A hybrid approach for an oil and gas company as a representative of a high reliability organization

2021 ◽  
pp. 1-27
Author(s):  
Gustavo Rivera ◽  
Akilu Yunusa-Kaltungo ◽  
Ashraf Labib
Keyword(s):  
Oil And Gas ◽  
High Reliability ◽  
Hybrid Approach ◽  
High Reliability Organization

scholarly journals Veränderte Kompetenzanforderungen an Mitarbeitende infolge zunehmender Automatisierung – Eine Arbeitsfeldbetrachtung

2021 ◽  
Author(s):  
Michèle Rieth ◽  
Vera Hagemann
Keyword(s):  
High Reliability ◽  
High Reliability Organizations ◽  
High Reliability Organization

ZusammenfassungBasierend auf einer Arbeitsfeldbetrachtung im Bereich der Flugsicherung in Österreich und der Schweiz liefert dieser Artikel der Zeitschrift Gruppe. Interaktion. Organisation. (GIO) einen Überblick über automatisierungsbedingte Veränderungen und die daraus resultierenden neuen Kompetenzanforderungen an die Beschäftigten im Hochverantwortungsbereich. Bestehende Tätigkeitsstrukturen und Arbeitsrollen verändern sich infolge zunehmender Automatisierung grundlegend, sodass Organisationen neuen Herausforderungen gegenüberstehen und sich neue Kompetenzanforderungen an Mitarbeitende ergeben. Auf Grundlage von 9 problemzentrierten Interviews mit Fluglotsen sowie 4 problemzentrierten Interviews mit Piloten werden die Veränderungen infolge zunehmender Automatisierung und die daraus resultierenden neuen Kompetenzanforderungen an die Beschäftigten in einer High Reliability Organization dargestellt. Dieser Organisationskontext blieb bisher in der wissenschaftlichen Debatte um neue Kompetenzen infolge von Automatisierung weitestgehend unberücksichtigt. Die Ergebnisse deuten darauf hin, dass der Mensch in High Reliability Organizations durch Technik zwar entlastet und unterstützt werden kann, aber nicht zu ersetzen ist. Die Rolle des Menschen wird im Sinne eines Systemüberwachenden passiver, wodurch die Gefahr eines Fähigkeitsverlustes resultiert und der eigene Einfluss der Beschäftigten abnimmt. Ferner scheinen die Anforderungen, denen sie sich infolge zunehmender Automatisierung gegenüberstehen sehen, zuzunehmen, was in einem Spannungsfeld zu ihrer passiven Rolle zu stehen scheint. Die Erkenntnisse werden diskutiert und praktische Implikationen für das Kompetenzmanagement und die Arbeitsgestaltung zur Minimierung der identifizierten restriktiven Arbeitsbedingungen abgeleitet.

scholarly journals A Literature Review of Hybrid System Dynamics and Agent-Based Modeling in a Produced Water Management Context

Modelling ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 224-239
Author(s):  
Saeed P. Langarudi ◽  
Robert P. Sabie ◽  
Babak Bahaddin ◽  
Alexander G. Fernald
Keyword(s):  
Water Management ◽  
New Mexico ◽  
Literature Review ◽  
System Dynamics ◽  
Oil And Gas ◽  
Produced Water ◽  
Hybrid Approach ◽  
Oil And Gas Industry ◽  
Hybrid Modeling ◽  
Agent Based

This paper explores the possibility and plausibility of developing a hybrid simulation method combining agent-based (AB) and system dynamics (SD) modeling to address the case study of produced water management (PWM). In southeastern New Mexico, the oil and gas industry generates large volumes of produced water, while at the same time, freshwater resources are scarce. Single-method models are unable to capture the dynamic impacts of PWM on the water budget at both the local and regional levels, hence the need for a more complex hybrid approach. We used the literature, information characterizing produced water in New Mexico, and our preliminary interviews with subject matter experts to develop this framework. We then conducted a systematic literature review to summarize state-of-the-art of hybrid modeling methodologies and techniques. Our research revealed that there is a small but growing volume of hybrid modeling research that could provide some foundational support for modelers interested in hybrid modeling approaches for complex natural resource management issues. We categorized these efforts into four classes based on their approaches to hybrid modeling. It appears that, among these classes, PWM requires the most sophisticated approach, indicating that PWM modelers will need to face serious challenges and break new ground in this realm.

Agile framework for capital projects

2021 ◽  
Vol 61 (2) ◽  
pp. 422
Author(s):  
Polly Mahapatra ◽  
Paris Shahriari
Keyword(s):  
Oil And Gas ◽  
Hybrid Approach ◽  
Oil And Gas Industry ◽  
Quick Response ◽  
Capital Projects ◽  
Gas Industry ◽  
Response To Change ◽  
The Cost ◽  
Early Phases ◽  
The Ideal

Under the increased pressure of rapidly changing market conditions and disrupting technologies, continuous improvements in efficiency become indispensable for all oil and gas operators. Traditional project management principles in the oil and gas industry employ rigid methods of planning and execution that can sometimes hinder adaptability and a quick response to change. Considering the potential that Agile principles can offer as a solution, the challenge, therefore, is to identify the ideal, hybrid, approach that leverages Agile while incorporating the traditional linear workflow necessitated by the oil and gas industry. This paper seeks to assess pre-existing literature in the application of the Agile principles in the oil and gas industry with a focus on Major Capital Projects (MCPs), backed by the successes experienced as a result of specific pilot projects completed at Chevron’s Australian Business Unit. In particular, this paper will focus on how agility has resulted in improvements to the cost, schedule, teaming and cohesion of MCPs in the early phases as well as key learnings form the pilot agility projects.

SafeOCS Industry Safety Data Program: An Industrywide Safety Data Management Framework

2020 ◽  
Vol 72 (12) ◽  
pp. 34-37
Author(s):  
Demetra V. Collia ◽  
Roland L. Moreau
Keyword(s):  
Oil And Gas ◽  
High Reliability ◽  
Safety Data ◽  
Oil And Gas Industry ◽  
Near Miss ◽  
Outer Continental Shelf ◽  
Gas Industry ◽  
The Us ◽  
Recommended Practices ◽  
Industry Associations

Introduction In the aftermath of the Deepwater Horizon oil spill, the oil and gas industry, regulators, and other stakeholders recognized the need for increased collaboration and data sharing to augment their ability to better identify safety risks and address them before an accident occurs. The SafeOCS program is one such collaboration between industry and government. It is a voluntary confidential reporting program that collects and analyzes data to advance safety in oil and gas operations on the Outer Continental Shelf (OCS). The US Bureau of Safety and Environmental Enforcement (BSEE) established the program with input from industry and then entered into an agreement with the US Bureau of Transportation Statistics (BTS) to develop, implement, and operate the program. As a principal statistical agency, BTS has considerable data-collection-and-analysis expertise with near-miss reporting systems for other industries and the statutory authority to protect the confidentiality of the reported information and the reporter’s identify. Source data submitted to BTS are not subject to subpoena, legal discovery, or Freedom of Information Act (FOIA) requests. Solving for the Gap Across industries, companies have long realized the benefits of collecting and analyzing data around safety and environmental events to identify risks and take actions to prevent reoccurrence. These activities are aided by industry associations that collect and share event information and develop recommended practices to improve performance. In high-reliability industries such as aviation and nuclear, it is common practice to report and share events among companies and for the regulators to identify hidden trends and create or update existing recommended practices, regulations, or other controls. The challenge for the offshore oil and gas industry is that industry associations and the regulator are typically limited to collecting data on agency-reportable incidents. With this limitation, other high-learning-value events or observed conditions could go unnoticed as a trend until a major event occurs. This lack of timely data represented an opportunity for the industry and the offshore regulator (BSEE) to collaborate on a means of gathering safety-event data that would allow for analysis and identification of trends, thereby enabling appropriate interventions to prevent major incidents and foster continuous improvement. The SafeOCS Industry Safety Data (ISD) program provides an effective process for capturing these trends by looking across a wider spectrum of events, including those with no consequences.

Integrity Assurance of an Oil Transportation Pipeline in a Transformed Design Environment

2015 ◽  
Author(s):  
Amitabh Kumar ◽  
Brian McShane ◽  
Mark McQueen
Keyword(s):  
Field Data ◽  
Oil And Gas ◽  
High Reliability ◽  
Complex Loading ◽  
Calibration Method ◽  
Real Field ◽  
Design Environment ◽  
Data Feedback ◽  
Integrity Management

A large Oil and Gas pipeline gathering system is commonly used to transport processed oil and gas from an offshore platform to an onshore receiving facility. High reliability and integrity for continuous operation of these systems is crucial to ensure constant supply of hydrocarbon to the onshore processing facility and eventually to market. When such a system is exposed to a series of complex environmental loadings, it is often difficult to predict the response path, in-situ condition and therefore the system’s ability to withstand subsequent future loading scenarios. In order to continue to operate the pipeline after a significant environmental event, an overall approach needs to be developed to — (a) Understand the system loading and the associated integrity, (b) Develop a series of criteria staging the sequence of actions following an event that will verify the pipeline integrity and (c) Ensure that the integrity management solution is simple and easy to understand so that it can be implemented consistently. For a complex loading scenario, one of the main challenges is the ability to predict the controlling parameter(s) that drives the global integrity of these systems. In such scenarios, the presence of numerous parameters makes the technical modeling and prediction tasks arduous. To address such scenarios, first and foremost, it is crucial to understand the baseline environment data and other associated critical design input elements. If the “design environmental baseline” has transformed (due to large events e.g. storms etc.) from its original condition; it modifies the dynamics of the system. To address this problem, a thorough modeling and assessment of the in-situ condition is essential. Further, a robust calibration method is required to predict the future response path and therefore expected pipeline condition. The study further compares the planned integrity management solutions to the field data to validate the efficiency of the predicted scenarios. By the inclusion of real field-data feedback to the modeling method, balanced integrity solutions can be achieved and the ability to quantify the risks is made more practical and actionable.

Technology Focus: Offshore Drilling and Completion (October 2021)

2021 ◽  
Vol 73 (10) ◽  
pp. 45-45
Author(s):  
Martin Rylance
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Oil And Gas ◽  
Hybrid Approach ◽  
Data Communication ◽  
Oil And Gas Industry ◽  
Oil Field ◽  
Real Time Processing ◽  
National University ◽  
Seoul National University

Communication and prediction are symmetrical. Communication, in effect, is prediction about what has happened. And prediction is communication about what is going to happen. Few industries contain as many phases, steps, and levels of interface between the start and end product as the oil and gas industry—field, office, offshore, plant, subsea, downhole, not to mention the disciplinary, functional, managerial, logistics handovers, and boundaries that exist. It therefore is hardly surprising that communication, in all its varied forms, is at the very heart of our business. The papers selected this month demonstrate how improved communication can deliver the prediction required for a variety of reasons, including safety, efficiency, and informational purposes. The application of new and exciting ways of working, partially accelerated by recent events, is leading to breakthrough improvements on all levels. Real-time processing, improved visualization, and predictive and machine-learning methods, as well as improvements in all forms of data communication, are all contributing to incremental enhancements across the board. This month, I encourage the reader to review the selected articles and determine where and how the communication and prediction are occurring and what they are delivering. Then perhaps consider performing an exercise wherein your own day-to-day roles—your own areas of communication, interfacing, and cooperation—are reviewed to see what enhancements you can make as an individual. You may be pleasantly surprised that some simple tweaks to your communication style, frequency, and format can deliver quick wins. In an era of remote working for many individuals, it is an exercise that has some value. Recommended additional reading at OnePetro: www.onepetro.org. OTC 30184 - Augmented Machine-Learning Approach of Rate-of-Penetration Prediction for North Sea Oil Field by Youngjun Hong, Seoul National University, et al. OTC 31278 - A Digital Twin for Real-Time Drilling Hydraulics Simulation Using a Hybrid Approach of Physics and Machine Learning by Prasanna Amur Varadarajan, Schlumberger, et al. OTC 31092 - Integrated Underreamer Technology With Real-Time Communication Helped Eliminate Rathole in Exploratory Operation Offshore Nigeria by Raphael Chidiogo Ozioko, Baker Hughes, et al.

Sign in / Sign up

Export Citation Format

Share Document