US Oil Reserve Growth

This is a guest post by Dennis Coyne.

The views expressed in this post are those of Dennis Coyne and do not necessarily  represent those of Ron Patterson.

How much oil can be extracted from known oil resources profitably? This depends on many factors, the price of oil and technological progress in oil extraction methods are the chief factors, but improved knowledge gained through the development wells drilled and the corresponding output and geological data as known reserves are developed is important as well. Oil reserves do not grow, they deplete as the oil is produced. With increasing knowledge, oil price, and improved technology and production methods, the estimate of oil reserves changes over time and on average these estimates tend to increase, this is what we mean by reserve growth.

The United States Energy Information Administration (EIA) has detailed data on proven (1P) reserves and proven discoveries from 1977 to 2013, but Jean Laherrere has taught us that it is proved plus probable (2P) reserves that we should focus on.

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Eagle Ford, Permian Basin, and Bakken and Eagle Ford Scenarios

This is a guest post by Dennis Coyne

Increased oil output in the US has kept World oil output from declining over the past few years and a major question is how long this can continue. Poor estimates by both the US Energy Information Administration (EIA) and the Railroad Commission of Texas (RRC) for Texas state wide crude plus condensate (C+C) output make it difficult to predict when a sustained decline in US output will begin.

 About 80 to 85% of Texas (TX) C+C output is from the Permian basin and the Eagle Ford play, so estimating output from these two formations is crucial. I have used data from the production data query (PDQ) at the RRC to find the percentage of TX C+C output from the Permian (about 44% in Feb 2015) and Eagle Ford plays (40% in Feb 2015).

Dean’s estimates of Texas C+C output are excellent in my opinion and are close to EIA estimates through August 2014. I used EIA data for TX C+C output through August 2014 and Dean’s best estimate from Sept 2014 to Feb 2015. By multiplying the % of C+C output from the RRC data with the combined EIA and Dean estimate, I was able to estimate Eagle Ford and Permian output. The chart below shows this output in kb/d.

  
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The Oil Shock Model with Dispersive Discovery- Simplified

 

This is a guest post by Dennis Coyne

Originally posted at peak oil climate and sustainability

Some changes have been made to this post see after the Excel File link.  Below figure 10.

The Oil Shock Model was first developed by Webhubbletelescope and is explained in detail in The Oil Conundrum. (Note that this free book takes a while to download as it is over 700 pages long.) The Oil Shock Model with Dispersive Discovery is covered in the first half of the book. I have made a few simplifications to the original model in an attempt to make it easier to understand.

shockmodfig/

Figure 1

In a previous post I explained convolution and its use in modelling oil output in the Bakken/Three Forks and Eagle Ford LTO (light tight oil) fields. Briefly, an average hyperbolic well profile (monthly oil output) is combined with the number of new wells completed each month by means of convolution to find a model of LTO output.

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Oil Field Models, Decline Rates and Convolution

This post is by Dennis Coyne

The eventual peak and decline of light tight oil (LTO) output in the Bakken/ Three Forks play of North Dakota and Montana and the Eagle Ford play of Texas are topics of much conversation at the Peak Oil Barrel and elsewhere.

The decline rates of individual wells are very steep, especially early in the life of the well (as much as 75% in the first year for the average Eagle Ford well), though the decline rates become lower over time and eventually stabilize at around 6 to 7% per year in the Bakken.

What is not obvious is that for the entire field (or play), the decline rates are not as steep as the decline rate for individual wells. I will present a couple of simple model to illustrate this concept.

Much of the presentation is a review of ideas that I have learned from Rune Likvern and Paul Pukite (aka Webhubbletelescope), though any errors in the analysis are mine.

A key idea underlying the analysis is that of convolution. I will attempt an explanation of the concept which many people find difficult.

At Wikipedia there is a fairly mathematical presentation of the concepts which often confuses people.  There are a couple of nice visuals to convey the concept as well see this page.

In the visual below a function f (in blue) is convolved with a function g (in red) to produce a third function (in black) which we could call h where h=f*g and the asterisk represents convolution, just as a + symbol is used to represent addition.

Convolution of box signal with itself2.gif
Convolution of box signal with itself2” by Convolution_of_box_signal_with_itself.gif: Brian Amberg
derivative work: Tinos (talk) – Convolution_of_box_signal_with_itself.gif. Licensed under CC BY-SA 3.0 via Wikimedia Commons.

I think the best way to present convolution is with pictures. Chart A below shows a relationship between oil output (in barrels per month) and months from the first oil output for the average well in an unspecified LTO play.

This relationship is a simple hyperbola of the form q=a/(1+kt), where a and k are constants of 13,000 and 0.25 respectively, t is time in months, and q is oil output.

Chart A is often referred to as a well profile. The values for the constants were chosen to make the well profile fairly similar to an Eagle Ford average well profile. EUR30 is the estimated ultimate recovery from this average well over a 30 year well life.

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Eagle Ford Update, Texas Condensate and Natural Gas

This is a brief update on Eagle Ford Crude plus Condensate (C+C) output through February 2014.  It can also be found at Peak Oil Climate and Sustainability.

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 Figure 1- RRC Data provided by Kevin Carter 

I have used my usual method of estimation where I find the percentage of total Texas(TX) C+C output that is from the Eagle Ford(EF) play (I call this %EF/TX ) and multiply this by the EIA’s estimate of TX C+C output.

The chart shows the Railroad Commission of Texas (RRC) Eagle Ford estimate (EF RRC) in thousands of barrels per day (kb/d), the EF est (kb/d) as described above, the percentage of EF C+C that is condensate (EF %cond/C+C), and the %EF/TX also described above.

As before I would like to thank Kevin Carter who created a method to simplify gathering the Eagle Ford data.

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