Subsurface engineering of CCUS in Australia (case studies)

2019 ◽  
Vol 59 (2) ◽  
pp. 762
Author(s):  
Mohammad B. Bagheri ◽  
Matthias Raab
Keyword(s):  
Uncertainty Analysis ◽  
Case Studies ◽  
Oil And Gas ◽  
Co2 Storage ◽  
Oil And Gas Industry ◽  
Reservoir Engineering ◽  
Co2 Injection ◽  
Gas Industry ◽  
Co2 Plume

Carbon capture utilisation and storage (CCUS) is a rapidly emerging field in the Australian oil and gas industry to address carbon emissions while securing reliable energy. Although there are similarities with many aspects of the oil and gas industry, subsurface CO2 storage has some unique geology and geophysics, and reservoir engineering considerations, for which we have developed specific workflows. This paper explores the challenges and risks that a reservoir engineer might face during a field-scale CO2 injection project, and how to address them. We first explain some of the main concepts of reservoir engineering in CCUS and their synergy with oil and gas projects, followed by the required inputs for subsurface studies. We will subsequently discuss the importance of uncertainty analysis and how to de-risk a CCUS project from the subsurface point of view. Finally, two different case studies will be presented, showing how the CCUS industry should use reservoir engineering analysis, dynamic modelling and uncertainty analysis results, based on our experience in the Otway Basin. The first case study provides a summary of CO2CRC storage research injection results and how we used the dynamic models to history match the results and understand CO2 plume behaviour in the reservoir. The second case study shows how we used uncertainty analysis to improve confidence on the CO2 plume behaviour and to address regulatory requirements. An innovative workflow was developed for this purpose in CO2CRC to understand the influence of each uncertainty parameter on the objective functions and generate probabilistic results.

Machine Learning Models With Engineering Insight: Case Studies From the Oil and Gas Industry

2020 ◽  
Author(s):  
Ishita Chakraborty ◽  
Daniel Kluk ◽  
Scot McNeill
Keyword(s):  
Machine Learning ◽  
Case Studies ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Mooring Line ◽  
Learning Models ◽  
Gas Industry ◽  
Position Data ◽  
Machine Learning Models

Abstract Machine learning is gaining rapid popularity as a tool of choice for applications in almost every field. In the oil and gas industry, machine learning is used as a tool for solving problems which could not be solved by traditional methods or for providing a cost-effective and faster data driven solution. Engineering expertise and knowledge of fundamentals remain relevant and necessary to draw meaningful conclusions from the data-based models. Two case studies are presented in different applications that will illustrate the importance of using engineering domain knowledge for feature extraction and feature manipulation in creating insightful machine learning models. The first case study involves condition-based monitoring (CBM) of pumps. A variety of pumps are employed in all aspects of the oilfield life cycle, such as drilling, completion (including hydraulic fracturing), production, and intervention. There is no well-established method to monitor the pump fault states as they are operating based on sensor feedback. As a result, maintenance is performed either prematurely or reactively, both of which result in wasteful downtime and unnecessary expense. A machine learning based neural network model is used for identifying different fault states in a triplex pump from measured pressure sensor data. In the second case study, failures of mooring lines of an offshore floating production unit are predicted from the vessel position data. Identifying a damaged mooring line can be critical for the structural health of the floating production system. In offshore floating platforms, mooring line tension is highly correlated to a vessel’s motions. The vessel position data is created from running coupled analysis models. A K-Nearest-Neighbor (KNN) classifier model is trained to predict mooring line failures. In all the case studies, the importance of combining a deep understanding of the physics of the problem with machine learning tools is emphasized.

Value Co-Creation Practices in the Decommissioning of Offshore Platforms: A Case Study Approach

2021 ◽  
pp. 239496432110320
Author(s):  
Francesca Loia ◽  
Vincenzo Basile ◽  
Nancy Capobianco ◽  
Roberto Vona
Keyword(s):  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Future Research ◽  
Offshore Platforms ◽  
Gas Industry ◽  
Study Approach ◽  
Collaborative Interactions ◽  
Exploratory Approach ◽  
Italian Context

Over the years, value co-creation practices have become increasingly more important by supporting collaborative interactions and the achievement of sustainable and mutual competitive advantage between the ecosystem’ actors. In this direction, the oil and gas industry is proposing a sustainable re-use of offshore platforms based on value co-creation and resources exchange between the actors involved. According to this consideration, this work aims at re-reading the decommissioning of offshore platforms in the light of value co-creation practices, trying to capture the factors that governments and companies can leverage to pursue a sustainable development of local communities. To reach this goal, this work follows an exploratory approach by using, in particular, the case study. Specifically, one of the most notably projects in the Italian context have been chosen, the Paguro platform, in order to provide empirical insights into the nature of these value co-creation processes. Five value co-creation practices have been identified which highlight the importance of synergistic efforts of institutions, companies and technology-based platforms for improving the ability to co-create and capture value in the process of decommissioning. This exploratory work establishes a foundation for future research, and offers theoretical and managerial guidance in this increasingly important area.

Complex Subsurface Well Abandonments Using Relief Well Methodologies

2021 ◽  
Author(s):  
Jamie Dorey ◽  
Georgy Rassadkin ◽  
Douglas Ridgway
Keyword(s):  
Case Studies ◽  
Best Practice ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Gas Industry ◽  
Gas Seepage ◽  
Cost Efficient ◽  
Well Abandonment ◽  
Efficient Option ◽  
Practice Methods

Abstract The field experience in the continental US suggests that approximately 33% of plug and abandonment operations are non-routine, and 5% require re-entry (Greer C.R., 2018). In some scenarios, the most cost-efficient option for the intervention is drilling an intercept well to re-enter the target well or multiple wells externally using advanced survey management and magnetic ranging techniques. This paper presents the methods applied of relief well methodologies from the planning to execution of a complex multiple-well abandonment project. Improvements in Active Magnetic Ranging sensor design and applications have improved the availability of highly precise tools for the purpose of locating and intercepting wellbores where access is not possible. These instruments were commonplace on relief well interventions, however, have found a new application in solving one of the major issues facing the oil and gas industry. Subsurface abandonments are a complex task that requires a robust methodology. In this paper, we describe the techniques that have been built upon the best practices from industry experience (ISCWSA WISC eBook). This paper also illustrates how the combination of advanced survey management, gyro surveying, and magnetic ranging can be used following the best industry practices for fast and cost-efficient non-routine plug and abandonment. Case studies of several abandonment projects are presented showing the various technical challenges which are common on idle and legacy wells. The projects include wells that are currently under the ownership of an operator and orphaned wells that have been insufficiently abandoned and left idle over many decades. The case studies outline how the application of relief well methodologies to the execution of complex sub surface interventions led to the successful outcomes of meeting environmental and government regulations for wellbore abandonment. This includes performing multiple zonal isolations between reservoirs, water zones and preventing oil and gas seepage to the surface. The projects and their outcomes prove economically viable strategies for tackling the growing issue of idle and orphaned wells globally in a fiscally responsible manner. Combining industry best practice methods for relief well drilling, along with the technological advancements in magnetic ranging systems is a solution for one of the largest dilemmas facing the oil and gas industry in relation to idle and orphaned wellbores. These applications allow previously considered impossible abandonments to be completed with a high probability of long-term success in permanent abandonment.

scholarly journals Strategic Thinking: Intelligent Opportunism and Emergent Strategy — The Case of Strategic Engineering Services

2016 ◽  
Vol 17 (1) ◽  
pp. 65-70 ◽  
Author(s):  
Steven Pattinson
Keyword(s):  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Strategic Thinking ◽  
Gas Industry ◽  
Covering System ◽  
Emergent Strategy ◽  
Engineering Company ◽  
Engineering Services ◽  
The Relationship

This case study focuses on strategic thinking and opportunistic approaches to business growth and diversification. It begins by examining the recent purchase of ‘Quickcover’, a remote-controlled sports pitch covering system, by engineering company Strategic Engineering Services and the company's current dilemma – whether to continue to develop this type of product, or sell it and concentrate on its existing engineering services business. In recent years, Strategic Engineering Services has moved away from traditional heavy engineering and diversified into related areas such as engineering services, oil and gas industry recruitment, plant and equipment hire, instrument calibration and project management. The case considers the relationship between strategic thinking and entrepreneurial approaches to opportunity recognition, exploring the concept of intelligent opportunism as an approach that enables entrepreneurs to develop emergent strategies and take advantage of new opportunities. It explores these concepts in the context of the current dilemma of Strategic Engineering Services.

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