Rocky Mountain Front Range Outcrops and Reserves

Theoretically, structural hydrocarbon traps might be present downdip from the near-mountain, front range outcrops of various oil and gas producing formations, of the Denver Basin.

There would be several ways to drill into such reservoirs, and obviously, if near-vertical penetration from a surface location upon the actual producing-formation outcrop occurs, a large amount of gross pay will be encountered. Thus, the question becomes, “Will a suitable trap be found?” Fault traps appear possible, as shown in the images.

Additionally, pressures indicate faults may exist:
“Although the overlying Codell-Niobrara reservoirs are overpressured, the Muddy (J) Sandstone is underpressured. An original formation pressure of 2,750 psi was reported by Higley and others (2003). The depth of the Muddy (J) Sandstone is about 7,000 ft, so the formation is clearly underpressured, because the pressure-depth ratio is less than the hydrostatic gradient of 0.433 psi/ft that characterizes fresh water.
. . .
A [test-version] numerical flow model . . . (Belitz and Bredehoeft, 1988) . . . also showed that the Dakota J interval must be hydraulically isolated from recharge areas along the Front Range of Colorado where rocks of Dakota age crop out. Hoeger (1968) noted that although the Dakota Group crops out at relatively high elevations along the Front Range, those outcroppings seem to have little influence as a high-potential water source on the regional hydrodynamic environment of the J system in the Denver Basin, and he conjectured that regional flow barriers, possibly faults or a facies trend of low transmissibility, must be present to provide that isolation.”

From:
http://pubs.usgs.gov/of/2011/1175/pdf/OF11-1175.pdf and

http://geosurvey.state.co.us/pubs/online/Documents/1996%20OF%2096-04%20(25).pdf

Thank you.

Regards,
Ronald Fey

AE Figures Of Merit

From the “higher plain” wizardry of the aerospace-design “numbers” folks, comes this excellent technique for making complicated choices, in a very quick, straightforward and clear manner.

When faced with a lot of choices (for example, picking a car model from among SUV’s, Sports Cars, Luxury Cars, Hyrbrids etc.), and also, considering a lot of options (such as capability, accessory options, economy, price, etc.), this method quantifies the combined importance, and generates a single number-figure for each of your possilibities.

Therefore, you can size-up the choices side by side (for example, the Prius Hybrid (a small, green, economic vehicle) would score 77%, perhaps, and the Range Rover Super Deluxe (a fictional large, high powered SUV) might score 75% – if, when you set-up the solution, you placed more significance on city fuel economy, and less on 4-wheel-drive / snow-performance.

This method has a broad range of application, across many industries and institutions, and if anyone would be interested in co-authoring a “FOM for Dummies” book or clone, let me know!

Send your email address for both a FREE spreadsheet and .pdf file – showing an FOM example.

Thank you.
Regards, rjf
(ron.bronco.fey@live.com)

United States SEC Regulations

Today, relevant SEC Oil and Gas reporting regulations were downloaded and compiled into a MS Word document.

The set is thought to be fairly complete, however my search was not exhaustive, thus there might be applicable sections not present ( I think the odds here are low that there are other “material” Reg. sections, but the matter is important, so don’t take that for granted, necessarily ).

The definitions portion, as well as examples of reporting forms, and the descriptions of the information to be included, all are informative. The document is available here for Free Download.

Federal Regulations from the SEC, regarding Oil and Gas Reporting:
SEC Regulations
Decision Support

Thank you.
Regards, rjf

PRMS Probability Reserves Computation Spreadsheet

This is Ron  ”Bronco”  Fey.      My other “innovations” blog is at URL: http://www.technologyinnovationproamerica.blogspot.com/

This blog post announces a new, probability-based reserves calculation spreadsheet-version, which has just been released.    The improved user interface, and improved graphics and numeric results, are available now.  

Among the functions of the application, are the following described methods (not the background hydrostatic pressure information/analysis, however):

It is for this reason that reservoir engineers are prepared to spend a great deal of time (and therefore, money) in defining the hydrostatic pressure regime in a new field. A simple way of doing this is to run a series of wireline formation tests5,6 in the exploration well, usually after logging and prior to setting casing, in which pressures are deliberately measured in water bearing sands both above and beneath the hydrocarbon reservoir or reservoirs. The series of pressure measurements at different depths enables the hydrostatic pressure line, equ. (1.6), to be accurately defined in the vicinity of the hydrocarbon accumulation, irrespective of whether the pressure regime is normal or abnormal.

Such tests are repeated in the first few wells drilled in a new field or area until the engineers are quite satisfied that there is an areal uniformity in the hydrostatic pressure. Failure to do this can lead to a significant error in the estimation of the hydrocarbons in place which in turn can result in the formulation of woefully inaccurate field development plans. [emphasis added]
. . .
Finally, with regard to the application of equ. (1.2), the correct figure for the STOIIP will only be obtained if all the parameters in the equation are truly representative of their average values throughout the reservoir. Since it is impossible to obtain such figures it is more common to represent each parameter in the STOIIP equation by a probability distribution rather than a determinate value. For instance, there may be several different geological interpretations of the structure giving a spread in values of the net bulk volume V, which could be expressed as a probability distribution of the value of this parameter.

The STOIIP equation is then evaluated using some statistical calculation procedure, commensurate with the quality of the input data, and the results expressed in terms of a probability distribution of the STOIIP. The advantage of this method is that while a mean value of the STOIIP can be extracted from the final distribution, the results can also be formulated in terms of the uncertainty attached to this figure, expressed, for instance, as a standard deviation about the mean. If the uncertainty is very large it may be necessary to drill an additional well, or wells, to narrow the range before proceeding to develop the field.

L.P. Dake, Fundamentals of Reservoir Engineering, Elsevier Science B.V., 1978, pgs 7, 9.

Contact me for details, and get a head start.

Thank you.  
Regards,   rjf
(ron.bronco.fey@live.com)