Digital transformation of existing processes using technologies such as big data, advanced data analytics, machine learning, automation and cloud computing will enable continuous performance improvements within the operational sphere. The application of the technology will link the physical and digital world, providing a digital model of physical assets and processes. It will represent the evergreen, wholly integrated digital asset model - from reservoir to export pipeline. The Brage operations team identified processes with the highest potential for digital transformations during an initial opportunity framing workshop. Based on pain points and business needs, the clear emphasis is in the areas of production & well performance optimization, high-spec live-data visualization, as well as the entire flow of information from database integration up to dashboarding. Strong reliance on an improved data infrastructure and IT/OT performance will require close cooperation with the IT/OT team. New solutions will be aligned with and integrated into already identified global solutions. The improved acquisition of data, together with the integration of already existing ‘Digital Twin’ technologies will enable the first redesign of work processes. Prioritization of processes to be transformed will be mandated by their business impact as well as possibility to scale to other Wintershall Dea assets too. Focus areas, such as Slugging, Digital Production Engineer, Intelligent Maintenance, Dashboarding and Planning/Scheduling, were defined as more and more ideas evolved. Individual processes such as water injection and scaling surveillance were made more time efficient and transparent. The vision is to bring all processes together into a customizable and collaborative dashboarding solution. Intended completion of the first phase is Q4 2019. The following phase will be the execution of a larger scoped technology implementation that will be defined in detail by then.
The simplest and oldest method to represent hydraulic fractures in reservoir simulation models is to use a negative skin factor for stimulated wells, the implicit representation. However, a negative skin factor approach does not capture several flow aspects that impact production significantly, especially in heterogeneous, lower permeability reservoirs. A better, more realistic, production forecast is obtained by modeling the effects of induced fractures and their associated flow patterns explicitely in the dynamic reservoir model using local grid refinements (LGR). This approach has been used and demonstrated in the industry for several decades and has proven to be a reliable and flexible approach. In single well models, with current computing power, this approach works well. In full field models, however, dynamic reservoir models with LGR's are computationally very demanding, and not applicable in many cases.To overcome these computing problems in larger, more complicated models with many wells, a so-called proxy model was developed that also represents a fracture explicitly. In the proxy approach, the fracture is modelled using a set of well completions placed in the host gridblocks associated with the (planned) hydraulic fracture geometry. The explicit proxy model approach is significantly (10x) more efficient in run-times, allowing for much faster scenario developments, while maintaining a similar quality production forecast.To calibrate the quality of the production forecast from the proxy approach, the proxy model settings were tuned against the LGR approach. An important aspect of this is in setting the transmissibility from the reservoir to the completions to match the productivity calculated with an explicity LGR model. The (local) PI of a proxy completion is controlled by a so-called proxy connection (transmissibility) factor. Proxy connection factors, in the Proxy approach, are a function of; dimensionless fracture conductivity, dimensionless fracture height, dimensionless fracture length, permeability heterogeneity effects and selected grid discretization options.To validate the Proxy model for a real field development scenario, the Proxy approach was assessed against the LGR approach for three wells in a very heterogeneous gas condensate reservoir. The LGR models were developed by history matching several years of actual production history, and then used to make forecast simulations. For all three wells, a close match was obtained between productivity forecasts of the Proxy and the LGR approach.Next to the improvement in efficiency, a further advantage of the Proxy model is that the fractures are defined in the schedule section of the run. In full field production forecasting, this allows for the representation and activation of a fractured well later in the life of the field, without disturbing the production simulation before the specific wells and fractures are present in the field, which is an issue with the LGR approach.
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Objectives/Scope The production technology working environment of an oil brownfield is usually an inconsistent collection of tools and spreadsheets. In this paper, we will explore Wintershall Dea's digitalisation journey from a patchwork of tools and spreadsheets to a unified corporate Production Technology Workbench (PTW) solution starting from the replacement of an existing and ageing tool on an asset on the Norwegian continental shelf and ending by incorporating the requirements of other assets from Wintershall Dea's diverse and geographically dispersed portfolio. Methods, Procedures, Processes The project started by selecting the low-code application platform suitable to be used as the basis for the journey. After a proof-of-concept stage, an Agile project was launched owned by the asset and with a geographically dispersed Development Team conformed by Wintershall Dea's Product Owners, IT/OT experts, UX consultants and Eigen's scrum master and Development Team. After the delivery of the MVP, a second Product Owner was incorporated from a second asset. The Agile project continued to deliver on enhanced functionality and requirements that would most benefit both assets. Results, Observations, Conclusions The original production system calculations and workflows are vital for the asset. However, such patchworks are not easy to work with and complex to maintain or change. This had a negative effect on the efficiency as work is time-consuming and cumbersome. Well anomalies were often detected by actively looking for them daily in various plots, reports and platforms, and therefore the detection and response time to production events was delayed. A Production Technology dashboard with built-in / automated data processing for standard tasks provides engineers with the required transparency of data to identify issues and pain-points in a timely manner. This helps engineers to proactively intervene to mitigate unplanned losses and downtime, reducing the amount of deferred production. Investment in a corporate-wide unified (standard UX) platform, will help engineers when starting new assignments to spot issues easier and quicker independently of the asset they are assigned to. But beyond a standardization, each engineer needs to be able to create individual workflows (for effects such as scaling, slugging, sand etc.) for their needs by means of the self-service capabilities of the technology. Also, the quick access to frequently used and relevant data could be accessed through one platform, making everyday life of the production engineer more efficient and smoother. Over the timeframe of 15+ Sprints the Product Owners refined and re-defined the exact functionality they would like to see delivered. Novel/Additive Information The PTW concept seeks to minimise the time that engineers require to learn the tool and use it to inspect, analyse, and make decisions to optimise the production of the field. This is one of Wintershall Dea's first projects executed following Agile, using a geographically dispersed team, during the restrictions imposed by the pandemic. The multi-Product-Owner project approach is a novel way to govern the evolution of the tool to suit multiple stakeholders. In comparison to a E&P typical waterfall project management approach, the application of Scrum really showed added value in reducing risk early on, increasing visibility and transparency and adapting to the customer's needs (production engineers) throughout the process.
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