Digital Workflow to Enhance Reservoir Management Strategies for A Complex Oil Field Through Real Time and Advanced Engineering Monitoring Solution

2021 ◽  
Author(s):  
Julieta Alvarez ◽  
Oswaldo Espinola ◽  
Luis Rodrigo Diaz ◽  
Lilith Cruces

Abstract Increase recovery from mature oil reservoirs requires the definition of enhanced reservoir management strategies, involving the implementation of advanced methodologies and technologies in the field's operation. This paper presents a digital workflow enabling the integration of commonly isolated elements such as: gauges, flowmeters, inflow control devices; analysis methods and data, used to improve scientific understanding of subsurface flow dynamics and determine improved operational decisions that support field's reservoir management strategy. It also supports evaluation of reservoir extent, hydraulic communication, artificial lift impact in the near-wellbore zone and reservoir response to injected fluids and coning phenomenon. This latest is used as an example to demonstrate the applicability of this workflow to improve and support operational decisions, minimizing water and gas production due to coning, that usually results in increasing production operation costs and it has a direct impact decreasing reservoir energy in mature saturated oil reservoirs. This innovative workflow consists on the continuous interpretation of data from downhole gauges, referred in this paper as data-driven; as well as analytical and numerical simulation methodologies using real-time raw data as an input, referred in this paper as model-driven, not commonly used to analyze near wellbore subsurface phenomena like coning and its impact in surface operation. The resulting analyses are displayed through an extensive visualization tool that provides instant insight to reservoir characterization and productivity groups, improving well and reservoir performance prediction capabilities for complex reservoirs such as mature saturated reservoirs with an associated aquifer, where undesired water and gas production is a continuous challenge that incorporates unexpected operational expenses.

10.2172/1464 ◽  
1998 ◽  
Author(s):  
Chris Phillips ◽  
Dan Moos ◽  
Don Clarke ◽  
John Nguyen ◽  
Kwasi Tagbor ◽  
...  

2020 ◽  
Author(s):  
Khalid Javid ◽  
Guido Bascialla ◽  
Alvaro Sainz ◽  
Mohamed Hossni Ali ◽  
Srinivas Ettireddi ◽  
...  

2002 ◽  
Author(s):  
Scott Walker ◽  
Chris Phillips ◽  
Roy Koerner ◽  
Don Clarke ◽  
Dan Moos ◽  
...  

2021 ◽  
Author(s):  
Wenyang Zhao ◽  
Salama Darwish Al Qubaisi ◽  
Salem Ali Al Kindi ◽  
Mohamed Helmy Al-Feky ◽  
Omar Yousef Al Shehhi ◽  
...  

Abstract Daily production compliance is fundamental to sustain reservoir management excellence and ultimately achieve an optimum oil recovery. The production activities execution is critical to adhere to the reservoir management guidelines and best practices. It is a more challenging task in brownfields due to the limitation of controlling system and limited access especially in offshore fields. A timely and efficient approach is undoubtedly necessary to enhance production efficiency and compliance. An integrated and automated tool has been innovated to analyze and report well production status against the guidelines and requirements in a mature offshore field with more than 50 years history. This systematic approach has been developed through integrating the planned rate, daily actual production rate, latest flow tests, and current well performance. Noncompliance is reported automatically on a user defined time scale, including daily, weekly, monthly or any customized time range within the month time. Daily violation report is generated automatically and sent to production operation for prompt adjustments and other requested actions. The automated workflow enables both daily production reporting and production compliance reporting. Daily production reporting is a routine work, which usually takes a lot of time every day. The workflow is capable of reducing 90% of the time comparing to the manual way. Production compliance reporting is currently mainly focusing on the comparison of actual production to planned rate and guideline rate. Any exception will be reported as violation. The violation dashboard summarizes the details based on the user selected time range. On daily basis, an email containing the violation details could be generated and sent to the corresponding teams for corrective actions. In this giant brown field, production GOR is a primary controlling parameter. The latest flow tests have been taken into account to evaluate the gas production compliance. Any violation to the GOR guidelines will be reported in the same communication email for timely correction. With the innovated tool, the violation ratio of the giant offshore field has been successfully reduced and controlled. The usual responding time for corrections has been dramatically reduced from months to days.


2021 ◽  
Author(s):  
Erismar Rubio ◽  
Mohamed Yousef Alklih ◽  
Nagaraju Reddicharla ◽  
Abobaker Albelazi ◽  
Melike Dilsiz ◽  
...  

Abstract Automation and data-driven models have been proven to yield commercial success in several oil fields worldwide with reported technical advantages related to improved reservoir management. This paper demonstrates the implementation of an integrated workflow to enhance CO2 injection project performance in a giant onshore smart oil field in Abu Dhabi. Since commissioning, proactive evaluation of the reservoir management strategy is enabled via smart-exception-based surveillance routines that facilitate reservoir/pattern/well performance review and supporting the decision making process. Prolonging the production sustainability of each well is a key pillar of this work, which has been made more quantifiable using live-tracking of the produced CO2 content and corrosion indicators. The intensive computing technical tasks and data aggregation from different sources; such as well testing and real time production/injection measurements; are integrated in an automatic workflow in a single platform. Accordingly, real-time visualizations and dashboards are also generated automatically; to orchestrate information, models and multidisciplinary knowledge in a systematic and efficient manner; allowing engineers to focus on problematic wells and giving attention to opportunity generation in a timely manner. Complemented with numerical techniques and other decision support tools, the intelligent system data-driven model assist to obtain a reliable short-term forecast in a shorter time and help making quick decisions on day-to-day operational optimization aspects. These dashboards have allowed measuring the true well/pattern performance towards operational objectives and production targets. A complete set of KPI's has helped to identify well health-status, potential risks and thus mitigate them for short/long term recovery to obtain an optimum reservoir energy balance in daily bases. In case of unexpected well performance behaviors, the dashboards have provided data insights on the root causes of different well issues and thus remedial actions were proposed accordingly. Maintaining CO2 miscibility is also ensured by having the right pressure support around producers, taking proactive actions from continues evaluation of producer-injector connectivity/interdependency, improving injection/production schedule, validating/tuning streamline model based on surveillance insights, avoiding CO2 recycling, optimizing data acquisition plan with potential cost saving while taking preventive measures to minimize well/facility corrosion impact. In this work, best reservoir management practices have been implemented to create a value of 12% incremental oil recovery from the field. The applied methodology uses an integrated automation and data-driven modeling approach to tackle CO2 injection project management challenges in real-time.


1997 ◽  
Author(s):  
Roy Koerner ◽  
Don Clarke ◽  
Scott Walker ◽  
Chris Phillips ◽  
John Nauyen ◽  
...  

10.2172/2201 ◽  
1997 ◽  
Author(s):  
Chris Phillips ◽  
Dan Moos ◽  
Don Clarke ◽  
John Nguyen ◽  
Kwasi Tagbor ◽  
...  

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