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.
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.
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.
One of the key aspects of production optimization and monitoring towards digital transformation requirements is to have reliable and accurate data / measurement. This submission demonstrates how the smart technologies for direct wellhead measurement using Coriolis meter in gas field significantly help asset in production monitoring and Opex optimization while accurately regulating the field rates. The use of the smart technology in direct well head measurement provided real time insight into well production, with continuous and reliable quality data on production enabling Reservoir and Production Engineers to take timely decisions to optimize production, improve mass balance, better reservoir management, and reduce operating cost. The technology also had built in advanced diagnostics and connectivity features paving way for digitalization of oil fields and remote online access of data. The high operating range and flexibility in switching between wells offered ease of adaptability, reduced engineering, and commissioning costs as well as reduced maintenance and inventory requirement in mass implementation. Prior to scale-up, a trial / pilot was conducted in collaboration between ADNOC TC, Bab site Production & Instrumentation team and vendor for the technology over a period of 2 months. First, Multiple wells were selected from different operating envelop aiming different reservoirs. Then, the technology was tested by installing the Wet-Gas Coriolis meter in series with a portable well testing package provider. The measurement of the well tests from both techniques were compared. This is to evaluate the performance of the technology in having a reliable data compared with the current periodic measurement. Finally, evaluation report was produced to show the challenges, data verification and validation, then plan for wide field implementation. The technology provides real time insight and continuous monitoring of well production and its profile resulting in better production management. With direct real time well head measurement, significant CAPEX and OPEX savings can be achieved in additional to optimizing production with the use of digital transformation capable technology. Additionally, Support the asset digital and back allocation initiatives. Significant optimization on periodic portable separator well testing requirement. Permanent installation of the Wet Gas Coriolis meter on all wells will empower continuous production monitoring capabilities by increasing the availability of the real time multivariable well data. Continuous data and actionable insights will be used to identify new development opportunity to maximize recovery. Advanced diagnostics capabilities enable predictive maintenance and reducing operating costs. Improved Reservoir and well modeling and production management. No intervention cost required and enhanced HSE measures. Well behaviors change over time and can't be accurately predicted specially with the depleted wells. The current method of relying on intermittent well testing data is insufficient, expensive, labor intensive and increases safety risk. Continuous real time insight into production is essential in optimizing production, improving mass balance, better reservoir management and reducing optimizing cost. The implantation in 60 wells have a value proposition of $5.98 M over a period of 5 years.
This paper reviewed the interpretation of repeat fall-off tests acquired in two vertical pattern injectors operating in a carbonate reservoir undergoing full field development. Water Alternating Gas first pattern (WAG-1) started in August 2002 with a period of continuous gas injection until 2006 when the first water cycle was initiated. In the second pattern (WAG-2) water injection was initiated in June 1998 until September 2007 when the first gas cycle started.A few pressure fall-off tests were acquired during the monophasic injection phase mostly to verify well injectivity. After Water Alternating Gas (WAG) cycles started, pressure fall-off tests were usually acquired at the end of each three-month injection cycle with 1:1 WAG ratio. Analytical fall-off test interpretation relied on the use of the two-zone radial composite model. The apparent permeability thickness product was corrected with the Perrine formulation of multiphase mobility. Triphasic oil permeability was calculated using the modified Stone I model. Multiple fall-off test interpretations indicated that the two pattern vertical injectors behaved differently even though both being fractured. The difference in behavior was linked to different perforated intervals and reservoir properties. Gas and water injection rates were showing differences between both pattern injectors as a consequence. No major operational issue was reported during the three-year operation of both WAG patterns. During the WAG cycles, gas banks were found to be of a small inner radius and almost undetectable at the end of the subsequent water cycle. Changes in the pressure derivative slope at the end of the subsequent water injection cycle indicated most likely the creation of an effective mixing zone of injected gas and water in the reservoir.Numerical finite-volume simulation was required to account for potential injected fluid segregation and, the multi-layered and heterogeneous nature of the reservoir. Repeat saturation logs acquired in observation wells provided critical information on the saturation distribution away from the injection wells. Enhanced vertical sweep conformance through phase mobility control in the presence of strong reservoir heterogeneity was the major expected benefit from an immiscible WAG displacement mechanism. All available observations were reviewed and integrated using a history-matched reservoir simulation sector model with boundary conditions obtained from a full-field model.
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