In E&P, from asset managers to front end operations staff, there is a common problem - we are data rich, but information poor. In particular, timely well-by-well production surveillance and allocation often remains a problem. Gathering data, even real time data, from wells and facilities hasn't been an issue, but validating the data and relating this data to individual well production rates in a coherent, consistent and timely manner and then taking prompt action, is a challenge. Traditional routine well testing simply provides a series of snap-shots of a well's performance, which may or may not reflect the production during the intervening period. Errors are typically spread across the wells and reservoirs through a reconciliation process comparing estimated well productions and actual metered sales on a weekly or monthly basis. This paper describes the development and application of a new tool, FieldWare* PRODUCTION UNIVERSE * (PU), which estimates real time well production rates from simple field measurements and provides online reconciliation against bulk measurements and export meters. The novel aspect of the technique is that it uses dynamic, data-driven models to describe the production process, together with a new well test methodology for capturing the data to build the initial models. Well tests include a deliberate disturbance to the production to determine the dynamic characteristics of a well. The models do not require underlying physical or process models, predetermined multiphase flow correlations, compositional data or well/piping/equipment details. This has made the models quick to set-up and easy to maintain. FieldWare PRODUCTION UNIVERSE is now fully operational and used for well-by-well production surveillance and monitoring at many of Shell's production facilities worldwide, both onshore and offshore. The application of PU has helped increase production through improved monitoring, resolved hydrocarbon allocation problems through real time reconciliation, allowed an increase in time between well tests and reduced travel to field locations. The availability of real time production data is a key enabler for future smart optimization and intelligent diagnostics. PU is a foundation element for Shell's Smart Fields initiative. Introduction This paper is intended to introduce the Shell's PRODUCTION UNIVERSE project at a high level and share some of the experiences and findings of the first phase of the development. In particular, we wish to highlight the PU application as an example of the innovative synthesis of oil and gas operational and technical expertise and state of the art mathematical techniques. Historically the oil and gas production industry has relied on traditional methods for individual well production flow monitoring and surveillance. This provides periodic well test information using test separators or multiphase meters, sometimes supplemented with real time pressure and temperature data gathered from the well between tests. Since the test separators / multiphase meters are normally shared among a number of wells, the actual performance of a well is only measured periodically or on demand. Typically around 2% of the well monthly production is measured by well testing. Thus the surveillance of individual wells is a periodic discontinuous process. This is not optimal, as many well problems are not detected until a well is re-tested. Well test conditions may be very different from actual operating conditions. This conventional surveillance and monitoring methodology is premised on the concept that oil and gas production systems were largely steady state and these snap shots in time were adequate to manage the business. However in many fields, well performance and plant-operating conditions can change rapidly and there is value in closer and more regular well production surveillance. Furthermore when a field enters a period of rapid production decline, it requires a higher level of attention and higher frequency of data gathering. The inadequacy of the "snap shot" paradigm then becomes even more pronounced.
With current economic realities, now is the time to produce "more with less". Exception Based Surveillance (EBS) helps eliminate waste in an engineer's day, by removing unnecessary analysis and allowing the engineer to focus on the highest value tasks. For the surveillance of oil wells, an efficient and effective way to achieve this is to use an automated Exception Based Surveillance System, often augmented by data-driven well rate estimates. Specifically, this paper provides examples from Shell operations in Gabon, Malaysia, and the Netherlands on how EBS systems have been set up to address day to day production challenges. The multiple EBS Systems to be described here have been achieved via the tight integration of real-time data in Well, Reservoir and Facilities management (WRFM) workflows and the automation of complex calculations and rule sets. This paper also describes the WRFM "Next Generation surveillance tool" (NGT) currently being rolled out in several Shell assets (Clinton 2016). The work described here regarding enhanced Exception Based Surveillance Systems and integrated Portals go beyond just deploying tools. To be sustainable and value adding over existing practices, the introduction of these systems requires the transformation of roles, processes and tools to fully and efficiently leverage and gain value from now mature
This paper describes the large-scale trial of Real-Time Optimization (RTO) that Shell Malaysia E&P has conducted on the Integrated Gas Production System iln Sarawak, implementing models for real-time monitoring and optimization of wells and facilities on a gas production network spanning more than 100 wells on more than 40 platforms across a number of different Production Sharing Contracts (PSCs). We highlight how Digital Oil Field (DOF) practices enable field-based data to be turned into information, support decision making, and lead to actions that ensure production is optimized continuously. Additionally, this approach replaces the traditional, daily or monthly optimization by a continuous one. The system generates optimal set-points for the control variables which are executed by the operators. Closed loop control is possible with remotely operated chokes which would allow the optimization of the entire gas system to be fully automated and minute-by-minute.
On a daily basis, the Well, Reservoir and Facility Management (WRFM) team screens all producer and injector wells to identify those wells that are under-performing or outside safe operating limits. A 'Well Operating Envelope' tool has been developed, focused on establishing the boundary conditions of various safety-critical parameters and optimized well performance. Current well operating conditions, derived from real-time gauges and flow estimates from Production Universe (PU), are monitored vis-à-vis these parameters via this tool to identify the "problematic" wells. Various diagnostic tools (i.e. Surface P-Q curves, VLP-IPR Nodal Analysis, Tulsa Flowline erosion model, Gas-Lift response curve, Inflow performance, SC-SSSV pressure plot and Hall plot derivatives) have been used and visualized for better understanding of the well flowing conditions for both production and injection systems. This tool fetches data from multiple databases like Data Historian, Energy Components and Production Universe (PU); it is also capable of interfacing with Prosper and WinGlue to fetch well performance data automatically. Following improvements have been observed with implementation of this tool:Traffic light and graphical representation enables quick well surveillance in identifying problematic wells and taking corrective measures.Monitoring of the daily PU estimated production vis-à-vis well tests, allocated production volumes and the physical well models will increase hydrocarbon accounting efficiency.Monitoring real-time parameters like FTHP, FBHP, and flowrates allows the Petroleum Engineers and Operations to operate safely within defined boundaries.Monitoring of parameters like GOR, drawdown will enable adherence to reservoir management guidelines and reduce potential reserve losses. Visualization of information from multiple data sources into this real-time tool provides an effective and efficient monitoring to ensure optimal well production within safe limits on a day-to-day basis for well, reservoir and facility management.
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