Digital platform for E&P Assets Business Process Optimization with a Module for Estimation and Optimizing of Greenhouse Gases Emissions. Case Study

2021 ◽  
Author(s):  
Denis Tokarev ◽  
Dmitry Tailakov ◽  
Anton Ablaev

Resume Due to the increasing requirements for reducing the carbon footprint on the part of end users of hydrocarbons, there is a need to develop a system for automated analysis of the main business processes of oil and gas field development to assess greenhouse gas emissions, as well as for optimization in order to improve environmental safety. The paper describes a prototype of a platform that was developed for decarbonization of oil and gas enterprises using modern optimization tools and up-to-date methods for inventory of greenhouse gas emissions. The platform is based on the following models: – simulation model (IM) – simulates the company's business processes, identifying weaknesses and areas of potential development, is a set of mathematical algorithms for solving direct problems; – optimization model (OM) – allows to conduct a comprehensive analysis with a large number of parameters, excluding manual data processing and using automated information exchange between various software that is used in the oil and gas industry for modeling and monitoring of various processes, as well as developing various development options (taking into account geological conditions, geophysical interpretation, etc.). The initial conditions and the specified criteria related to economic indicators allow to solve the problem of finding the optimal parameters for the development of the selected asset. This paper shows the economic effect of implementing software based on a digital twin, implemented as a platform with the ability to build a model of an oil and gas asset, using various data (SAP, 1C, IPM GAP, Repos, Eclipse, etc.) and targets for the development. In the same way, the possible losses of the oil and gas industry from the introduction of additional carbon taxation and the potential for optimizing processes to minimize these costs are considered. IPCC methods are used to calculate greenhouse gas emissions, and direct, indirect, and fugitive emissions are considered in the calculation. The main conclusion is the need to reduce the costs for oil and gas companies and prepare modern automated digital solutions for accounting for greenhouse gas emissions in advance to achieve a zero-carbon footprint and maintain the competitiveness of the Russian oil and gas industry. As a result of the work done, the feasibility was justified, and the result was demonstrated to the customer for calculating greenhouse gas emissions based on digital twins of key business processes of oil and gas enterprises. The use of automated systems makes it possible to reduce the potential economic risks associated with the introduction of a carbon fee from large oil and gas consumers.

2012 ◽  
Author(s):  
Robert Siveter ◽  
Karin Ritter ◽  
Michael Clowers ◽  
Arthur Lee ◽  
Jaime Martin Juez ◽  
...  

2018 ◽  
Vol 58 (2) ◽  
pp. 493
Author(s):  
Joachim Bamberger ◽  
Ti-Chiun Chang ◽  
Brian Mason ◽  
Amer Mesanovic ◽  
Ulrich Münz ◽  
...  

As our energy systems evolve with the adoption of more variable renewable energy resources, so will our oil and gas industry play a pivotal role in what is expected to be a lengthy transitional phase to a greater mix of renewables with a reliance on fast, reliable gas peaking power generation, which have lower greenhouse gas emissions, and short delivery periods to construct. Oil and gas companies are also rapidly moving towards becoming integrated energy companies supplying a mix of gas, oil, photovoltaic power, wind power and hydrogen, coupling these into the electrical and gas grids. We discuss some of the components and tasks of a distributed energy system in its various system guises that contribute to a more cost effective, reliable and resilient energy system with lower greenhouse gas emissions. We discuss the role that hydrogen will play in the future as oil and gas companies explore alternatives to fossil fuels to address their need to reduce their carbon footprint, substituting or supplementing their conventional gas supply with renewably produced hydrogen. We talk about how Australia with its excellent renewable resources and the opportunity to potentially develop a new industry around the production of renewable fuels, power-to-X, such as hydrogen, with the potential for the oil and gas industry to leverage its existing assets (i.e. gas pipelines) and future embedded renewable assets to produce hydrogen through electrolysis with the intention of supplementing their liquefied natural gas exports with a portion of renewably produced hydrogen.


2012 ◽  
Vol 52 (2) ◽  
pp. 660
Author(s):  
Mathew Nelson

The oil and gas industry in Australia consists of a range of complicated joint venture (JV) and processing arrangements. With a future price on carbon in the Clean Energy Future Legislation Package, parties are keen to understand their carbon liabilities where they have interests (both operated and non-operated), and the extent to which a price on carbon can be passed on to customers. Many oil and gas companies have been reporting greenhouse gas emissions from their facilities to the Department of Climate Change and Energy Efficiency since 2009 using the National Greenhouse and Energy Reporting System framework. Subsequently, numerous companies from the sector have developed greenhouse gas reporting systems linking into existing oil and gas production allocation systems. These companies are now turning their attention to using this information to allocate greenhouse gas emissions from their facilities to specific oil and gas sales products, as well as to JV partners. This extended abstract, which includes a case study, explores these developments and discusses the key considerations when allocating greenhouse gas emissions to specific products and JV partners. Also explored are the following questions: What assumptions need to be made at the facility level for emissions associated with extracting, processing and refining specific products ready for sale? How robust and defensible are these assumptions? How do you build these assumptions into a system or model that allocates emissions to different products? What processes do you then put in place to allocate emissions to specific JV partners, and what information will be reported to them and what quality and assurance processes need to be in place to provide comfort to your JV partners of the robustness of the numbers? How will the costs associated with carbon be allocated?


Sign in / Sign up

Export Citation Format

Share Document