Publication History: This article is based on "Log Evaluation Results in the Deep Basin of Alberta" by E. R. (Ross) Crain, P.Eng., first published in 1981. This 2021 webpage version is the copyrighted intellectual property of the author.

Do not copy or distribute in any form without explicit permission.

TiGht Gas ReservoirS- Deep Basin, Alberta
The Alberta Deep Basin gas play was “disvovered in 1973, but the presence of the gas was kmown 10 -15 years earlier because of numerous blowouts and rig fires that occured during the search for oil in the area. I arrived at two such fires in a single week in 1965 with my logging crew, omly to be sent home to “wait on orders”. So we knew the gas was there, but at 2 cents per mcf and no pipelimes, nobody cared. Ten years later, Alherta hooked up homes and farms to the gas and we never looked back.

The material on this page is from a 1981 log evaluation, based on random wells, undertaken to determine the gas-in-place in various formations in the Deep Basin area of Alberta. In addition, comparison of log analysis porosity and water saturation, core porosity and permeability, and in-situ (pressure build-up) flow capacity were made in order to find a relationship between log analysis porosity (or saturation or both) and well performance. Log to core comparisons were adequate, but core to in-situ data failed to produce an acceptable correlation, probably due to fractures not identified on the core. Thus no method was found, during this investigation, to predict well performance from log analysis data alone.


There are at least 11 productive gas intervals spanning Cretaceous theough Mississippian wea reservoirs. The gas is trapped by a relative permeability water block above the gas. See HERE foe more on thos topic.

The results were to be used to help evaluate the resource base in the Deep Basin, and to provide information needed for deliverability and supply cost estimates for the area. This paper discusses only the log analysis methods and results, and does not deal with the supply-cost estimates which were undertaken by another consulting firm.

To accomplish these objectives, we first computed a Log/Mate analysis on all prospective zones in 50 wells selected at random throughout the 200 township area (7200 sq miles). Data from 150 wells (500 zones) in the same area had been studied for other clients and, with their consent, the core versus log calibration data and selected results from most of these wells were incorporated into this study.

Since this data could be from so-called "sweet-spots", the 50 random wells were thought necessary to remove any bias, and thus prevent too optimistic a result. We then summarized, for various cutoffs, on separate data files, the porosity-meters, hydrocarbon meters and net pay-meters for the 50 random wells and the 150 non-random wells. In addition, data from 19 specially selected wells were added to another file, as these wells had extensive pressure build-up data for correlating log response to productivity.

Crossplots of core permeability versus core porosity, and overlays of core porosity and log analysis porosity were made to demonstrate the direct relationship between these properties.

Finally, pore volume, hydrocarbon volume and net pay at various cutoffs were compared to well productivity before and after hydraulic fracturing. No relationship was found to exist between these computed log properties and productivity, even though a good relationship exists between log analysis results and core analysis data. This likely due to varying amounts of natueal fractures.

This demonstrates that, at least for now, there is an insurmountable problem in translating gas-in-place figures into economic terms in tight sands such as these, due mainly to the fact that core permeability or core derived well productivity does not seem to correlate with in-situ data from extended pressure build-up data.

LOG ANALYSIS MODEL and PARAMETERS

The computation model varied with the data type and quality, and in order of preference was the following

    1. shaly-sand density-neutron crossplot method, where hole condition permitted and if logs were available,

    2. sonic log porosity in bad hole or where density and/or neutron data was unavailable.(Some wells were done with this method even when density and neutron log data were available, in order to meet time deadlines),

    3. in zones below the Nordegg,the complex lithology model was used, which is also a density-neutron crossplot method, with the sonic log porosity being used in bad hole.

All three of these methods were correct for the presence of shale in the zone.Shale content was derived from the gamma-ray log response using a linear interpolation technique.  

Various parameters in the interpretation model were varied for each zone. These reflect changes in the shale, matrix rock and fluid properties of the zone. The values can be derived in various ways by comparison with core data. This was done on all wells incorporated in this study, where core data was available.

Fortunately we have found the values to be quite consistent throughout the area, provided logs are normalized between wells. A few wells required shifts to logs to give consistent results. This was kept to a minimum, and wells were discarded from the study if the logs were not good enough, or if they required too much editing and shifting.

The usual parameters for the zones computed in this study are shown in the table below. These were varied from time to time to account for perceived changes in tool response between service companies or for log miscalibration. Standard values of a = 0.62, m = 2.15 and n = 2.00 were used, since no special core studies were available to us.

 

TABLE I: ANALYSIS PARAMETERS

Zone Name

Neutron Log Shale Value

PHINSH%

Density Log Shale Value

PHIDSH%

Matrix Density

RHOMA

gm/cc

(Kg/m3)

Sonic Log Shale Value

DELTSH usec/ft

(usec/m)

Sonic Log Matrix Value

DELTMA

Usec/ft

(usec/m)

Shale Resistivity

RSH

ohm-m

Water Resistivity

RW@FT

ohm-m

Formation Temperature

FT

oF

(oC)

Bad Heart Cardium

Doe Creek Dunvegan

30

0 to 10

Average 2

2.65 (2650)

81 (265)

to

77 (253)

55 (182)

20

0.30

140 (40)

Paddy Cadotte

27

2

2.67 (2670)

77 (253)

53 (174)

20

0.20

122 (50)

Spirit River Falher

27

2

2.69 (2690)

70 (230)

51 (167)

20

0.15

131 (55)

Bluesky Gething

27

0

2.69 (2690)

70 (230)

53 (174)

25

0.10

149 (65)

Cadomin Nikanassin

27

3

2.67 (2670)

66 (215)

51 (167)

20

0.07

167 (75)

Halfway Doig Charlie Lake

15

-6

2.71 (2710)

60 (197)

48 (157)

50

0.06

176 (80)

Belloy Stoddart Debolt

10

-6

2.71 (2710)

60 (197)

48 (157)

50

0.05

185 (85)

Devonian

10

-6

2.71 (2710)

60 (197)

44 (144)

50

0.04

195 (90)


Calculations were made with the author's Log/Mate software package running on HP9835/9845 micro-computers. These systems were sold commercially beteen 1976 and 1986. Typical Log/Mate results, alonq with comparisons to core porosity, are shown below for the Falher, Nikanassin, Gething, Cadotte and Cardium zones. Note the good match beteeen log and core porosity (in Track 1). The integration of core data with the log analysis was vital to the credibility of the project.
    
                       

                                                        

                              To illustrate the log to core comparison in a different way, we plotted core porosity versus log porosity crossplots. The example below is typical for the Falher (same data as Falher depth plot above).
 



 

We have found also that there is a reasonable correlation between core permeability and core porosity, when plotted on semi-log paper (and hence a correlation between log analysis porosity and core permeability). This relationship is shown for a the Falher example wel. The slope of the best fit line is fairly flat, so small changes in porosity are significant.

Flow capacity (permeability-meters) calculated fron core were compared to insitu build-up test flow capacity. The results for a few of the more consistent data points is given below, showing a 10 to 1000 times difference between core and in-situ values.

 

RESULTS OF THE STUDY

Detailed listings of the pore volume, hydrocarbon volume, and net pay at various cutoffs were generated for the 41 random wells, for the 19 special wells, and for the 150 non-random wells. The figures for the random wells at 5% porosity cutoff are summarized below:

 

TABLE 2: SUMMARY OF RESULTS
Formation Name     # Zones          Avg Net

                                                      Pay-Meters

Belly River                       1              8.5

Bad Heart                      15               2.0

Cardium                         35              9.0

Dunvegan                      22              8.2

Shaftesbury                    1             10.6

Paddy/Cadotte             35               6.1

Spirit River                   30             30.1

B1uesky/Gething         31             13.5

Cadomin                       17             36.6

Nikanassin                     7             23.8

Rock Creek/Nordegg     6              5.9

______________________________

TOTAL                         200

AVERAGE PER WELL 4.9        58.8

 

Data from the 150 non-random wells (possibly biased by "sweet-spots") and the 19 special wells (definitely biased by "sweet-spots") produced similar average net pay, average porosity and average water saturation. This suggests that a large number of potential gas zones, with thick net pay intervals, and apparently ubiquitous gas saturation, are present in the Deep Basin of Alberta. This is no longer news, but some interesting points develop:


    1. the log analysis suggests a very high gas-in-place figure based on the net pay, porosity, and water saturation figures - which are confirmed by cores,

    2. "sweet-spots" of high productivity are not easily seen by log analysis,

    3. much of the gas-in-p1ace is in low porosity rock, which suggests very low recovery factors at foreseeable wellhead net-back prices, because of the high cost of delivery of such gas.

 

 

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