UAE's First End to End Standardized Workflow-Based Digital Transformation in a Giant Gas Producing Asset - Lessons Learned and Way Forward

Day 3 Wed, November 02, 2022

et al. 2022

With a vast reservoir with a complex and dynamic system production system containing more than 300 wells, both producers and injectors, keeping track of the field operational activity like Reservoir Monitoring Plan (RMP) jobs can lead to sub-utilization, confusion, lack of efficiency, and loss of time. This paper describes an integrated and collaborated method that supports monitoring and execution of field activity tasks utilizing the integrated production optimization platform and the business intelligence tools. Reservoir monitoring planning (RMP) is one of the critical workflows used to ensure the smooth execution of tasks at the required time. This enables the user to plan future tasks based on the reservoir behavior and have a quick comparison between actual and planned tasks. The process starts with inputting the planned tasks into the integrated system, categorizing the tasks based on types, and assigning the executors. The system sends reminders/notifications of the planned task approaching the task due date to all the stakeholders. It also provides an automated direct summary/bird's eye view utilizing the business intelligence tool. Using an integrated asset operation model (IAOM) solution in a digital platform, this planning and monitoring workflow has enabled the users to establish a standardized and unified central repository for the tasks to ensure the single source of truth. With the help of this advanced workflow, inter-departmental communication gaps have been reduced tremendously, thus enabling better execution, analysis, gaps, or bottleneck identification. The automated summary dashboard contains the comparison of the actual status of tasks versus planned tasks. This helps in optimal facility utilization based on dynamic RMP monitoring. Additionally, the integrated solution for planner, performer & approver enabled the users to prioritize the activity based on bottlenecks faced during the past months and reduce the times used to update the monitoring Excel sheets. This outlining process provides a standardized approach across the assets, leading to improved tracking efficiency, minimizing the time spent on manual monitoring, planning, and receiving automatic reminders to avoid delay in the planned tasks, which assisted the users in focusing on production optimization and solving different bottlenecks. This reservoir monitoring and planning approach aligns with the overall corporate strategy of using an integrated asset operation Model (IAOM) for providing end users with tremendous opportunities related to system optimization. This also supports the users’ drive to switch the approach from individual people oriented to standardized process oriented. This approach supports standardization of the work process across the organization and a minimum of $ 700K value proposition from manpower time saving over five years.

Optimization of Reservoir Monitoring Planning, Reporting, and Shortfall Identifications Using a Centralized Automated Integrated Asset Operation Model System

Day 3 Wed, November 02, 2022

et al. 2022

Business Production Target Achievement and an Automated Allowable Workflow Challenges and Opportunities Under the Integrated Asset Operation Model

Day 4 Thu, November 03, 2022

et al. 2022

This paper describes accurate, efficient, and time-saving methodology for achieving the Business target by determining well allowable using advanced, integrated, and automated work-process for a gas condensate field with more than 350 (producing and injecting) well strings from a multi-layered reservoir, having varied reservoir characteristics. This paper will also illustrate challenges and enhancement opportunities toward full smart field applications. Integrated asset operation modeling (IAOM) within a digital framework provides automation to the engineering and analytical approach of allowable rate calculations. The approach comprises 3 step calculation process to determine the Well targets/allowable. Firstly, using the shareholder/reservoir management guideline along with calibrated well models for calculating the well's technical rate. Secondly, calculation of the well and reservoir available/potential rate using the well technical rates, reservoir target, and an inbuilt analytical solver. Thirdly, determination of the well allowable rate by conjugation of various well production components, including wellbore dynamics (Inflow performance and Well performance) and surface constraints. In a digital platform, this automated "Well allowable" workflow has enabled engineers and operators to determine the true potential of wells and reservoirs, thus overcoming potential challenges of computational time saving and identification of cost improvement opportunities. The use of the automated workflow has reduced the time to compute well allowable rates by more than 90% for a gas condensate field with more than 350 (producing and injecting) strings. Implementing this workflow prevented engineers from performing a tedious manual calculation on a well-by-well basis, allowing engineers to focus on engineering and analytical problems. Additionally, this efficient engineering approach provided the user with key information associated with the well's performance under various guideline indexes such as well available/potential rates, well technical rate, reservoir available rate, and rate to maintain drawdown/ minimum Bottom-hole Pressure. This advanced workflow computes the rate that can be delivered from each well corresponding to each guideline and constraint, thereby providing key inputs to various business objective scenarios for production efficiency improvement. Post-implementation, some challenges turned into opportunities to ensure the full and smooth implementation of the generated production scenarios adhering to the gas demand fluctuation. The accuracy and robustness of advanced and automated workflow of setting well allowable /production scenarios empower users to establish well performance and deliverability with a solid engineering analysis base, thereby providing key opportunities for saving cost computational time and assuring short-term production mandate deliverables. This approach supports standardization of the work process across the organization and a minimum of $ 2.8M value proposition from manpower time saving over 5 years.

Integrated Model Framework in a Giant Gas Condensate Field for Well Performance Evaluation, Monitoring, Performance Tracking and Remedial Action

Day 3 Wed, November 02, 2022

et al. 2022

This paper demonstrates the use of an integrated production optimization platform to determine the well performance for gas condensate wells in a statistical approach to increase the data accuracy for reservoir studies, simulate the field limitations, and provide recommendations for production optimization in a multilayered large carbonate reservoir field. This case involves wells under recycle and natural decline with challenges in the evaluation of well performance where the bulk of the information is available in multiple data sources The first elemental block in establishing the well performance of a gas condensate well is to determine and simulate its fluid behavior. Based on the PVT reports and subsurface fluid studies, compositional PVT models are built and matched with experimental data analyzing representative phase envelop properties and relevant Equation of State (EOS). The next step incorporates the utilization of representative physics-based well models in an integrated system to determine the reservoir and well deliverability. Finally, by applying a detailed statistical approach to the production well test history, models are calibrated in order to predict the performance of the gas condensate wells. Tuning of compositional PVT models established the EOS to be incorporated in predicting the fluid behavior and integrating representative PVT models with well models to determine such behavior along the fluid path. Using the statistical approach, the poor well measurements were identified, facilitating the well-performance and deliverability calculation. In addition, the use of representative models helped in increasing the accuracy of identifying well performance. During this study, two different methodologies were identified based on the reservoir management guidelines. Firstly, for the recycle reservoir in which, the decline of reservoir pressure is arrested using gas Injection. Secondly, for the depletion reservoir, in which the reservoir pressure declines rapidly. For the recycle reservoir, it was statistically identified that the reservoir pressure was declining at less than 4%. Therefore, the acceptance criteria for the operating envelope for each well was defined using the reservoir decline of less than 4%. Similarly, for the depletion reservoir, the pressure was declining between 7% and 10%. Thus, the operating envelope's acceptance criteria were defined using the max reservoir decline tolerance of 10%. The above-identified criteria were incorporated into the integrated model framework to validate the well performance generated from the well tests. Implementing this specialized engineering approach in an integrated model framework considerably reduces the time required by engineers to validate the production well tests and provides higher levels of accuracy for production optimization, voidage replacement ratio calculation, daily rate estimation, and surveillance.