Completing the Second Target: Finding Optimal Completion Practices for the Three Forks Formation in the Williston Basin Using Multivariate Statistical Analysis

Williams, Brandon L.; Weaver, Brian Michael; Weijers, Leen

doi:10.2118/173377-ms

SPE Hydraulic Fracturing Technology Conference 2015

DOI: 10.2118/173377-ms

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Completing the Second Target: Finding Optimal Completion Practices for the Three Forks Formation in the Williston Basin Using Multivariate Statistical Analysis

Brandon L. Williams

Brian Michael Weaver²,

Leen Weijers³

Abstract: The Three Forks Formation in the Williston Basin has started to see a large increase in activity in the past six years. This is largely due to the shallower Bakken Formation transitioning into an infill development mode and operators looking at finding incremental reserves from the Three Forks Formation below. The objective of this paper is to evaluate the geological and completion variables of Three Forks horizontal wells in the North Dakota portion of the Williston Basin, and show which factors impact produc… Show more

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Cited by 3 publications

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Sand, Resin-Coated Sand or Ceramic Proppant? The Effect of Different Proppants on the Long-Term Production of Bakken Shale Wells

Schmidt²,

Barhaug³

et al. 2015

Day 3 Wed, September 30, 2015

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Proppants and their effect on the production of wells are not thoroughly understood. When selecting a proppant, operators deliberate: “Do I purchase a low-cost proppant to reduce completion costs or do I spend more for higher conductivity to increase long-term production and greater return on my investment?” Good well data can be difficult to obtain and completion designs can vary. Hence, only a few existing case histories provide apples-to-apples comparisons of long-term production performance based on the use of different proppant types. Continuing our prior research (SPE Paper 169544), we present data that will help operators make informed decisions when selecting proppants for optimizing Bakken wells. To investigate effectiveness of different proppants, researchers tracked long-term production rates of several comparable well sets. For example, in the first study, three wells on the same pad in the Haystack Butte Field in McKenzie County, North Dakota were completed by one operator. A second study included 11 Bakken wells fractured by another operator in the Grail Field in McKenzie County. All three wells in Haystack Butte Field were hydraulically fractured with similar completion methods. The only significant difference was the proppant type. One well used 100% uncoated sand, another well combined 45% uncoated sand with 55% resin-coated sand, and the third well used 45% uncoated sand and 55% ceramic proppant. The well completed with sand and ceramic proppant did not have the highest initial production rate (IPR), but had, on average, 20% higher production over a 365 day period. The well where sand was combined with resin-coated sand produced a higher IPR. However, over 365 days, that well's production was outpaced by the other two wells with the sand/ceramic well delivering the best long-term production of all three. Similar findings were confirmed among the wells in the Grail Field. This study focused on 11 Bakken wells that used sand with a tail in of 30% to 40% ceramic proppant, sand with a tail in of 30% resin-coated sand, and sand with 50% higher volume. It also indicated that using a high percentage and high volume of ceramic proppant delivers superior long-term economic benefits in Bakken wells. These findings, in addition to others outlined in the paper, challenge the preconception that wells completed using ceramic proppant should deliver higher initial production rates. Time and again, the findings demonstrated that the long-term production of Bakken wells completed with ceramic proppant significantly outperforms wells completed exclusively with other proppant types. Moreover, data demonstrates that compared to sand-only completions, resin-coated sand helped improve initial production but did nothing to improve long-term production, especially in deeper wells.

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Sand, Resin-Coated Sand or Ceramic Proppant? The Effect of Different Proppants on the Long-Term Production of Bakken Shale Wells

Schmidt²,

Barhaug³

et al. 2015

Day 3 Wed, September 30, 2015

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Evaluating the Relationship Between Well Parameters and Production Using Multivariate Statistical Models: A Middle Bakken and Three Forks Case History

Lolon¹,

Hamidieh

Weijers³

et al. 2016

Day 3 Thu, February 11, 2016

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Building a predictive statistical model for evaluating the impact of various fracture treatment and well completion designs on production has been of great interest in the oil and gas industry. The objectives of this study were to evaluate the benefits of advanced statistical and machine-learning techniques for predicting production from oil wells, highlight the strengths and weaknesses of these techniques, and gain insight into the relationship between well parameters and production. The predictive models are described through mathematical functions or algorithms that rely on well data (training set). The ongoing dilemma is that these models often result in poor predictions, even if they result in a high R-squared (0.7 or higher). The new perspective that this study brings is the importance of cross-validation with "hold-out" datasets in the workflow to develop reliable statistical models. A database of available completion and production data has been assembled from the North Dakota Industrial Commission (NDIC) and Frac Focus websites and from internal completion documentation. To date, there are at least 6,800 horizontal wells completed in the Middle Bakken formation and 3,600 completed in the Three Forks formation on the North Dakota side of the Williston Basin. Various models such as multiple regression, random forests, and gradient boosting machine were built to predict the cumulative oil production of the Middle Bakken and Three Forks horizontal wells. Model predictive abilities were assessed by cross-validating the root mean squared errors (in cross-validation, a hold-out set was used to assess the modelis predictive ability). The results showed the following conclusions about statistical evaluation techniques: 1) regression models that account for overfitting provided the best predictive ability, 2) gradient boosting model with the highest R-squared value had the worst predictive ability for the specific datasets in this paper— which shows why it is critical to not rely solely on R-squared value to assess a modelis predictive ability, but to also perform cross-validation, and 3) random forests and gradient boosting machine can be used for determining variable importance. Moreover, we observed that there is statistical evidence to support the presence of important interactions among variables in predicting cumulative oil production. For the Middle Bakken and Three Forks wells included in this study, the results showed that water cut, which can be used as a proxy for reservoir quality, is the most important predictor for cumulative oil production. However, the most important completion-related variables for predicting oil production were total frac fluid and proppant pumped. The analysis and results presented in this paper will enable companies to apply the approach to their own data when building production prediction models and analyzing the complex relationships of variables that control well performance.

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A Cost/Benefit Review of Completion Choices in the Williston Basin Using a Hybrid Physics-Based Modeling/Multi-Variate Analysis Approach

Mayerhofer¹,

Oduba²,

Agarwal³

et al. 2017

Day 1 Mon, October 09, 2017

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In the Williston Central Basin the role of a well's completion design has a significant impact on well productivity and ultimate recovery. More than 12,000 horizontals have been drilled and completed while completion practices continue to vary widely across the basin. Several companies have adopted slickwater-only designs while others have dramatically increased proppant mass. Completions strategies have differed depending on the area in the basin. The objective of this paper is to discuss the impact of various completion changes in the Central Basin and determine which particular change delivers the most "bang for the buck" using a $/BO metric. The approach centered around multi-variate analysis (MVA) from an extensive petrophysical/completion/production database to verify what completion and petrophysical parameters independently drive production in different areas. While MVA has been used by the authors and many others before, statistical models are limited by their ability to provide predictive relationships (mostly simple linear regressions and un-reliable beyond the data range). This paper provides a novel hybrid approach that uses calibrated relationships from physics-based modeling (combination of fracture and numerical reservoir modeling) between completion parameters and production response in combination with statistical MVA results. Specifically, the physics-based model is calibrated or "history matched" to a measured production/completion parameter response as provided by MVA, thus delivering a constrained and more physically realistic production response to suggested completion changes. This model is then coupled with a completion cost model to determine which completion method is the most effective to lower $/BO. Many common completion parameter changes, such as increasing stage intensity, moving to plug & perf cemented well designs, increasing injection rate, increasing proppant mass per lateral foot and fluid volume per lateral foot, have a positive impact on production and are advantageous to lower $/BO in all areas of the Middle Bakken and Three Forks. The new hybrid MVA approach indicates that pumping slickwater treatments with average proppant concentrations of 1 lb/gal and treatment sizes from 750 to 1,150 lb/ft at pump rates approaching 100 bpm through a stage length of 200 ft (50 stages for a 10,000 ft lateral) may be the economic optimum provided there are no significant well communication issues.

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Completing the Second Target: Finding Optimal Completion Practices for the Three Forks Formation in the Williston Basin Using Multivariate Statistical Analysis

Cited by 3 publications

References 1 publication

Sand, Resin-Coated Sand or Ceramic Proppant? The Effect of Different Proppants on the Long-Term Production of Bakken Shale Wells

Sand, Resin-Coated Sand or Ceramic Proppant? The Effect of Different Proppants on the Long-Term Production of Bakken Shale Wells

Evaluating the Relationship Between Well Parameters and Production Using Multivariate Statistical Models: A Middle Bakken and Three Forks Case History

A Cost/Benefit Review of Completion Choices in the Williston Basin Using a Hybrid Physics-Based Modeling/Multi-Variate Analysis Approach

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