Optimizing Location and Perforation Interval for CO2 SequestrationArchana Kumari Bharti Singhla Criti Mahajan Paridhi Khandelwal Sweekriti Dhanpuri

1. Study, monitor & predict plume behavior by alternate ways instead, as satellite studies are expensive and are inapplicable in many areas.2. To predict movement during storage and assess risk.3. To optimize perforation interval to improve trapping and reducing leakage potential

•A reservoir model : Distribution of permeability in the formation•Provides best fit to observed field data (the rates and pressures at which injection and production wells have operated)•Random function: characterized by the ‘ joint conditional probability distribution function’ P(A|B,C),

P(A|BC)= a/(a+bc) (permanence of ratio hypothesis)a= (1-P(A))/ P(A) b=(1-P(A|B))/P(A|B) c=( 1-P(A|C))/P(A|C)A -Reservoir parameter at un-sampled location B- Geological information C- Production/injection data

Steps :1. Initial model using the hard data from well locations and variogram models, with target histogram of the reservoir property2. Perturb to optimizing rd to minimize mismatch b/w actual and simulated data3. Next series of iterations with optimum rd until global convergence4. Porosity transformed to permeability : location of streak

[1] Ashraf M., Lie K. A., Nilsenx H. M., Nordbotten J. M., Skorstady A., (2010) Impact of geological heterogenity on early-stage CO2 plume migration, XVIII International Conference on Water Resources, CMWR[2] Bhowmik S., Srinivasan S., Bryant S. L., (2011) Inferring migration of CO2 plume using injection data and a probabilistic history matching approach, Energy Procedia 4, 3841–3848[3] Kumar N., Bryant S. L., 2008) Semi-analytical model to determine perforation interval for secure CO2 storage in saline aquifers, Energy Procedia 1, 3071-3078[4] Noh, M. Lake, L., Bryant, and Araque-Martinez, A. (2007) Implications of coupling fractional flow and geochemistry for CO2 injection in aquifers, SPEREE 10 (4): 406-411. SPE 89341-PA[5] Burton, M., Kumar, N., Bryant, S.L., 2008. Time –Dependent Injectivity During CO2 Storage in Aquifers, paper SPE 113937 presented at SPE Improved Oil Recovery symposium in Tulsa.[6] Kumar, N., 2008. CO2 Sequestration : Understanding Plume Dynamics and Estimating Risk. MS Thesis, U. of Texas at Austin, Austin, Texas

• Predicting the movement of CO2 plumes during its sequestration is important for mitigating its undesired movement.• Current technologies for monitoring the movement of CO2 plumes beyond the region permitted for storage :

1. Time-lapse seismic (expensive)2. Surface deformation measurements using satellite (inapplicable in many areas)

• Alternate Method: Data from CO2 injection wells (pressures, rates) used to predict the spatial distribution of permeability in an aquifer governing the movement of CO2 plume.

• Using subsurface geology, an initial model of permeability variations is created and then iterations are carried out subject to the bottomholepressures of the injectors to produce a final model of permeability heterogeneity in the aquifer.

• Assumption: The permeability heterogeneity is introduced by high permeability streaks (fractures) superimposed on matrix permeability.

Development of Drying Region : Creation of a dry region surrounding the well divides the aquifer into 3 flow regions : single phase brine, two-phase (aqueous phase and CO2–rich phase), and single phase CO2.

Single Phase Brine Two Phase Region Dry Region Average MobilityDifference in hydrostatic gradient between brine and CO2 : Non-Uniform Flux - Due to difference density between CO2 and brine, there is higher difference in hydrostatic gradient within the wellbore and within the reservoir leading at the upper perforations. So, top perforations initially accept a larger rate of CO2 injection into the aquifer which increases the average mobility near top layers as the drying region penetrates deeper. Inactive Bottom Perforations - The increase in mobility decreases the required bottom-hole pressure for injection. This cause the deeper portions of the well pressure profile and the reservoir fluid pressure profile to approach each other leading to inactive perforations.

Problem Statement

Physical Phenomenon during CO2 injection

Plume Migration Monitoring: Background

Probabilistic History Matching Method

References

Results: Consistent with faster-than-expected arrival of CO2 at that location.Predicts the subsequently observed pressure.

• Aim: Obtaining uniform flux distribution while maintaining injection pressurebelow fracture pressure of rock. Maximize efficiency of CO2 immobilization.

• Optimum perforation interval: Using pressure distribution and flux distributionalong the well length (z). Placing the perforations at bottom of aquifer yields a plume that can move vertically under gravity after injection ends.

• The injection rate varies with depth, the distance travelled by CO2 varies withdepth, thus the average mobility varies with depth. This coupling leads to preferentialflow into the upper perforations and the total injection rate is given by summation of injection rate as a f(z).

Modeling Approach

Results & Conclusions

Fig 1 (Base Case): Perforation interval=500 ft, Q* = 350rBBL/day. є=30 md, µ=0.135, pCO2= 650 kg/m3 & pbrine=1020 kg/m3.Fig 2 shows effect of change of µ of formation(є=100md); Fig 3 shows effect of change in injection rate (Q* = 7000rBBL/day)

Fig on left shows effect of horizontal well length on time to hit top seal. Performance of horizontal well depends on length of perforated horizontal section & vertical permeability of storage formation. Distributing total flow uniformly along horizontal perforated length reduces velocity of plume compared to a vertical well operating at same injection rate; allows more CO2 contact with brine & rock along well length compared to vertical well. Smaller fluid velocity means that gravity force is more influential & flow has greater vertical component, thus contacting less brine/rock in horizontal direction.

Conclusions: 1) The difference in hydrostatic gradient of fluid in well & reservoir coupled with relative permeability effects leads to under utilization of perforations at smaller injection rates. This reduces extent of trapping of CO2 as a residual phase and by dissolution in brine. 2) The perforation interval can be optimized for uniform flux distribution or fracture pressure of aquifer. 3) In horizontal well trapping occurs along well length & transverse direction. For a given rate, there is no benefit unless it is very long.