What did we learn from injecting over 300 tons of CO2? 1 of 7 Field Injectivity Testing (Task 7.2): Pressure Production Data and Modeling Objectives Field injectivity testing aimed to develop and understanding of field scale injectivity issues, perform modeling studies of the pressure and production responses, and gather practical data on infrastructure issues. The work began with the selection of two injection sites in depleted oil wells; one in the Clinton sandstone and one in the Copper Ridge dolomite (Field Injectivity Testing Task 7.1). Injection of CO2 was then performed, and pressure-production data analyzed as the wells were shut in and produced. Pressure Production Data and Modeling Approach For the Turner-Doughty #1 well, a radial grid was employed in CMG-IMEX to build numerical models representing the well of interest within its drainage area. The models had 10 layers in the vertical direction, and 10 concentric rings in the radial direction with a geometric grid spacing increasing radially outward from the wellbore. One of the models was a single porosity model, and the other was a fracture-matrix (dual porosity) model. A trial-and-error approach was used to adjust the model parameters (i.e., permeability, relative permeability relations) in order to match: (a) primary production response (i.e., oil and gas rates or equivalently, the corresponding cumulative production volumes), (b) average reservoir pressure prior to CO2 injection, and (c) pressure buildup and falloff during the CO2 injection period. Similarly, for the Brugger Brodzinski #1 well, a radial grid was employed in CMG-IMEX to build numerical models representing the well of interest within its drainage area. The models had 20 layers in the vertical direction, and 10 concentric rings in the radial direction with a geometric grid spacing increasing radially outward from the wellbore. Starting with fluid and reservoir properties from previous tasks, a trial-and-error approach was used to adjust the model parameters (i.e., permeability, relative permeability relations) in order to match: (a) primary production response (i.e., oil and gas rates or equivalently, the corresponding cumulative volumes), (b) average reservoir pressure prior to CO2 injection, and (c) pressure buildup and falloff during the CO2 injection period. Results Turner-Doughty #1 Well. Figure 1 shows the history match with the primary production data for the Turner-Doughty #1 well. The cumulative oil is specified as a constraint (which should be, and is, satisfied by both models). The behavior of gas and water production is shown here for completeness, since no historical data is available.
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What did we learn from injecting over 300 tons of CO2?
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Field Injectivity Testing (Task 7.2):
Pressure Production Data and Modeling
Objectives
Field injectivity testing aimed to develop and understanding of field scale injectivity issues,
perform modeling studies of the pressure and production responses, and gather practical data on
infrastructure issues. The work began with the selection of two injection sites in depleted oil
wells; one in the Clinton sandstone and one in the Copper Ridge dolomite (Field Injectivity
Testing Task 7.1). Injection of CO2 was then performed, and pressure-production data analyzed
as the wells were shut in and produced.
Pressure Production Data and Modeling Approach
For the Turner-Doughty #1 well, a radial grid was employed in CMG-IMEX to build numerical
models representing the well of interest within its drainage area. The models had 10 layers in the
vertical direction, and 10 concentric rings in the radial direction with a geometric grid spacing
increasing radially outward from the wellbore. One of the models was a single porosity model,
and the other was a fracture-matrix (dual porosity) model. A trial-and-error approach was used
to adjust the model parameters (i.e., permeability, relative permeability relations) in order to
match: (a) primary production response (i.e., oil and gas rates or equivalently, the corresponding
cumulative production volumes), (b) average reservoir pressure prior to CO2 injection, and (c)
pressure buildup and falloff during the CO2 injection period.
Similarly, for the Brugger Brodzinski #1 well, a radial grid was employed in CMG-IMEX to
build numerical models representing the well of interest within its drainage area. The models
had 20 layers in the vertical direction, and 10 concentric rings in the radial direction with a
geometric grid spacing increasing radially outward from the wellbore. Starting with fluid and
reservoir properties from previous tasks, a trial-and-error approach was used to adjust the model
parameters (i.e., permeability, relative permeability relations) in order to match: (a) primary
production response (i.e., oil and gas rates or equivalently, the corresponding cumulative
volumes), (b) average reservoir pressure prior to CO2 injection, and (c) pressure buildup and
falloff during the CO2 injection period.
Results
Turner-Doughty #1 Well. Figure 1 shows the history match with the primary production data
for the Turner-Doughty #1 well. The cumulative oil is specified as a constraint (which should
be, and is, satisfied by both models). The behavior of gas and water production is shown here
for completeness, since no historical data is available.
Field Injectivity Testing (Task 7.2): Pressure Production Data and Modeling
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Figure 1. History match to cumulative oil production for the Turner-Doughty #1 well.
Figure 2 shows the predicted average pressure behavior for the Turner-Doughty #1 well during
the primary production period. Although new intermediate pressures between the discovery
pressure and the pre-injection pressures were available, both models are capable of matching the
observed pressure of ~200 psi prevailing prior to the CO2 injection.
Figure 2. History match to cumulative water production and average reservoir pressure for the Turner-
Doughty #1 well.
Field Injectivity Testing (Task 7.2): Pressure Production Data and Modeling
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Figure 3 shows the history match to the pressure buildup during CO2 injection and pressure
falloff during the shut-in (soak) period at the Turner-Doughty #1 injection well. Here, both
models generally match the pressure buildup amplitude, but neither is satisfactory in terms of
matching the final stabilization at ~600 psi.
Figure 3. History match to CO2 injection related pressure buildup and falloff in the Turner-Doughty #1 well.
Finally, Figure 4 shows the increase in oil recovery following CO2 injection over a period of 2
years for the Turner-Doughty #1 well. During this period, 1641 extra barrels are projected to be
produced after injection of 162 tons of CO2, corresponding to a utilization ratio of 10 STB/tons.
Figure 4. Actual (until July 2018) and forecasted oil production (based on CO2 injection in July 2018) for fractured
and un-fractured cases in the Turner-Doughty #1 well.
Field Injectivity Testing (Task 7.2): Pressure Production Data and Modeling
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Brugger Brodzinski #1 Well. Figure 5 shows the history match with the primary production
data for the Brugger Brodzinski #1 well. The cumulative oil (right panel) is specified as a
constraint (which should be, and is, satisfied by all three models). Thus, the history match is
primarily against the cumulative gas production (left panel). Model 3 performs somewhat better
compared to the other 2 models.
Figure 5. History match to cumulative gas and oil production in the Brugger Brodzinski #1 well.
Figure 6 (left panel) shows the history match with respect to cumulative water production for the
Brugger Brodzinski #1 well. Both models 2 and 3 appear to be acceptable. Finally, the
predicted average pressure behavior during the primary production period is shown in Figure 6
(right panel). Although new intermediate pressures between the discovery pressure and the pre-
injection pressures were available, all three models are capable of matching the observed
pressure of ~300 psi prevailing prior to the CO2 injection.
Figure 6. History match to cumulative water production and average reservoir pressure, Brugger Brodzinski #1l.
Field Injectivity Testing (Task 7.2): Pressure Production Data and Modeling
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Figure 7 shows the history match to the pressure buildup during CO2 injection as well as pressure
falloff during the shut-in (soak) period at Brugger Brodzinski #1 injection well. Here, model 3 is
clearly capable of better representing the observed pressure stabilization at ~1100 psi compared
to the other 2 models.
Figure 7. History match to CO2 injection related pressure buildup and falloff in the Brugger Brodzinski #1 well.
Finally, Figure 8 shows the increase in oil recovery following CO2 injection over a period of 2
years. During this period, 477 extra barrels are projected to be produced after injection of 159
tons of CO2, corresponding to a utilization ratio of 3 STB/tons.
Figure 8. Actual and forecasted oil production (based on July 2018 CO2 injection), Brugger Brodzinski #1 well.
Field Injectivity Testing (Task 7.2): Pressure Production Data and Modeling
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Significance
The significance of this work includes the following:
• Analysis of the bottom hole pressure data was useful in determining the injectivity index,
a proxy for permeability at the field-scale. The injectivity index for Copper Ridge
dolomite was found to be approximately two times higher than that for the Clinton
sandstone, which is consistent with results from reservoir characterization (Task 2).
• The pre-test production data and the bottom-hole pressure data from the CO2 injection
test were used to calibrate reservoir models of the region surrounding both wells. The
models were reasonably calibrated by adjusting parameters such as absolute permeability
and relative permeability relationships. The absolute permeability values were compared
those obtained from injectivity-index correlations and were found to agree well. The
relative permeability relationships were compared to those obtained from laboratory
measurements on small-scale core samples (Task 3 Laboratory Testing) and were also
found to generally agree well.
• Modeling results from the pressure and production response suggest that the yield in the
Morrow well will be on the order of 10 stock tank barrels (STB) of oil per ton of CO2
injected, and 3 STB per ton of CO2 for the East Canton well.
For more information, refer to: "CO2 Utilization for Enhanced Oil Recovery and Geologic
Storage in Ohio, Task 7: Field Injectivity Testing Topical Report.," OCDO Grant/Agreement
OER-CDO-D-15-08, Columbus, 2018.
What did we learn from injecting over 300 tons of CO2?