Tuesday, July 09
Safety Announcement, Introduction and Keynote Speech, Q&A.
Health, Safety, Security, and Environment (HSSE) is fundamental to our industry’s reputation and for the license to operate. This applies everywhere, on-site or in the office, in our professional or personal environment!
Application of digital technologies is increasingly adding efficiency in analysing, monitoring, and improving all aspects of HSSE. For example, predictive technical monitoring (PTM) can ‘see’ catastrophic equipment failures before they happen, online analysis of safety events such as Learning from Incidents (LFIs) can then be disseminated faster, and IoT, using many sensors, respond faster to the right-side of the bow tie in case of an incident. Numerous innovative solutions are being deployed across the industry with exponential benefits.
Data security is also a key concern for every entity in the world—public, private, and personal. Several preventive measures are adopted for data protection. Various technologies help use, store, and transfer data in a secure environment.
This session aims to enlighten where we see industry disruptions, as well as, ongoing evolutions in the dynamically changing ecosystem of HSSE.
Subsurface has always analysed large volumes and complex data, and the recent digital interventions promise creating huge value for the industry. With improved algorithms and high performance infrastructures at low costs, digital technologies are being applied for faster data access, greater insight, optimising subsurface workflows, and enabling better decision-making.
This session will focus on various initiatives, case studies, and the possibilities of digital interventions that are emerging in subsurface workflows. Of particular importance will be the application of machine learning, artificial intelligence, and cloud computing in increasing the efficiency of subsurface geoscience, reservoir engineering, and production operation workflows. Speakers are expected to elicit how these digital technologies will be supporting or replacing existing workflows and generating values for their organisations. Speakers will also reflect on what the word "success" means in these contexts and the best possible ways to measure.
Wednesday, July 10
The construction and maintenance of a wellbore has over the years undergone tremendous technological innovations. Recently, from mathematical modelling to advanced simulations, the understanding of actual well conditions has only grown in precision. Wholly integrated digital approaches to business processes through the means of software has ensured elimination of subjectivity related to human interventions. This is reflected in operations where the possibility of overlooking minute details by the human eye has been reduced. Digitalisation and automation of processes ensure that all parameters affecting well performance in terms of productivity are monitored and maintained consistently. The advent of machine learning and artificial intelligence have further given us the opportunity to comprehend dependencies of various parameters on each other through data analytics, which can serve as a building block for complete automation of well activities in the future and increase visibility inside the well.
The session will discuss the current and upcoming digital processes in place to reduce cost and time in drilling, completions, interventions, thereby improving the integrity of the well.
Productivity in engineering and construction in the oil and gas Industry has stagnated for decades, and now significantly lag behind other industries such as aerospace and automotive. The average capital project in the O&G sector is around 20 months behind schedule and about 80% over budget. While project complexity and scale continue to be contributing factors, resistance to adoption of digital solutions and common data platforms by owners/operators and EPC’s is largely to blame.
This session addresses some of the ways the industry is responding to this challenge and how digitalisation and data-centric ways of working are being used to deliver more capital efficient projects. Infrastructure and manufacturing industries have significantly benefitted from large-scale adoption of advanced analytics, design automation, robotics, Building Information Modelling (BIM) and data standards.
The oil and gas sector is a highly asset-intensive industry. New wells are drilled regularly in remote and hostile locations and getting help and expertise is generally a problem. This results significant downtime in production and can lead to serious issues related to environment and safety.
Thus asset management offers a powerful platform to maximise reliability, availability, and safety of assets in the oil and gas industry. Asset management encompasses the capabilities of data capture, integration, visualisation, and analytics tied together for the explicit purpose of improving the operational performance of physical assets. It includes the concepts of condition monitoring, predictive forecasting, and reliability-centered maintenance (RCM), risk-based inspection (RBI), quantitative risk assessment (QRA), and safety integrity level (SIL).
Asset management issues are better addressed using digital twins. The digital twin is a digital, virtual representation of an asset, maintained throughout the lifecycle and easily accessible at any time It consists of two main components: a process representation and a plant representation.
The process representation is a digital replica of the process and automation system that enables testing of the process and control infrastructure, safety logic, and operating procedures before start-up. The plant representation is a smart 3D viewer for the entire topsides that provides access to equipment, maintenance, and real-time operations data for construction, commissioning, and maintenance planning complemented by AR and VR technologies.
This session will focus on various digital technologies and solutions used to manage oil and gas companies assets that drive efficiency and reduce costs while effectively managing operational risk and safety.
Production optimisation refers to the various activities of measuring, analysing, modelling, prioritising, and implementing actions to enhance productivity of a field: reservoir/well/surface. It is a fundamental practice to ensure recovery of developed reserves with maximum returns. The advancements in sensor technologies and widening connectivity of devices (IoT) are creating a vast pool of 24x7 wells, equipment, and facilities with real-time data enabling field staff to respond faster to events and trends. The new advanced data analytics (ML and AI) when clubbed with engineering tools, open ways to identify optimisation opportunities, foresee events, and act in a timely fashion. This reduces downtime and deferred production, lowers cost, increases integrity and improves HSE.
The focus of the session is to show how automation, advanced data analysis, and connected devices can be used to accelerate and improve decision-making in production and operations, leading to efficiency gains.
Thursday, July 11
Oil and gas data management has been a mainstream activity for a decade now. Operators and service providers have been struggling to get the required and accurate information from their data, and still face challenges with the interpretation and visualisation of the collected data. However, implementing successful data and information management strategies remains the key to driving an organisation’s operational efficiency. Data generation has increased multi-fold in the last decade due to the innovations in real-time and GIS technologies. The new storage solutions have solved the constraints of storing petabytes of data. Digital transformation can help oil and gas companies to make huge strides to improve the way they manage their data and information. Enterprise data management, well logging data analysis, data monitoring of surveillance systems, and many more functions can be effectively managed by a central data management centre ensuring improved data governance, quality, and security. Growing volume, diversity, and complexity of data constraints oil and gas specialists to perform non-value added data management operational activities.
This session will focus on innovation in data management activities, technology solutions, frameworks, and case studies for effective oil and gas data management. Along with demonstrating business value through technology innovation leveraging with next generation technologies like big data, cloud enablement, data lake, etc.
Digitalisation is by far the hottest topic of 2018. Is it a hype? Have we quietly been moving for years from digitisation to digitalisation? AI existed 4 decades ago, so what has changed since then, that everyone has a story about AI, AA and ML?
Companies are at crossroads between causing disruption to the organisation, or taking a more-paced and gradual approach to changing the way work is done. The variables under consideration include the ability to upscale staff’s digital capabilities, the rapid changing digital landscape, and shifting company culture to the new digital world, along with proving that the promised efficiency gains exist.
This panel session’s objective is to debate whether it is best to treat digitalisation as disruptive or is it better to move in a more evolutionary way. We assume that the camps will be divided, but find out by attending this panel session!