Cardium Case Study 6 POR

8/2/2019 Cardium Case Study 6 POR

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www.reconpetro.com 1

Are We Underestimating Our Resources?Increased Original Gas-In-Place (OGIP) as a Result of VolumetricAnalysis of RECON HDDTM Well Logs; Cardium FormationAlberta

Volumetric estimation provides the basis for determining the Original Gas-In-Place (OGIP) ofa prospect prior to flow testing and production. The OGIP determines the feasibility of aproject and gives operators a starting point in order to characterize their prospects in terms ofrisk. Accurate calculations of OGIP give operators the confidence to move forward withdevelopment/investment and the degree of accuracy can have great implications for how aprospect is developed and exploited. The OGIP also has implications on the bookablereserves that a company can report and therefore their access to capital. Traditionally, thedetermination of OGIP is based on standard well log analysis, and the incorporation of coreanalysis and mapping to verify the properties and extent of the prospect.

Based on previous core to log comparison work done by RECON, one can be confident thatHDDTM well logs better represent the true porosity of the rock. Therefore, applying porositycutoffs when doing volumetric interpretation to tight gas reservoirs, such as presented here,which have low effective porosities, is an ideal situation to use HDDTM log derived porositiesin order to ensure better accuracy.

RECONs HDDTM samples at 132 samples per meter, which is nearly four times greater thanindustrys standard (28-40 samples per meter) for high resolution logs, and sixteen timesmore than industry standard (8-10 samples per meter) main pass logs. RECONs standardnon-HDDTM,main pass logging resolution is 33 samples per meter, equivalent to the industrystandard for high resolution logs.

Typical logging speed for industry standard main pass resolution logs is 9 meters per minute.RECON standard main pass logs, which are the equivalent of industry standard highresolution logs, are run at 9 meters per minute (industry high resolution logs are run at 4 to 5meters per minute). In comparison, RECON HDDTM logs are run at ~7 meters per minute.These advantages mean more data for the same amount of rig time, equating to betterreservoir understanding at no additional cost.

RECON Petrotechnologies Ltd. developed the ability to sample at higher rates thanpreviously seen in industry to allow for increased confidence in log derived porosity whencompared to core, better thin bed resolution, and clearer interface boundary definition.

This then results in an increase in volumetric OGIP using HDDTM logs compared to RECONstandard main pass logs and other industry standard main pass logs. The following casestudy highlights the implications of higher sampling rates in order to more accuratelycharacterize the rock and quantify the OGIP. Interpretation was done by hand as well asusing RAW LAS Data files. This in turn leads to the question: Are we underestimating ourresources?


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Regional Geological Setting

The Cardium Formation of Alberta is exposed along the Rocky Mountain Foothills andpresent beneath the Alberta Plains region. It is comprised of a terrigenous, muddy, sandy,and conglomeratic wedge deposited during the Late Cretaceous age. It lies along the

western margin of the Alberta Foreland Basin. In the surface of the plains, the Cardiumformation is encased in marine shales. The sediments were accumulated in muddy andsandy inner and outer shelves, beaches, lagoonal, barrier islands, tidal, estuarine and coastalplains. The deposits alternate between coarse- and fine-grained stages controlled by bothautocyclic and allocyclic processes. The Cardium forms a large stratigraphic trap in itseastern shaleout, producing Canadas largest individual oil field Pembina. Accumulations ofgas and liquids rich gas are consistently reported throughout the depositional area of theFormation. The thickness varies from 0 to over 134 meters throughout the extent.

Volumetric Estimation

Volumetric estimation is based on various geological inputs from core analysis, wireline loginterpretation and geological mapping. It is termed the Geologists Method and is thefundamental starting point for any work with gas-in-place (GIP) and recoverable volumes.Volumetric estimation is the only available means to assess original hydrocarbons-in-place,prior to the acquisition of sufficient pressure and production information, in order to applymaterial balance and/or decline analysis. After pressure and production data have beencollected for a reasonable period of history, volumetric estimation provides a valuable checkon the estimates derived from material balance and decline analysis (Dean, L. 2007).Volumetric estimation is therefore the ideal solution in new field/pool and wildcat wellsituations.

For the purpose of this case study we will be using the equation for OGIP for a typical gasreservoir:

Gas-In-Place Calculation (Imperial): Gas Reservoirs

OGIP (MMCF) = 0.04356 * A * H * * SgBgi

A = Area (Acres)H = Net Pay (ft) = Porosity (fraction)Sg = Gas Saturation (fraction)

Bgi = Initial Gas Volume Factor

Bgi = (Psc * Ti * Zi)(Tsc * Pi)

= 14.65*(Ti+459.67)*Zi(520*Pi)


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Psc = Pressure at Surface (atmospheric = 14.65 psi)Ti = Temperature Initial (Fahrenheit + 459.67 (Rankine))Zi = Initial Compressibility (unitless)Tsc = Temperature at Surface (60 Fahrenheit + 459.67 (Rankine))Pi = Pressure Initial (psi at reservoir)

*All input values are in Imperial

Area (A):Area or Drainage Area is the expected area of drainage for a particular well. In the case oforiginal gas-in-place it may be a particular area for which volumes are being determined,based on a reasonable distance from the wellbore being evaluated. For the purpose of thiscase study, the area is one (1) section or 640 acres. This is based on the heterogeneousnature of the Cardium Sand in the study area.

Net Pay (H):

Net pay is the portion of the reservoir that can be produced at economical rates given aparticular method of completion. Gross pay is the complete interval regardless of cutoffswhereas the net pay is the portion of the gross pay with a particular cutoff applied,determined by core analysis and comparative analysis of similar log signatures fromproductive reservoirs. These are determined based on the relationships between porosityand permeability, as well as water saturation and capillary pressure data from core. Thecutoffs distinguish the portion of a reservoir deemed to be producible from those that aredeemed non-productive. Due to the nature of the completion of this reservoir (perforate thenfrac or horizontal drilling and multi-stage frac), the entire interval from top sand to base sandis recognized as the gross pay interval. Any portion of this zone exceeding 6% porosity cutoffis determined to be producible based on core analysis (to follow).

Porosity ():Porosity values are applied as an average over the entire Net Pay for the zone; in the case ofthis study they are applied as a weighted average over the Net Pay for the entire interval, topsand to base sand, for the portions exceeding the 6% porosity cutoff.

Gas Saturation (Sg):Gas saturation is a function of the water saturation of the reservoir. The reservoir is beingevaluated as a two phase system containing only water and gas for simplicity sake. Gassaturation is determined by the equation:

Sg = (1-Sw)

Historical data of production within the field suggest that water saturations between 25% and35% are reasonable. For the OGIP calculations a mean value of 30% water saturation wasused.


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Initial Gas Volume Factor (Bgi):This factor is used to convert surface measured volumes to reservoir conditions and viceversa. The Bgi is a function of various inputs, many of which are considered constant forevaluation purposes. The three dependent factors are; Ti (Initial Temperature), which isdetermined from well logs and/or static gradients; Pi (Initial Pressure), which is virgin/initial

reservoir pressure as determined by static gradients, build up tests and/or shut in tests; andZi (Initial Compressibility), which is a function of pressure and temperature. All threevariables were confirmed by the Operator for this case study.

Porosity Cutoff Determination

In order to determine porosity cutoffs for the Cardium Sand in the area of study two coreswere evaluated; 00/07-14-067-12W6/0 and 00/04-13-068-10W6/0. Both cores were plottedporosity vs. permeability, one with all points included and one with only points with a Kmaxabove 0.1mD. Each was fitted with an exponential trend line to determine the effectivepermeability to gas porosity cutoff at a Kmax value of 0.1mD.

Figures 1 and 2 are the data points for 7-14 and 4-13 respectively with no Kmax cutoffapplied. The porosity cutoff values attained by extrapolating an exponential line of best fit forthe data points and the corresponding porosity at 0.1mD are 6.8% (7-14) and 6.5% (4-13).The average porosity cutoff for the 2 wells is 6.65%.

Figure 1. Figure 2.

Figures 1 and 2.Permeability vs. Porosity for the 7-14 and 4-13 wells with no Kmax cutoff applied.

Figures 3 and 4 are the data points for 7-14 and 4-13 respectively with a Kmax cutoff of 0.1mD applied. The porosity cutoff values attained by extrapolating an exponential line of bestfit for the data points and the corresponding porosity at 0.1mD are 4.6% (7-14) and 6.5% (4-13). The average porosity cutoff for the 2 wells is 5.55%.

7-14-67-12W6

No Kmax Cutoff

0.001

0.01

0.1

1

10

0.04 0.05 0.06 0.07 0.08 0.09 0.1 0.11 0.12 0.13

Porosity

Kmax(mD)

Kmax

Expon. (Kmax)

4-13-68-10W6

No Kmax Cutoff

0.001

0.01

0.1

1

10

0.04 0.06 0.08 0.1 0.12 0.14

Porosity

Kmax(mD)

Kmax

Expon. (Kmax)


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Figure 3. Figure 4.

Figures 3 and 4.Permeability vs. Porosity for the 7-14 and 4-13 wells with a Kmax cutoff of 0.1 mD applied.

In order to remain conservative when doing the volumetric estimation for the four wells in thecase study a porosity cutoff of 6% was used based on the preceding data.

Volumetrics by Interpretation

Due to the nature of the completion strategy for wells such as those in the examples, thevolumetric estimates are based on the entire interval from top sand to base sand (withinreasonable limits). Given this, all reservoir rock that exceeded the 6% porosity cutoff is

considered pay. The intervals were defined with a top and base. Net pay was measuredalong with the average porosity for each interval. The values were then converted to aweighted average for the well.

Each well was evaluated by hand using both the standard main pass (33 samples per meter)data (1:240 scale stretched over a 1:60 scale) and the HDDTMpass (132 samples per meter)data (1:60 scale). Due to the density of the samples in the main pass data (33 samples permeter) the data needs to be filtered in order to display it at a comparable scale to that ofindustry standard 1:240 logs. This filtering essentially converts the data to a 15 samples permeter data set, still more detailed than industry standard 8-10 samples per meter data. Thepurpose of this is to illustrate, to the best of our ability, what the comparison would be like if

industry standard main pass data was used. Each example shows the intervals chosen aspay (highlighted boxes) and summarizes the volumetric parameters, as well as the top payzone and base pay zone.

The following are the results of by hand log evaluation:

7-14-67-12W6

0.1 Kmax Cutoff

0.001

0.01

0.1

1

10

0.04 0.05 0.06 0.07 0.08 0.09 0.1 0.11 0.12 0.13

Porosity

Kmax(mD)

Kmax

Expon. (Kmax)

4-13-68-10W6

0.1 Kmax Cutoff

0.001

0.01

0.1

1

10

0.04 0.06 0.08 0.1 0.12 0.14

Porosity

Kmax(mD)

Kmax

Expon. (Kmax)


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Gamma Ray

0 150API

SP

-91 9MV

Density Porosity (SS)

0.45 -0.15V/V

Neutron Porosity (SS)

1.05 0.45

0.45 -0.15V/V

PE

0.0 20.0BARNS/E

Shallow Resistivity

0.2 2000OHMM

Medium Resistiivity

0.2 2000OHMM

Deep Resistivity

0.2 2000OHMM

1:48.0MDinM

1115

1116

1117

1118

1119

1120

1121

1122

1123

1124

1125

1126

1127

1128

1129

1130

1131

1132

1133

1134

1135

1136

1137

1138

1139

1140

Net Pay = 12.6m (41ft)

Avg = 9.36

Sw = 30%

Base 1135.9m

Top 1119.9m

Non Reservoir

Gamma Ray

0 150API

SP

-91 9MV


0.45 -0.15V/V


1.05 0.45

0.45 -0.15V/V

PE

0.0 20.0BARNS/E

Shallow Resistivity

0.2 2000OHMM

Medium Resistiivity

0.2 2000OHMM

Deep Resistivity

0.2 2000OHMM

1:48.0MDinM

1115

1116

1117

1118

1119

1120

1121

1122

1123

1124

1125

1126

1127

1128

1129

1130

1131

1132

1133

1134

1135

1136

1137

1138

1139

1140


Avg = 9.36

Sw = 30%

Base 1135.9m

Top 1119.9m

Non Reservoir

Figure 5. 00/09-30-067-09W6/0, RECON Main Pass (33 samples/meter) 1:240 scale stretched over 1:60 scalefor comparison purposes, objective volumetric interpretation.


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Gamma Ray

0 150api

SP

-78 22mv


0.45 -0.15v/v


1.05 0.45

0.45 -0.15v/v

PE

0.0 20.0b/e

Shallow Resistivity

0.2 2000ohmm

Medium Resistiivity

0.2 2000ohmm

Deep Resistivity

0.2 2000ohmm

1:48.0MDinM

1115

1116

1117

1118

1119

1120

1121

1122

1123

1124

1125

1126

1127

1128

1129

1130

1131

1132

1133

1134

1135

1136

1137

1138

1139

1140


Avg = 9.80%

Sw = 30%

Top 1120.3m

Base 1136.1m

Non Reservoir

Gamma Ray

0 150api

SP

-78 22mv


0.45 -0.15v/v


1.05 0.45

0.45 -0.15v/v

PE

0.0 20.0b/e

Shallow Resistivity

0.2 2000ohmm

Medium Resistiivity

0.2 2000ohmm

Deep Resistivity

0.2 2000ohmm

1:48.0MDinM

1115

1116

1117

1118

1119

1120

1121

1122

1123

1124

1125

1126

1127

1128

1129

1130

1131

1132

1133

1134

1135

1136

1137

1138

1139

1140


Avg = 9.80%

Sw = 30%

Top 1120.3m

Base 1136.1m

Non Reservoir

Figure 6. 00/09-30-067-09W6/0, RECON HDD

TM Pass (132 samples/meter) 1:60 scale for comparison

purposes, objective volumetric interpretation.


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Gamma Ray

0 150API

SP

-70 30MV


0.45 -0.15V/V


0.45 -0.15V/V

PE

0.0 20.0BARNS/E

Shallow Resistivity

0.2 2000OHMM

Medium Resistiivity

0.2 2000OHMM

Deep Resistivity

0.2 2000OHMM

1:48.0MDinM

1090

1091

1092

1093

1094

1095

1096

1097

1098

1099

1100

1101

1102

1103

1104

1105

1106

1107

1108

1109

1110

1111

1112

1113

1114

1115


Avg = 8.42%

Sw = 30%

Top 1093.6m

Base 1106.8m

Non Reservoir

Gamma Ray

0 150API

SP

-70 30MV


0.45 -0.15V/V


0.45 -0.15V/V

PE

0.0 20.0BARNS/E

Shallow Resistivity

0.2 2000OHMM

Medium Resistiivity

0.2 2000OHMM

Deep Resistivity

0.2 2000OHMM

1:48.0MDinM

1090

1091

1092

1093

1094

1095

1096

1097

1098

1099

1100

1101

1102

1103

1104

1105

1106

1107

1108

1109

1110

1111

1112

1113

1114

1115


Avg = 8.42%

Sw = 30%

Top 1093.6m

Base 1106.8m

Non Reservoir



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Gamma Ray

0 150api

SP

-68 32mv


0.45 -0.15v/v


1.05 0.45

0.45 -0.15v/v

PE

0.0 20.0b/e

Shallow Resistivity

0.2 2000ohmm

Medium Resistiivity

0.2 2000ohmm

Deep Resistivity

0.2 2000ohmm

1:48.0MDinM

1090

1091

1092

1093

1094

1095

1096

1097

1098

1099

1100

1101

1102

1103

1104

1105

1106

1107

1108

1109

1110

1111

1112

1113

1114

1115

Net Pay =7.3m (24ft)

Avg = 9.12%

Sw = 30%

Non Reservoir

Top 1093.4m

Base 1107.4m

Gamma Ray

0 150api

SP

-68 32mv


0.45 -0.15v/v


1.05 0.45

0.45 -0.15v/v

PE

0.0 20.0b/e

Shallow Resistivity

0.2 2000ohmm

Medium Resistiivity

0.2 2000ohmm

Deep Resistivity

0.2 2000ohmm

1:48.0MDinM

1090

1091

1092

1093

1094

1095

1096

1097

1098

1099

1100

1101

1102

1103

1104

1105

1106

1107

1108

1109

1110

1111

1112

1113

1114

1115

Net Pay =7.3m (24ft)

Avg = 9.12%

Sw = 30%

Non Reservoir

Top 1093.4m

Base 1107.4m





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Gamma Ray

0 150api

150 300

SP

-72 28mv


0.45 -0.15v/v


1.05 0.45

0.45 -0.15v/v

PE

0.0 20.0b/e

Shallow Resistivity

0.2 2000ohmm

Medium Resistiivity

0.2 2000ohmm

Deep Resistivity

0.2 2000ohmm

1:48.0MDinM

1130

1131

1132

1133

1134

1135

1136

1137

1138

1139

1140

1141

1142

1143

1144

1145

1146

1147

1148

1149

1150

1151

1152

1153

1154

1155


Avg = 8.10%

Sw = 30%

Top 1136.5m

Base 1150.6m

Non Reservoir

Gamma Ray

0 150api

150 300

SP

-72 28mv


0.45 -0.15v/v


1.05 0.45

0.45 -0.15v/v

PE

0.0 20.0b/e

Shallow Resistivity

0.2 2000ohmm

Medium Resistiivity

0.2 2000ohmm

Deep Resistivity

0.2 2000ohmm

1:48.0MDinM

1130

1131

1132

1133

1134

1135

1136

1137

1138

1139

1140

1141

1142

1143

1144

1145

1146

1147

1148

1149

1150

1151

1152

1153

1154

1155


Avg = 8.10%

Sw = 30%

Top 1136.5m

Base 1150.6m

Non Reservoir



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Gamma Ray

0 150api

150 300

SP

-76 24mv


0.45 -0.15v/v


1.05 0.45

0.45 -0.15v/v

PE

0.0 20.0b/e

Shallow Resistivity

0.2 2000ohmm

Medium Resistiivity

0.2 2000ohmm

Deep Resistivity

0.2 2000ohmm

1:48.0MDinM

1130

1131

1132

1133

1134

1135

1136

1137

1138

1139

1140

1141

1142

1143

1144

1145

1146

1147

1148

1149

1150

1151

1152

1153

1154

1155

Non Reservoir

Top 1136.3m

Base 1150.5m


Avg = 9.03%

Sw = 30%

Gamma Ray

0 150api

150 300

SP

-76 24mv


0.45 -0.15v/v


1.05 0.45

0.45 -0.15v/v

PE

0.0 20.0b/e

Shallow Resistivity

0.2 2000ohmm

Medium Resistiivity

0.2 2000ohmm

Deep Resistivity

0.2 2000ohmm

1:48.0MDinM

1130

1131

1132

1133

1134

1135

1136

1137

1138

1139

1140

1141

1142

1143

1144

1145

1146

1147

1148

1149

1150

1151

1152

1153

1154

1155

Non Reservoir

Top 1136.3m

Base 1150.5m


Avg = 9.03%

Sw = 30%





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Gamma Ray

0 150api

150 300

SP

-78 22mv


0.45 -0.15v/v


1.05 0.45

0.45 -0.15v/v

PE

0.0 20.0b/e

Shallow Resistivity

0.2 2000ohmm

Medium Resistiivity

0.2 2000ohmm

Deep Resistivity

0.2 2000ohmm

1:48.0MDinM

1210

1211

1212

1213

1214

1215

1216

1217

1218

1219

1220

1221

1222

1223

1224

1225

1226

1227

1228

1229

1230

1231

1232

1233

1234

1235

Net Pay = 16.1m (53

Avg = 8.30%

Sw = 30%

Base 1231.0m

Top 1213.1m

Non Reservoir

Gamma Ray

0 150api

150 300

SP

-78 22mv


0.45 -0.15v/v


1.05 0.45

0.45 -0.15v/v

PE

0.0 20.0b/e

Shallow Resistivity

0.2 2000ohmm

Medium Resistiivity

0.2 2000ohmm

Deep Resistivity

0.2 2000ohmm

1:48.0MDinM

1210

1211

1212

1213

1214

1215

1216

1217

1218

1219

1220

1221

1222

1223

1224

1225

1226

1227

1228

1229

1230

1231

1232

1233

1234

1235

Net Pay = 16.1m (53

Avg = 8.30%

Sw = 30%

Base 1231.0m

Top 1213.1m

Non Reservoir

Figure 11. 00/06-23-067-12W6/0, RECON Main Pass (33 samples/meter) 1:240 scale stretched over 1:60scale for comparison purposes, objective volumetric interpretation.


13/18


Gamma Ray

0 150api

150 300

SP

-74 26mv


0.45 -0.15v/v


1.05 0.45

0.45 -0.15v/v

PE

0.0 20.0b/e

Shallow Resistivity

0.2 2000ohmm

Medium Resistiivity

0.2 2000ohmm

Deep Resistivity

0.2 2000ohmm

1:48.0MDinM

1210

1211

1212

1213

1214

1215

1216

1217

1218

1219

1220

1221

1222

1223

1224

1225

1226

1227

1228

1229

1230

1231

1232

1233

1234

1235


Avg = 9.47%

Sw = 30%

Top 1213.1m

Base 1231.6m

Non Reservoir

Gamma Ray

0 150api

150 300

SP

-74 26mv


0.45 -0.15v/v


1.05 0.45

0.45 -0.15v/v

PE

0.0 20.0b/e

Shallow Resistivity

0.2 2000ohmm

Medium Resistiivity

0.2 2000ohmm

Deep Resistivity

0.2 2000ohmm

1:48.0MDinM

1210

1211

1212

1213

1214

1215

1216

1217

1218

1219

1220

1221

1222

1223

1224

1225

1226

1227

1228

1229

1230

1231

1232

1233

1234

1235


Avg = 9.47%

Sw = 30%

Top 1213.1m

Base 1231.6m

Non Reservoir





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Volumetrics from LAS

In order to eliminate the bias that may be perceived by doing volumetric estimates byhand/interpretation the LAS File Data was used as a check in order to show that in fact theincreased step rate/sampling rate does have an effect on the overall OGIP calculations. Due

to the principles of area under a curve one can show that by decreasing the step rate(increasing sample rate) (Figure 13), which in turn creates more information under the curve,you increase the mathematical certainty of the calculated porosity values, making reserveestimates more accurate.

Figure 13.Decreased step rate (increased sampling rate) translates into more accurate averaging of the areaunder a curve.

The LAS files are the numerical data outputs, tied to depth, for each log curve that was run inthe well logging program. In the case of RECONs main pass logs (33 samples per meter)

there is an output of data points every 0.0303 meters (Step Rate). This means there is areading generated with values for density porosity, neutron porosity, GR,shallow/medium/deep resistivity and so on, every 3.03 cm throughout the run. RECONHDDTM logs (132 samples per meter) generate a data set every 0.0075 meters (Step Rate) orless than every 1 cm throughout the run. Using raw data rather than log interpretation is afeasible means of evaluating reservoirs where cutoffs such as porosity and resistivity arenormally applied, generally in both tight oil and gas reservoirs.

Tops and bases of the intervals were determined from logs and then verified with the LASdata. In the case of the tops, the point at which you begin seeing the data values for theNeutron porosity (NPSS) and the Density porosity (DPSS) approaching, where the DPSS

exceeded the 6% porosity cutoff. In some case the point at which crossover occurred wasdetermined to be the top. The base was the point within the zone of interest where the DPSSfell below the 6% porosity cutoff.

The data was then transferred into an excel spreadsheet where the Net Pay was determinedfor all intervals exceeding the 6% porosity cutoff for both the main pass and HDDTMLAS data,as well the average porosity for the entire Net Pay interval.

RECON HDDTM

132 samples per meter

RECON Main Pass 33 samples per meter


15/18


The following tables summarize the data obtained for each well via this method:

00/09-30-067-09W6/0 00/05-17-068-09W6/0

RECON Standard Log (33sample/meter)

RECON HDDTM

Log (132Samples/meter)


RECON HDDTM


394 Data Points 1575 Data Points 334 Data Points 1246 Data PointsNet Pay (ft) Net Pay (ft)

39 39 33 31

Por Avg Por Avg

9.48% 9.88% 8.00% 9.00%

Figure 14. Reservoir parameters for the 9-30 well. Figure 15. Reservoir parameters for the 5-17 well.

00/16-36-067-10W6/0 00/06-23-067-12W6/0


RECON HDDTM



RECON HDDTM


244 Data Points 928 Data Points 511 Data Points 2027 Data Points

Net Pay (ft) Net Pay (ft)24 23 51 50

Por Avg Por Avg

8.69% 9.16% 8.74% 9.45%

Figure 16. Reservoir parameters for the 16-36 well. Figure 17. Reservoir parameters for the 6-23 well.

OGIP Calculation

In order to complete the gas-in-place calculation there are multiple parameters that need tobe determined that cannot be acquired from the log data. More specifically these factors arethe reservoir pressure, temperature, compressibility factor (Zi), and acreage. For simplicity ofcomparison purposes acreage of 640 acres was assumed in all the calculations. Parameterssuch as temperature and pressure were assigned to the wells in two groups:

Group 1:Wells: 00/09-30-067-09W6/00, 00/16-36-067-10W6/00, 00/05-17-068-09W6/00

Reservoir Pressure: 1217 psi (8390 kpa)Reservoir Temperature: 99oF (37oC)Reservoir Acreage: 640 AcresInitial Compressibility (Zi): 0.81

Group 2:

Well: 00/06-23-067-12W6/00

Reservoir Pressure: 1372 psi (9460 kpa)Reservoir Temperature: 102oF (39oC)Reservoir Acreage: 640 AcresInitial Compressibility (Zi): 0.81


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Each of these parameters was confirmed by the Operator of the wells along with anindependent analysis of available public data. The following table summarizes the results ofthe OGIP calculations for each well. Data is stated for the by hand log interpretations bothmain and HDDTM, as well as the data obtained by LAS file analysis.

Volumetric Analysis

RECON Standard Logs Vs. RECON HDDTMLogs

Log Interpreted Raw LAS Data FileRECON Standard Log

(33 sample/meter)(Filtered)

RECON HDDTM

Log(132 Samples/meter)

RECON Standard Log(33 sample/meter)

RECON HDDTM

Log(132 Samples/meter)

Well Location 00/09-30-067-09W6/0

Net Pay (ft) 41 39 39 39

Porosity (%) 9.36 9.80 9.48 9.88

Sw (%) 30.00 30.00 30.00 30.00

OGIP (MMCF/Sec) 7,149 7,120 6,887 7,178

Well Location 00/16-36-067-10W6/0

Net Pay (ft) 25 24 24 23

Porosity (%) 8.42 9.12 8.69 9.16

Sw (%) 30.00 30.00 30.00 30.00

OGIP (MMCF/Sec) 3,921 4,077 3,885 3,925

Well Location 00/05-17-068-09W6/0

Net Pay (ft) 36 35 33 31

Porosity (%) 8.10 9.03 8.00 9.00

Sw (%) 30.00 30.00 30.00 30.00

OGIP (MMCF/Sec) 5,432 5,888 4,918 5,197

Well Location 00/06-23-067-12W6/0

Net Pay (ft) 53 51 51 50Porosity (%) 8.30 9.47 8.74 9.45

Sw (%) 30.00 30.00 30.00 30.00

OGIP (MMCF/Sec) 9,422 10,344 9,547 10,120

* 6% Porosity Cutoff

*Based on a single well analysis and does not account for lithology changes that may occur across the section of interest.Mapping may alter volumetric assignment to the entire section.

Table 1.Resulting volumetric analysis parameters and calculated OGIP from by hand log interpretation andLAS data file analysis


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For convenience the OGIP numbers have been combined into a single table highlighting theincrease in OGIP calculated via both methods for all four wells used in this case study.

Summary Table

RECON Standard Logs Vs. RECON HDDTM

Logs

Log Interpreted Raw LAS Data File

RECON Standard Log(33 Samples/meter)

(Filtered)

RECON HDDTMLog(132 Samples/meter)

RECON Standard Log(33 Samples/meter)

RECON HDDTMLog(132 Samples/meter)Well Location

Original Gas-In-Place (OGIP) (MMCF/Sec)

PercentIncrease

Original Gas-In-Place (OGIP) (MMCF/Sec)

PercIncre

00/09-30-067-09W6/0 7,149 7,120 0% 6,887 7,178 4%

00/16-36-067-10W6/0 3,921 4,077 4% 3,885 3,925 1%

00/05-17-068-09W6/0 5,432 5,888 8% 4,918 5,197 5%

00/06-23-067-12W6/0 9,422 10,344 9% 9,547 10,120 6%

Average Increase 5% Average Increase 4%

* 6% Porosity Cutoff

*Based on a single well analysis and does not account for lithology changes that may occur across the section of interest. Mapping may altevolumetric assignment to the entire section.

Figure 2. Summary Table of OGIP calculated by hand and with LAS Raw Data. Both methods show an

increase in OGIP from RECON main pass logs to RECONHDD

TM

logs.

Conclusions

The OGIP for these four wells clearly identifies that there is a benefit/relationship to increasedsampling rate, in order to determine more accurate reservoir parameters to incorporate intothe OGIP calculation when doing standard well log volumetric analysis.

The LAS data results are based on what the industry considers to be High Resolution logs(33 samples per meter) and what is now seen as Ultra High Resolution or HDDTM logs (132samples per meter). A significant average increase over the four wells confirms theimportance of more accurate log data.

Although an attempt has been made to represent industry standard data in the by handevaluation (33 samples per meter, filtered on to a 1:240 scale), it can be inferred that if loganalysis were carried out on what industry is deeming to be true main pass log data (i.e. - 8-10 samples per meter) there would be a greater average increase in OGIP than the 5%shown here. It can be suggested that an increase in OGIP of ~10% would not be improbable.However, given the relative inaccuracy of 8-10 samples per meter data, when compared to


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33 and 132 samples per meter data, can one really trust the accuracy of industry main passevaluations?

Work continues in conjunction with this paper to better define the ability of HDDTM log data tocorrelate with porosity values and saturations obtained by standard core testing. Preliminary

results continue to suggest a better correlation between HDD

TM

(132 samples per meter) logdata and core than main pass (33 samples per meter) and core. HDDTMwell logging servicesmore accurately represent actual reservoir parameters with increased confidence.

So the question is: Are You Underestimating Your Resources?

Written By:Jarett Gough, P.Geol. Senior Technical Advisor,Recon Petrotechnologies Ltd.

Acknowedgements:

Shawn Lafleur Caltex Energy Inc. and the Caltex staff and Management for allowingRECON to use and publish the data herein and collaborating on the OGIP calculationparameters.

James Ablett Technical Training Manager, Recon Petrotechnologies Ltd. for coordinatingthe collaboration with Caltex Energy Inc.

Ron Krawchuck Reservoir and Production Services, Recon Petrotechnologies Ltd. forgenerating the figures used.

For more information regarding RECON and their services, as well as case studieshighlighting core vs log porosity comparison between main pass and HDDTM logs please visit:

www.reconpetro.com

References:

Lisa Dean, Fekete Associates Inc. Reservoir Engineering For Geologists, Part 3 Volumetric Estimation, Reservoir Issue 11, December 2007, Canadian Society of PetroleumGeologists

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