◽  
Milad A. Ershaghi ◽  
Fatimah Al-Ruwai

Abstract A serious issue facing many oil and gas companies is the uneasiness among the traditional engineering talents to learn and adapt to the changes brought about by digital transformation. The transformation has been expected as the human being is limited in analyzing problems that are multidimensional and there are difficulties in doing analysis on a large scale. But many companies face human factor issues in preparing the traditional staff to realize the potential of adaptation of AI (Artificial Intelligence) based decision making. As decision-making in oil and gas industry is growing in complexity, acceptance of digital based solutions remains low. One reason can be the lack of adequate interpretability. The data scientist and the end-users should be able to assure that the prediction is based on correct set of assumptions and conform to accepted domain expertise knowledge. A proper set of questions to the experts can include inquiries such as where the information comes from, why certain information is pertinent, what is the relationship of components and also would several experts agree on such an assignment. Among many, one of the main concerns is the trustworthiness of applying AI technologies There are limitations of current continuing education approaches, and we suggest improvements that can help in such transformation. It takes an intersection of human judgment and the power of computer technology to make a step-change in accepting predictions by (ML) machine learning. A deep understanding of the problem, coupled with an awareness of the key data, is always the starting point. The best solution strategy in petroleum engineering adaptation of digital technologies requires effective participation of the domain experts in algorithmic-based preprocessing of data. Application of various digital solutions and technologies can then be tested to select the best solution strategies. For illustration purposes, we examine a few examples where digital technologies have significant potentials. Yet in all, domain expertise and data preprocessing are essential for quality control purposes


Author(s):  
Masahiko Tsukakoshi ◽  
Mostafa Al Mamun ◽  
Kazunori Hashimura ◽  
Hiromi Hosoda ◽  
Steven C. Peak

Sign in / Sign up

Export Citation Format

Share Document