Dimensionless Section-Level Cumulative Oil Vs. Pumped Fluid Normalization Plot in Unconventional Development

Rosenhagen, Nicolas M.; Nash, Steven D.; Dobbs, Walter C; Tanner, Kevin

doi:10.2118/195204-ms

Cited by 4 publications

References 8 publications

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Improving Completions Immediately: An Applied Methodology for Real-Time Optimization

Stark

Tran

Mogck

et al. 2020

Day 1 Tue, February 04, 2020

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A proven and tested method for helping improve completion design during well stimulation is formally presented. Systematic changes in terms of cluster spacing, fluid design, proppant design, and perforating scheme were evaluated and implemented in real time. Post completion evaluation led to a series of design improvements applied to active and future projects. The ultimate goal of the project was to identify an improved completion design both in terms of productivity and economic efficiency in real time. A formal approach of beginning at the cluster level and expanding to the asset level was followed. The project focus progressed from the optimal stage completion to well completion and then section. For stage and well optimization, the target was to meet or exceed the type curve for the area while maintaining economic discipline. This paper will focus on the near wellbore aspect of asset optimization. The diagnostic pad consisted of six wells configured in a wine rack spacing design. A single diagnostic well "Wildcat No. 1" was completed individually and included a fiber-optic cable installed on casing. During completion downhole, microseismic monitoring and tilt were recorded from nearby vertical wellbores. The cluster-level flow profiles were recorded at each stage using fiber-optics. This data, provided in real time, enabled a dynamic workflow to test, assess, and immediately apply learnings. For example, stage length was tested, evaluated, and adjusted until a favorable length was identified. Improvements in the completion design around the fluid system, cluster spacing, shots per foot (spf), injection rate, and execution parameters were identified based on the Uniformity Index (UI). Temporal changes to the completion design were also reviewed and identified. This approach is as significant as the technologies that enable it and is discussed in detail.

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Improving Completions Immediately: An Applied Methodology for Real-Time Optimization

Stark

Tran

Mogck

et al. 2020

Day 1 Tue, February 04, 2020

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Application of Data Mining to Small Data Sets: Identification of Key Production Drivers in Heterogeneous Unconventional Resources

Ning

Schumann

Jin

2022

SPE Reservoir Evaluation &Amp; Engineering

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Summary In this study, we developed a data mining-based multivariate analysis (MVA) workflow to identify correlations in complex high-dimensional data sets of small size. The research was motivated by the integration analysis of geologic, geophysical, completion, and production data from a 4-square-mile study field located in the Northern Denver-Julesburg (DJ) Basin, Colorado, USA. The goal is to establish a workflow that can extract learnings from a small data set to guide the future development of surrounding acreages. In this research, we propose an MVA workflow, which is modified significantly based on the random forest algorithm and assessed using the R2 score from K-fold cross-validation (CV). The MVA workflow performs significantly better in small data sets compared to traditional feature selection methods. This is because the MVA workflow includes (1) the selection of top-performing feature combinations at each step, (2) iterations embedded, (3) avoidance of random correlation, and (4) the summarization of each feature’s occurrence at the end. When the MVA workflow was initially applied on a complex synthetic small data set that included numerical and categorical variables, linear and nonlinear relationships, relationships within independent variables, and high dimensionality, it correctly identified all correlating variables and outperformed traditional feature selection methods. Following that, a field data set consisting of the information from 23 wells was investigated using the MVA workflow aiming at identifying the key factors that affect the production performance in the study area. The MVA workflow reveals the weak correlation between production and legacy well effect. The results show that the key factors affecting production in this study area are total organic carbon (TOC) percentage, open fracture densities, clay content, and legacy well effect, which should receive significant attention when developing neighboring acreage of the DJ Basin. More importantly, this MVA method can be implemented in other basins. Considering the heterogeneity of unconventional resources, it is worthwhile to identify the key production drivers on a small scale. The outperformance of this MVA method on small data sets makes it possible to provide valuable insights for each specific acreage.

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Performance Redefined: A Business-Centric Approach to Assessing Hydraulic Fracturing Execution

Mogck,

Doucette

2024

Day 2 Wed, February 07, 2024

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The hydraulic fracturing of an unconventional well is typically the single most significant component of the expenditure for that well; however, there is no industry standard for assessing the efficiency of that operation. This work will present an approach for evaluating hydraulic fracturing performance that transcends commonly used key performance indicators (KPIs). Historically, the industry has focused on various metrics, such as pumping hours per day, to quantify a frac crew's efficiency. However, many commonly used KPIs may provide incomplete and sometimes misleading indicators of the actual performance of a given completions spread. This paper will present examples of traditionally used KPIs, instances where they have gone wrong, and offer an alternative means of consolidating and visualizing data from various commonly available sources. The intent is to better diagnose drivers affecting the performance of a given hydraulic fracturing spread. Commonly collected data from a hydraulic fracturing job, including rates, volumes, design parameters, and job logs, are transformed into consistent and easily understandable metrics. These data have been collected for hundreds of jobs and stages over the last few years and integrated into a dashboard to get a high-level understanding of performance. The authors of this paper have mined these data sets for examples to share lessons learned from experience and present some of the critical factors that can substantially impact performance. A review of historically used KPIs (stages, hours, feet per day, transition times, etc.) will reveal that none are ideal, and many suffer significant flaws. For example, a typical ‘stage’ design can vary wildly between areas. Pumping hours per day do not account for actual output during those hours. Case studies will illustrate the potential pitfalls of traditional KPI tracking and introduce the value of a more comprehensive approach. The methodology presented will divide the efficiency of a frac crew into a few broad buckets. The first encompasses surface efficiency - how physical operations on the well site affect the ability to pump. The second is hydraulic efficiency - quantifying how effectively the spread can attain and maintain the target pumping rate. The final bucket focuses on capturing overall crew performance in a single metric – slurry volume pumped. The volume pumped per day captures daily performance, while cumulative volume pumped over time reveals macro efficiency trends. Hydraulic fracturing KPIs have not been standardized. Additionally, they are often only evaluated and reviewed monthly or quarterly, not daily. Subsurface drivers of efficiency are also commonly neglected. To the authors' knowledge, this is the first work to present a methodology for holistically assessing a hydraulic fracturing operation's effectiveness and efficiency using a combination of surface and subsurface metrics trackable on a daily basis.

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Dimensionless Section-Level Cumulative Oil Vs. Pumped Fluid Normalization Plot in Unconventional Development

Cited by 4 publications

References 8 publications

Improving Completions Immediately: An Applied Methodology for Real-Time Optimization

Improving Completions Immediately: An Applied Methodology for Real-Time Optimization

Application of Data Mining to Small Data Sets: Identification of Key Production Drivers in Heterogeneous Unconventional Resources

Performance Redefined: A Business-Centric Approach to Assessing Hydraulic Fracturing Execution

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