It is better to know what you don't know than not know anything at all. For operators, this means using data analytics to understand shortcomings and successes in their own operations as well as competitors. Unfortunately, public data sources aren't always maintained to the same standards as internal data, making field analysis difficult and accurate recommendations inconsistent or impossible. Leveraging multidisciplinary data analytics from raw public data such as digital well logs and production and completion data can help deliver necessary insights to understanding key successes and shortcomings of unconventional plays.

A case study of the Wattenberg field will be presented in this session, demonstrating why public data cannot be used in its raw format and the exponential value gained from a cross-discipline analytical process. Within the field, four geological horizons are targeted through horizontal drilling – the Niobrara (A-C Chalks) and Codell formations. The Niobrara consists of alternating chalk and marl units, whereas the Codell Formation consists of a clay-rich sandstone; both were deposited within the Interior Cretaceous Seaway. The petroleum system is overpressured and is believed to be self-sourced from the organic-rich marl intervals.

This study analyzed 1,100 digital well logs to generate a surface-based geological model that delineates where horizontal wells were drilled. In addition, completion and production data from over 4,500 wells were compiled, with type curves generated based on sub-region within the field, operator and vintage to normalize for geological variabilities. Highlights of this work include: geological parameters for optimal targets; differing estimated ultimate recoveries (EUR) on a lateral foot basis as operators transition away from the core of the play; optimal completion design; and changes in wellhead liquids percentages across the play. Results can be directly traced to conclusions such as higher proppant loading and longer well lateral lengths yield materially better well performance. In general, data accessed through public sources allows for larger sample sizes; however, it's through a technically-sound methodology that the data can be analyzed at a granular level, illustrating the effectiveness of using a multidisciplinary approach.

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