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Invisible Lost Time (ILT) related to routine rig drilling operations is the difference between actual operational duration and a best practice target. It is invisible as it does not appear on any conventional morning reports. The measurement of Invisible Lost Time starts by analyzing each individual key performance indicator (KPI) that can be produced by a particular crew (drilling crew, casing crew, etc.) or by a machine automated operation or a combination of both. The measurement of Invisible Lost Time was first developed and used by Statoil and TDE.
Rashid, Faisal (Adnoc Offshore) | Al Saadi, Hamdan Mohamed (Adnoc Offshore) | Duivala, Shahid Yakubbhai (Adnoc Offshore) | Butt, Steve (Memorial University, ST. John's) | Al Mansoori, Sultan (Adnoc Offshore) | Mughal, Muhammad Idrees (Adnoc Offshore)
Abstract With the launch of a mega drilling project in the Middle East, the drilling data during the execution stage was collected in two formats; Low-Frequency Data and High-Frequency Data. This paper explains the effective utilization of data in the performance enhancement scheme. The paper also demonstrates the combination of Low-frequency and High-frequency data can reveal the many secrets of the drilling operations and can open the many sides of drilling operations for improvements. Low-Frequency data was entered manually at the rig-site using an improved coding system to identify the activities start and end times. High-Frequency data was collected through real-time transmission from the different data streaming services at the rig-site. Both data forms were collected simultaneously using stringent rules and close follow-ups to make sure that data collection was free of any reporting mistakes and gaps. Later, the collected data was extracted for different types of analyses and interpretations. Low-frequency data was studied in a novel way to get the best analytical and critical outcome to make sure that the right areas for improvements were identified and actions were implemented for enhanced performance. Improved operations coding system helped the team to categorize the operations and failures in an effective way to set new standards in data analysis. More than 100 different types of analyses using the best data analysis technique, such as trailing average, normalization, trends, etc., were conducted based on the information collected during the execution phase, and many new KPIs were established with challenging milestones to be achieved in the prescribed period. High-Frequency data was split into different sets of KPIs to identify the multiple Invisible Lost Time (ILT) areas to boost the operational efficiency. Various performance enhancement schemes were developed based on High-frequency data. As a result, these schemes were proven to enhance the performance of the mega drilling project. This paper discusses the novel methods of drilling data analysis based on low and high-frequency data and shows the effectiveness of the data presented in a standardized format over a period. It deliberates how the teams were challenged to enhance the performance. Such detailed data analysis will bring valuable information for the industry to utilize the conventional database in modernized ways to get the best outcomes from the data analysis results.
Bimastianto, Paulinus (ADNOC Offshore) | AlSaadi, Hamdan (ADNOC Offshore) | Khambete, Shreepad (ADNOC Offshore) | Cotten, Michael (ADNOC Offshore) | Couzigou, Erwan (ADNOC Offshore) | Al-Marzouqi, Adel (ADNOC Offshore) | Chevallier, Bertrand (Schlumberger) | Qadir, Ahsan (Schlumberger) | Pausin, Wiliem (Schlumberger)
Abstract Majority of organizations endeavor to reduce operating costs and improve operational efficiencies. The concept of Mechanical Specific Energy (MSE) has long been implemented in the industry to improve drilling performance. The Drilling Real time Operations Center (RTOC) has taken the concept of MSE beyond its traditional approach by developing a Drilling Performance Measure combining data science and statistics to benchmark drilling efficiency. To extract maximum value from the available database, a workflow was developed to construct a Drilling Efficiency Benchmarking Tool. The different steps will be described for performing the data ingestion, cleansing, selection (offset well selection), methodology of computing the statistical model for MSE baseline per Formations and visualization of the output (charts and logs), to compare the actual MSE with baseline and thereby measuring the performance efficiency. The offset wells analysis results show that the workflow can construct an MSE baseline using high frequency data in a meaningful way, which is then set as a target envelope and projected through the real-time platform for monitoring and intervention purposes. This implementation of real-time MSE benchmarking helps identify the area of potential improvement, optimize drilling parameters to ultimately improve ROP and minimize lost time. As an analytical tool, it highlights achievable performance for each field and provide insights to consider new Best Practices.
Abstract Since the implementation of the Drilling Performance Department in late 2017, ADNOC Offshore has been able to develop a company performance-oriented culture among the drilling teams. This performance culture is reflected in 25% ILT reduction in 2018 and 12% in 2019. Furthermore, 37 NPT RCA cases were investigated and concluded in 2019, which resulted in 57 actions for tracking and closure. With 5 (five) concessions, 9 (nine) different shareholders, and 39 (thirty-nine) rigs, drilling performance management is challenging. ADNOC Offshore created a centralized Drilling Performance Team to capitalize on this diversity as an opportunity to improve the traditional drilling performance role. This paper describes the team's approach on Drilling Performance and the consecutive result. The team enhances the typical drilling performance role of Key Performance Indicator (KPI) management and reporting by adopting the Performance Opportunity Time (POT) and Root Cause Analysis (RCA) Process. At the same time, the Drilling Performance Team facilitates the flow of information between teams to ensure effective knowledge transfer within such a large organization. The POT concept tackles the well duration reduction through the reduction of Invisible Lost Time (ILT) and Non-Productive Time (NPT). To reduce the ILT, the team took advantage of the extensive technical background in the various drilling teams. Performance improvement initiatives were proposed by taking references from different teams within ADNOC Offshore and evaluating the application in other concession. Other approach is to compare with out-of-company references. For NPT reduction, the innovative approach was to use the HSE Root Cause Analysis (RCA) concept. This RCA process led by the Drilling Performance Team was implemented to standardize the approach and have a systematic investigation analysis. This process resulted in identifying root causes and effective corrective action plans. As per HSE, addressing the root causes of incidents would result in the most significant impact in NPT. This approach also allows an independent and more detailed look on the subjects, where commonly these tasks are done in a limited manner by drilling teams alone with their ongoing operational workload. Finally, results are communicated to the drilling organization through lessons learned portal and technical bulletins.
Johnson, Caroline (Heriot-Watt University–Edinburgh (*Corresponding author) | Sefat, Morteza Haghighat (email: email@example.com)) | Elsheikh, Ahmed H. (Heriot-Watt University–Edinburgh) | Davies, David (Heriot-Watt University–Edinburgh)
Summary In the next decades, tens of thousands of well plugging and abandonment (P&A) operations are expected to be executed worldwide. Decommissioning activities in the North Sea alone are forecasted to require 2,624 wells to be plugged and abandoned during the 10-year period starting from 2019 (Oil&Gas_UK 2019). This increase in decommissioning activity level and the associated high costs of permanent P&A operations require new, fit-for-purpose, P&A design tools and operational technologies to ensure safe and cost-effective decommissioning of hydrocarbon production wells. This paper introduces a novel modeling framework to support risk-based evaluation of well P&A designs using a fluid-flow simulation methodology combined with probabilistic estimation techniques. The developed well-centric modeling framework covers the full range of North Sea P&A well designs and allows for quantification of the long-term (thousands of years) evolution of hydrocarbon movement in the plugged and abandoned well. The framework is complemented by an in-house visualization tool for identification of the dominant hydrocarbon flow-paths. Monte Carlo methods are used to account for uncertainties in the modeling inputs, allowing for robust comparison of various P&A design options, which can be ranked on the basis of hydrocarbon leakage risks. The proposed framework is able to model transient conditions within the well P&A system, allowing for the development of new key performance indicators (e.g., time until hydrocarbons reach surface and changes in hydrocarbon saturation within the P&A well). Such key performance indicators are not commonly used, because most published work in this area relies on steady-state P&A models. The developed framework was used in the assessment of several P&A design cases. The results obtained, which are presented in this paper, demonstrate its value for supporting risk-baseddecision-making by allowing for quantitative comparison of the expected performance of multiple P&A design options for given well/reservoir conditions. The framework can be used for identifying cost-effective, fit-for-purpose P&A designs, for example by optimizing the number, location, and length of wellbore barriers and evaluating the effectiveness of annular cement sheath remedial operations. Additionally, this framework can be used as a sensitivity analysis tool to identify the critical parameters that have the greatest impact on the modeled leakage risks, to guide data acquisition plans and model refinement steps aimed at reducing the uncertainties in key model parameters.
The current era of unconventionals reflects the industry's opportunistic development mode, with the increasing focus on cash flow overgrowth. The journey started more than 15 years ago with technology that enabled the production and development of reservoirs once thought unrecoverable. Reserve was king and capital was easy to access. It has been a steep learning curve for the industry while growing production from 5 MM barrels per day to about 13 MM barrels per day and drilling about 200,000 horizontal wells across several basins. As technology and knowledge improved over the years, the definition of risk and opportunity in each unconventional play has undergone various phases.
Hamid, Mohd Ridzuan (PETRONAS Carigali Sdn Bhd) | Meor Hashim, Meor M. (PETRONAS Carigali Sdn Bhd) | Norhashimi, Lokman (PETRONAS Carigali Sdn Bhd) | Arriffin, Muhammad Faris (PETRONAS Carigali Sdn Bhd) | Mohamad, Azlan (PETRONAS Carigali Sdn Bhd)
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.
Ho, Yeek Huey (Petroliam Nasional Berhad) | Guillory, Ryan (Petroliam Nasional Berhad) | Kumar Sinha, Ankaj (Petroliam Nasional Berhad) | Din, Rusli (Petroliam Nasional Berhad) | Ranjan, Rakesh (Petroliam Nasional Berhad) | Masoudi, Rahim (Petroliam Nasional Berhad)
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.
Rosli, Azlesham (PETRONAS Carigali Sdn Bhd) | Mak, Whye Jin (PETRONAS Carigali Sdn Bhd) | Richard, Bobbywadi (PETRONAS Carigali Sdn Bhd) | Meor Hashim, Meor M (PETRONAS Carigali Sdn Bhd) | Arriffin, M Faris (PETRONAS Carigali Sdn Bhd) | Mohamad, Azlan (PETRONAS Carigali Sdn Bhd)
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.