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Abstract As host authority for all hydrocarbon resources in Malaysia, Petroliam Nasional Berhad (PETRONAS) Malaysia Petroleum Management (MPM) has championed Asset Value Framing (AVF) since 2016 to facilitate identification of asset enhancing opportunities and to establish a roadmap for opportunity realization. This paper is the continuation of the previous paper (SPE-196486) which illustrated opportunity identification through AVF. In 2019, PETRONAS had embarked on benchmarking oil reservoirs for all Malaysian oil reservoirs which was used for the AVF process to improve economic recovery factor of an oil field and booking new contingent resources. This paper focuses on enhanced AVF approach to integrate subsurface, wells, surface and operations; coupled with recommended improvements to AVF process from lookback exercise, reservoir performance assessment, data analytic through reservoir benchmarking tool and assessment of analogue reservoirs. A case study will be shared from one of the largest oilfields in Sarawak wherein enhanced AVF approach was applied to unlock significant potential of which conventional techniques faced challenges in identifying opportunities. Field B consists of multi-layered depositional system with numerous fault-bounded accumulation areas. Benchmarking process was performed for each of reservoir units to estimate the potential recovery factor and degree of complexity. In reservoirs where current estimates of recovery factor were lower than the benchmark, these were screened to be considered for identification of new opportunities through AVF process. Additionally, benchmarking process was applied to evaluate optimal well spacing, need for secondary recovery and identification of potential challenges for future development planning. A paradigm shift was undertaken to AVF process itself whereby focused development plan was considered for the entire column of rock within every fault block - instead of chasing oil by reservoirs. This subsequently allowed an integrated approach to optimize well type and cost, infill and water injection well count, completion design and overall evacuation strategy. Application of reservoir benchmarking significantly improved the delivery of AVF process by identification of recovery gaps in the field and application of learnings from better performing reservoirs. This coupled with Enhanced AVF workflow approach of focused development plan has resulted a roadmap for Field B to achieve ultimate recovery factor of 40% through a number of potential development opportunities within the next few years. An enhanced AVF workflow coupled with benchmarking process has facilitated field potential evaluation within two months, leading to efficient decision making, resource accrual and value creation for all stakeholders. This workflow can be replicated to other fields, maximizing economic reserves, increasing asset value, and defining the development roadmap.

Abstract The execution phase of the wells technical assurance process is a critical procedure where the drilling operation commences and the well planning program is implemented. During drilling operations, the real-time drilling data are streamed to a real-time centre where it is constantly monitored by a dedicated team of monitoring specialists. If any potential issues or possible opportunities arise, the team will communicate with the operation team on rig for an intervention. This workflow is further enhanced by digital initiatives via big data analytics implementation in PETRONAS. The Digital Standing Instruction to Driller (Digital SID) is a drilling operational procedures documentation tool meant to improve the current process by digitalizing information exchange between office and rig site. Boasting multi-operation usage, it is made fit to context and despite its automated generation, this tool allows flexibility for the operation team to customize the content and more importantly, monitor the execution in real-time. Another tool used in the real-time monitoring platform is the dynamic monitoring drilling system where it allows real-time drilling data to be more intuitive and gives the benefit of foresight. The dynamic nature of the system means that it will update existing roadmaps with extensive real-time data as they come in, hence improving its accuracy as we drill further. Furthermore, an automated drilling key performance indicator (KPI) and performance benchmarking system measures drilling performance to uncover areas of improvement. This will serve as the benchmark for further optimization. On top of that, an artificial intelligence (AI) driven Wells Augmented Stuck Pipe Indicator (WASP) is deployed in the real-time monitoring platform to improve the capability of monitoring specialists to identify stuck pipe symptoms way earlier before the occurrence of the incident. This proactive approach is an improvement to the current process workflow which is less timely and possibly missing the intervention opportunity. These four tools are integrated seamlessly with the real-time monitoring platform hence improving the project management efficiency during the execution phase. The tools are envisioned to offer an agile and efficient process workflow by integrating and tapering down multiple applications in different environments into a single web-based platform which enables better collaboration and faster decision making.

Abstract The recent global pandemic is an unprecedented event and took the world by storm. The Movement Control Order (MCO) issued by Malaysia's government to halt the spread of the deadly infection has changed the landscape of work via a flexible working arrangement. The Wells Real Time Centre (WRTC) is not an exception and is also subjected to the change. WRTC is an in-house proactive monitoring hub, built to handle massive real-time drilling data, to support and guide wells delivery effectiveness and excellence. The functionality of the WRTC system and applications are embedded in the wells delivery workflow. The centre houses drilling specialists who are responsible for observing the smooth sailing of well construction and are tasked to intervene when necessary to avoid any unintended incidents. WRTC is equipped with myriads of engineering applications and drilling software that are vital for the operations. Such applications include monitoring software, machine learning applications, engineering modules, real-time data acquisition, and database management. These applications are mostly cloud-based and Internet-facing, hence it is accessible and agile as an infrastructure that is ready to be deployed anytime anywhere when it is required. The strategy for WRTC mobility started as soon as the MCO was announced. This announcement mandated the WRTC to operate outside of the office and required the staff to work from home. The careful coordination and preparation to transform and adapt WRTC to a new norm was greatly assisted by the infrastructure readiness. All of these factors contributed greatly to a successful arrangement with zero to minimal downtime where a workstation was set up in each personnel's home, running at full capacity. This transformation was done within one day of the notice and completed within hours of activation. Despite the successful move, few rooms for improvements such as redundancy of VPN use to access applications and limited access to some proprietary software can be enhanced in the future. WRTC is ready to be mobile and agile to support the drilling operations remotely either in the office or from home. The quick turnaround is a major indicator that WRTC infrastructure and personnel are ready and capable for remote operations without interruption.

Abstract A large collection of data recorded during coiled tubing (CT) operations has been analyzed using proprietary pattern recognition algorithms to identify downhole events with a high degree of confidence. These events include the drilling of plugs and stuck pipe incidents. Key performance indicator (KPI) metrics derived from this analysis provide insight into industry trends over time and by region, and can provide useful performance benchmarks for service providers and operator companies. Depth, weight and pressure data from multiple sources has been streamed and stored on a shared platform over a five year period, creating a record of over 39,000 data files. This data was processed to generate KPI-type statistics for over 500,000 detected plugs and 760 possible stuck pipe scenarios, based on analysis of depth and weight signatures. Using surface measurements to quantify downhole events has some limitations, but the method has proven sufficiently robust to allow useful trends to be observed and evaluated. While the analysis is confidential to the parties involved, a contributing company can compare their ‘performance’ statistics (as evaluated by the third party algorithms) against averages representative of the industry at large, arranged by year and geographic region, to identify areas of relative strength or weakness. An operator company can likewise compare metrics for different service providers (derived solely from jobs performed for their company) for those which elect to share data in this fashion. This paper presents statistics for plug drilling operations and stuck pipe incidents in North America between 2016-2020, a period of significant change in the CT industry. Examples show how average plug drilling times have generally decreased, with less frequent use of short trips and fewer pipe cycles. The data shows that, for some companies, faster operations have come at the expense of more frequent or severe stuck pipe incidents, whereas other companies have experienced fewer such problems. This comparative analysis illustrates how downhole outcomes can be deduced from surface measurements, and resulting performance metrics can vary widely between companies, fields and geographic regions.

This different way of looking at cultural maturity through the lens of what should be expected of supervisors and employees may help organizations develop plans and strategies to achieve an incident- and injury-free workplace. Over the years, various authors have put forth cultural maturity models for organizations to describe the pathway toward high levels of safety performance. While these models are readily accepted and viewed as benchmarks for assessments of the state of safety culture, what lies beneath the premise and what may we be searching for? We now know, through both the study of employee attitudes and brain science, that individuals respond well to having a say in their work output and environment. If we apply the lens of employee engagement to a typical culture maturity model, it will look different.

This paper presents numerical modelling results of the interaction between a group of steep waves and a fixed vertical cylinder performed with a one-way coupled hybrid model. A set of experimental data is used to benchmark the accuracy of the modelling results. The wavemaker signal generated in the physical experiments is used to reproduce the incident wave conditions without a priori knowledge of the rest of the dataset. A Lagrangian numerical wave flume propagates the wave group, producing the nonlinear free surface elevation and wave kinematics with high accuracy in the vicinity of the cylindrical structure. This data is used as the input to the olaFlow CFD model, which calculates the wave-structure interactions. One-way coupling approaches based on boundary conditions and relaxation zones are tested and compared in terms of the recorded free surface elevation and pressures at the structure. The results present an adequate degree of accordance, and turbulence effects are found to be negligible in the simulations.

A selected reference point for comparing performance.

Implementing a physics-based digital twin of a drilling system can enable the drilling team to leverage data at each stage of the engineering process to deliver more-consistent, repeatable drilling performance and improved borehole quality, which in turn enables drilling farther and faster while increasing downhole tool life. The complete paper discusses a new performance-evaluation methodology that combines bottomhole assembly (BHA) modeling with field data. BHA modeling simulates the drilling process accurately to establish key performance indicators (KPIs) to help optimize BHA designs to deliver improvements in drilling performance and wellbore quality. The model also can estimate quantities such as microtortuosity that are not directly measured by standard equipment. Determining the cumulative effect of BHA behavior during drilling on the quality of the wellbore and the subsequent impact on performance and life of the BHA is an important goal for improving overall drilling and well-delivery efficiencies.

As the Permian Basin has boomed again, recent conversations focused on how pipeline takeaway capacity limits the ability of operators to develop the basin to its full potential. In addition to solving the takeaway problem, water management is another bugbear waiting to be addressed.