Uncover new strategies for high-performing unconventional wells
Facing tight margins and the pressure to continuously increase productivity, operators in unconventional plays are looking for new tactics to keep their operations profitable. Unconventional assets have ample availability of low-resolution data across thousands and thousands of fractured horizontal wells—representing a potential goldmine of information to inform operational strategies. However, in reality, an inability to seamlessly integrate and process this data makes conducting timely and accurate analysis near-impossible.
Currently, engineers must use numerous disparate applications to complete workflows, with data scattered between tools. In addition to wasting valuable time, this also introduces the risk of producing errors and of using out-of-date information. Finding new ways to easily manage and use this enormous volume of distributed data is among the biggest challenges facing operators.
Rapidly perform workflows with machine learning technology
With easily accessible and integrated data, engineers can quickly and efficiently pull information for analysis and workflows. As a result, operators can pinpoint where and how to optimize well performance. Reservoir Analytics from SLB uses high/low frequency static and time series data and machine learning methodologies to uncover answers to critical unconventional challenges. The application has the capability to reduce time to solution from weeks to hours by generating calculated variables on the fly and interactive visuals of multi-dimensional data. Available to operators through the cloud-enabled Delfi environment, it can be run on any laptop and be purchased on a monthly subscription basis.
- Workflow 1: Well Inventory Ranking
Use completion or production data to analyze wells and rank them based on their performance, enabling engineers to identify wells where output could be improved or pinpoint potential refracturing candidates.
- Workflow 2: Well Productivity
With wells ranked by performance, operators can then conduct well-level analysis using standard industry methodologies and machine learning technology to forecast production.
- Workflow 3: Asset Forecasting
Explore historical asset performance and future projections to accurately assess production behavior, decline curves, and EUR.
- Workflow 4: Completion Optimization
Deploy machine learning models to find the optimal completion design and proppant and fluid volumes for a target production.
With a host of powerful features, this best-in-class, open, cloud-native, and secure platform is a go-to solution for ensuring sustained productivity. Learn how Reservoir Analytics can help you seamlessly plan for all unconventional asset development needs, be it assessment, evaluation, or planning. See real-life examples of how engineers can use Reservoir Analytics to perform rate transient analysis, decline curve analysis, completion optimization, diagnostic plotting, BHP calculations, and more in a powerful cloud-based platform.