Algorithms for CO₂ Storage Capacity Estimation: Review and Case Study

Abstract

The estimation of CO₂ storage capacity in deep geologic formations is a pre-requisite for an efficient and safe application of Carbon Capture and Storage (CCS). The evaluation of storage resources for CO₂ geological sequestration is a challenging task and has been tackled using several static algorithms and dynamic methods, on a variety of scales ranging from country to site-specific. The purpose of this study is to present an up-to-date as well as an overall review of the storage capacity algorithms for oil and gas reservoirs, coal seams, and deep saline aquifers, including some worldwide estimation examples. Moreover, a practical application at local scale was also performed for an Italian deep reservoir located in the Po Plain (Northern Italy). The effective storage capacities were obtained applying the commonly established static methods, using both the theoretical and the geocellular volume of the reservoir. Although a conservative approach, this study demonstrates that the selected structure has favorable characteristics for CO₂ geological storage and has the capacity to host the most part of the Po Plain CO₂ emissions for several decades.

Nomenclature and Greek Letters

Nomenclature

A:

Geographical/Trap area of the storage site

B_f :

Formation volume factor: converts oil/gas volume from standard to reservoir conditions (15 °C and 1 bar)

D:

Depth to top of the aquifer

E:

CO₂ storage efficiency factor

E_f :

Sweep efficiency

G:

Acceleration gravity

G_e :

Effective storage capacity by CO₂ mass

${G}_{e- geoc}$ :

Effective storage capacity by CO₂ mass computed by geocelluar volume

G_t :

Theoretical storage capacity by CO₂ mass

G_tech :

Technically accessible storage resource by CO₂ mass

H:

Average gross thickness of the reservoir

H:

Net thickness of the reservoir

K:

Rock permeability

${k_{CO}}_{{}_2r}$ :

CO₂ relative permeability

L_T :

Length of domain for migration model

${m}_{C{O}_2}$ :

CO₂ solubility coefficient. Subscripts oil and water stand for CO₂ solubility in oil and water, respectively

P:

Pressure. Subscripts r and s stand for reservoir and surface conditions; respectively

P_frac :

Fracture pressure

ΔP_max :

Maximum allowed pressure

R_f :

Recovery factor

R_w :

Recovery of reservoir water

${S}_{C{O}_2}$ :

CO₂ saturation within the Volume where CO₂ plume is present

${S}_{C{O}_{2irr}}$ :

Irreducible CO₂ saturation within the Volume where CO₂ plume is present

${S}_{C{O}_{2 trap}}$ :

Trapped CO₂ saturation after flow reversal

S_w :

Water saturation

S_wirr :

Irreducible water saturation

T:

Time

T:

Temperature. Subscripts r and s stand for reservoir and surface conditions; respectively

V_geoc :

Reservoir volume computed by £G geological models

V_w :

Water volume. Subscripts i and p stand for injected and produced; respectively

ΔV_trap :

Rock volume previously saturated with CO₂ that is invaded by water

W:

Width of the well array

X^CO2 :

CO₂ mass fraction in formation water. Subscripts 0 and s stand for initial and CO₂ content at saturation, respectively

Z:

Gas compressibility. Subscripts r and s stand for reservoir and surface conditions; respectively

Greek Letters

B:

Bulk compressibility. Subscripts p and w stand for porous medium and water, respectively

Μ:

Dynamic viscosity. Subscripts CO₂ and w stand for initial CO₂ and water, respectively

${\rho}_{C{O}_2}$ :

Density of CO₂ at reservoir pressure and temperature conditions. Subscripts std indicate standard conditions (15 °C and 1 bar)

ρ _coal :

Bulk coal density

ρ_w :

Density of water at reservoir pressure and temperature conditions. Subscripts 0 and s stand for initial and CO₂ content at saturation, respectively

Φ:

Average porosity of reservoir, subscript e stand for effective porosity