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Normalized Cumulative Production Curves Estimate Ultimate Recovery

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Operators and investors are interested in finding better metrics to evaluate the production performance of unconventional multifractured horizontal wells (MFHWs). The complete paper discusses the use of cumulative production ratio curves normalized to a given reference volume in time for different unconventional plays in North America to investigate the median trend for each play and the median ultimate recovery per play. The paper discusses the choice of 12-month cumulative production for a reference volume as a normalization parameter.

Introduction

Many methods exist for forecasting the production rate from unconventional reservoirs, but all have limitations. Recently, several publications have appeared relating the expected ultimate recovery (EUR) to the initial rate or the cumulative production after 3, 6, or 24 months. In the complete paper, these publications are reviewed, and their learnings extended, to several unconventional reservoirs.

Work in 2018 studied 147 MFHWs covering many formations in the Permian Basin and a wide range of input variables and determined EUR using rate transient analysis, numerical simulation, and decline-curve analysis. The authors of that work compared the EUR with various cumulative production intervals (3, 6, 12, and 24 months) and concluded that the ­correlation with 3 months was poor; 24 months’ cumulative production was an accurate predictor of EUR but was not considered to be an early-enough predictor. That work’s authors chose 12 months as a preferred early-time predictor of EUR and justified its use by stating that operating conditions have usually stabilized by that time. A universal type curve of cumulative production was created as a percent of EUR vs. years of production (e.g., after 1 year of production, 33% of the EUR has been produced). This type curve accounted for different well lengths and completions and both strong and weak wells. The universality of the type curve is consistent with the understanding that the factors that make a well a high- or low-rate producer affect the 12-month cumulative and the EUR proportionally. A different work from 2018 studied approximately 3,000 wells in the Delaware Basin to determine an early indicator of long-term performance. These authors used not only the EUR but also the actual cumulative production from 252 wells with 6 years of production history. Results showed that the correlation coefficient between the 6-year production and various early-time indicators (cumulative production at 30, 60, 90, and 180 days and 1, 2, 3, and 5 years) improves from 0.23 (for 30 days) to 0.73 (for 1 year) and only minimally thereafter.

A 2012 work studied public production data from more than 6,000 wells from the Barnett, Fayetteville, and Woodford shales. These authors binned the data into quartiles and used a key performance indicator (KPI) that combines a confusion matrix and a cost matrix (penalty function). Results indicated that the prediction ability of various metrics ranged from 48% (3-month cumulative production) to 85% (2-year cumulative production) and that, in some cases, the peak month production KPI was only marginally lower than the 6- or 12-month cumulative.

A 2013 work developed a simple scaling theory and a dimensionless type curve for the Barnett Shale on the basis of transient linear flow followed by boundary-dominated exponential decline. A 2018 work validated the use of this technique in the Eagle Ford and Niobrara shales. Using this type curve, short-term production data can be used to forecast the EUR, provided that the time to boundary-dominated flow is known.

Methodology

The authors of the summarized paper build on the previously described concepts and investigate the performance of 12 oil and gas shale plays.

Production Ratio (PR) With Respect to Different Reference Criteria (3-, 6-, 12-, 24-, 36-, 48-, and 60-Month Cumulative Production). Data were obtained from public sources. The cumulative production at each month was divided by one of the following:

  • 3-month cumulative production (corresponding ratio=PR3)
  • 6-month cumulative production (corresponding ratio=PR6)
  • 12-month cumulative production (corresponding ratio=PR12)
  • 24-month cumulative production (corresponding ratio=PR24)
  • 36-month cumulative production (corresponding ratio=PR36)
  • 48-month cumulative production (corresponding ratio=PR48)
  • 60-month cumulative production (corresponding ratio=PR60)

A plot was generated for each production ratio for all considered oil (PRo) and gas (PRg) shale plays. To illustrate the procedure, Eagle Ford data per oil well is presented in Fig. 1 of the complete paper. The effect of the normalization change on the data spread as different reference cumulative oil production volumes are used is observable.

With practicality in mind, and based on a review of the plots, PRo12 was selected as the standard for further work.

Generating PR12 Profiles. Having accepted that, for practical purposes, the desirable-reference early indicator of future production is the 12-month cumulative production, the authors of the summarized paper generated PR12 profiles for several selected shale plays, including Bakken, Barnett, Eagle Ford, Fayetteville, Haynesville, Marcellus, Permian, Duvernay, Montney, and Horn River. These profiles were then curve-fitted to a two-segment hyperbolic curve and extended to the 40‑year (480‑month) EUR. The authors use Eagle Ford oil shale production data to demonstrate the procedure with the aim of ultimately presenting a comparison plot of PRo12 and PRg12 profiles for the shale plays studied.

Eagle Ford Oil Example.

  • The cumulative oil production profile for each well was divided by its oil cumulative production at the 12-month mark. This ratio is referred to as PRo12. The median value of that plot is shown as red square markers in Fig. 1a. At 12 months, PRo12 must equal 1.0.
  • The number of wells producing at any given month and contributing to the median production is also shown as the blue dotted line in Fig. 1a. In this shale play sample, the well count exceeded 1,000 wells for most of the data.
  • From 80 months onward, the well count is small and the shape of the PRo12 curve is erratic and not& representative.
  • A two-segment hyperbolic curve was fitted to the data from 12 to 80 months to avoid unrepresentative data. This is shown in Fig. 1b. The “b” value of the first segment was based on decline-curve analysis of the typewell of the play, and, in all cases, the terminal decline was set at 10%.
  • The two-segment hyperbolic decline was extended to obtain the EUR ratio (EUR/cumulative production at 12 months). For practical purposes, this was defined as the cumulative production after 480 months (approximately 10 years of history+30 years of forecast). For the Eagle Ford oil shale, this ratio is 3.1. This means that, for that particular play, the EUR is 3.1 times the 12-month cumulative production. In other words, if the 12-month cumulative production of a well is known, its EUR can be estimated reliably despite a short production history.

This procedure was followed for all the shale plays and their PR12 profiles.

Fig. 1—(a) Ratio of cumulative oil production to 12-month cumulative and number of wells on production; (b) two-segment hyperbolic fit of production ratio profile.

 

Use of Normalized Production Curves To Estimate Well Performance. Once the normalized production curve for a play has been defined, the EUR for a well can be estimated by multiplying the 12-month cumulative production for each well by the value of the production ratio from the PRo12 curve at 480 months. If desired, each point of the full PRo12 curve and normalized production over 12 months can be used to obtain cumulative oil production and oil rate forecast for each well.

Conclusions

A reliable, consistent procedure to obtain the EUR of wells, especially for those with short production life, is of great value. A 12-month cumulative production ratio (PR12) curve can be an early indicator of future production. By using PRo12 and PRg12 curves (obtained from the median trend of a play) once the cumulative production at reference time for each well has been reached, it is possible to estimate quickly the EURo or EURg as applicable and produce cumulative and rate forecasts for each well on the basis of the median trend of the play.

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 199981, “Use of Normalized Cumulative Production Curves To Estimate Ultimate Recovery of Unconventional Plays in North America,” by Ivan Olea, Hamed Tabatabaie, SPE, and Louis Mattar, SPE, IHS Markit, et al., prepared for the 2020 SPE Canada Unconventional Resources Conference, Calgary, 15–16 September. The paper has not been peer reviewed. As of July 1 this paper is unavailable in OnePetro.org.

Normalized Cumulative Production Curves Estimate Ultimate Recovery

01 July 2020

Volume: 72 | Issue: 7

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