Screening CO2 storage options in The Netherlands

International Journal of Greenhouse Gas Control 4 (2010) 367–380

Screening CO2 storage options in The Netherlands

Andrea Ramı́rez a,*, Saskia Hagedoorn b, Leslie Kramers c, Ton Wildenborg c, Chris Hendriks b

a Utrecht University, Copernicus Institute, Group Science, Technology and Society, Heidelberglaan 2, 3584 CS Utrecht, The Netherlandsb Ecofys Netherlands, B.V., P.O. Box 8408, 3503 RK Utrecht, The Netherlandsc TNO Built Environment and Geosciences, P.O. Box 80015, 3508 TA Utrecht, The Netherlands

A R T I C L E I N F O

Article history:

Received 17 April 2009

Received in revised form 13 October 2009

Accepted 15 October 2009

Available online 27 November 2009

Keywords:

CO2 storage

Screening

Costs

Risks

A B S T R A C T

This paper describes the development and application of a methodology to screen and rank Dutch

reservoirs suitable for long-term large scale CO2 storage. The screening focuses on off- and on-shore

individual aquifers, gas and oil fields. In total 176 storage reservoirs have been taken into consideration:

138 gas fields, 4 oil fields and 34 aquifers, with a total theoretical storage potential of about 3200 Mt CO2.

The reservoirs are screened according to three criteria: potential storage capacity, storage costs and

effort needed to manage risk. Due to the large number of reservoirs, which limits the possibility to use

any pair-wise comparison method (e.g. Multi-Criteria programs such as Bosda or Naiade), a spreadsheet

tool was designed to provide an assessment of each of the criteria through an evaluation of the fields

present in the database and a set of scores provided by a (inter)national panel of experts. The assessment

is sufficiently simple and allows others to review it, re-do it or expand it. The results of the methodology

show that plausible comparisons of prospective sites with limited characterization data are possible.

� 2009 Elsevier Ltd. All rights reserved.

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International Journal of Greenhouse Gas Control

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1. Introduction

Carbon dioxide capture, transport and geological storage (CCS)is increasingly being considered as a significant greenhouse gas(GHG) mitigation option that could allow the continued use offossil fuels while providing time to develop and deploy renewableenergy at large scale. The 2008 Energy Technology Perspectivesreport of the International Energy Agency estimated a CCSpotential of about 20% of global CO2 emissions in 2050 (IEA,2008), with other studies showing similar ranges (e.g. IPCC, 2005).The significant role forecasted for CCS is based on three mainassumptions:

� CO2 capture technology will be available;� The option will be competitive (i.e., cost reductions will be

achieved via learning and market conditions will be present) and,� Sufficient and suitable underground storage capacity will be

available and accessible.

Work on storage capacity evaluation has focused on two mainareas: (i) assessments of total capacities per country or region; (ii)risk assessment and uncertainty analysis of CO2 storage. The firstapproach has resulted in inventories and global atlases, with an

* Corresponding author. Tel.: +31 30 2537639; fax: +31 30 2537601.

E-mail address: [email protected] (A. Ramı́rez).

1750-5836/$ – see front matter � 2009 Elsevier Ltd. All rights reserved.

doi:10.1016/j.ijggc.2009.10.015

emphasis on storage capacities in developed countries. Suchcapacities are being used by modelers and policy makers to set thephysical boundaries for national deployment of CCS. The secondapproach has resulted in the on-going development of methodo-logical frameworks for risk assessments. Almost all frameworksare based on quantitative mathematical modeling (e.g., Wild-enborg et al., 2003; Walton et al., 2004) and only a few semi-quantitative assessments have been developed (e.g., Oldenburg,2008; Bachu, 2002). The fully quantitative methods comprisemajor involvement of many experts, detailed knowledge of localgeology and extensive modeling work. Their applicability for alarge set of potential storage sites is therefore limited unlesssignificant time and effort is committed to the outcome.

Most information used by national policy makers on thepossible role of CCS in a portfolio of mitigation measures is basedon national estimations of CO2 storage capacities that, in mostcases, assume all fields to be available and suitable. Risk factorsassociated with CO2 storage also influence the suitability of areservoir and consequently have an effect on regional and nationalcapacity estimates. It is important to take risk aspects into accountas it will result in more realistic valuations of total CO2 storagepotential. A simplified screening method for comparison of theportfolio of CO2 storage options that uses (publicly) available datawould be helpful. However, until now few efforts have been madeto develop such methods (e.g. Van Egmond, 2006; Meyer et al.,2006). The objective of this study is to develop a methodologicalframework to screen and rank CO2 reservoirs in The Netherlands.

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Fig. 1. Schematic diagram of the methodology used in this research.

Table 1Thresholds used for the pre-screening of CO2 storage options in The Netherlands.

Parameter Threshold

Capacity �4 Mt for gas/oil and �2 Mt for aquifersa

Thickness reservoir >10 m

Depth top reservoir �800 m

Porosity reservoir Aquifers: >10%b

Permeability reservoir Aquifers: an expected permeability of

200 mD or moreb

Thickness seal �10 m. Both simple seals as well as complex

caprock have been taken into accountc

Seal composition Salt, anhydrite, shale or claystones

Reservoir composition Aquifers: sandstones, hydrocarbon fields:

limestone, sandstone, siltstone, carbonates

Initial pressure Overpressure areas excluded

Salt domes Relevant for aquifers. Traps located alongside/

near salt domes/walls have been excluded

because there is a high risk of salt

cementation

a In an early study (TNO, 2007) it is considered that these fields are not

economically feasible for CO2 storage.b Previous studies indicate that aquifer properties for CO2 injection should have a

porosity greater than 10% and a permeability in the order of 200 mD to prevent

extreme overpressures near the injection well. As permeability measurements are

scarcely entered in the national database especially for aquifers, the threshold of

200 mD is not strictly used here. Instead, we have studied lithology descriptions to

find out which aquifers are most likely candidates for CO2 storage. In this sense, the

selected aquifers are expected to have moderate to good permeability and porosity.c Simple caprocks are located directly on top of the aquifer, while sequences of

claystones intercalated with carbonates, thin (<10 m) sandy layers, etc. are

considered complex seals.

A. Ramı́rez et al. / International Journal of Greenhouse Gas Control 4 (2010) 367–380368

Such a methodological framework should enable integration oftheoretical knowledge, expert knowledge and data of the storagelocations in The Netherlands in a consistent systematic andtransparent way.

2. Methodology

This project aims to develop a methodology that allows thescreening of CO2 storage fields in The Netherlands. The screeningof potential locations should deal with qualitative and quanti-tative data and parameters. An initial literature survey pointedout Multi-Criteria Analysis (MCA) as a methodological frame-work that could integrate these two aspects (e.g., Figueira et al.,2005; Scholz and Tietje, 2002; Gough and Shackley, 2006).However, the number of storage options to be compared in thisresearch is large (>170) and limits the possibility to use anyformal pair-wise comparison method (e.g. Multi-Criteria pro-grams such as Bosda (Janssen et al., 2000) or Naiade (Munda,1995)). We have therefore used the main aspects of MCA in alinear aggregation tool. The results are further assessed with asensitivity analysis on weights and a detailed analysis ofuncertainty, especially of the knowledge base. In this research,the screening of storage options is based on a set of three criteria:potential storage capacity, storage costs and effort needed tomanage risk. Furthermore, the results will be analyzed takinginto account availability (before and after 2020).

Fig. 1 shows a schematic diagram of the methodology used andof the flows of information among the different steps. Note thatinputs obtained from consultation rounds with an expert panelplay a central role in the methodology. In the first expertconsultation an (inter)national panel of experts was asked theiropinions on the method, criteria, and indicators selected. Thefeedback of the expert evaluation resulted in changes in theoriginal indicators. The second consultation focused on gatheringthe information needed to aggregate and score the values for thecriteria ‘‘effort needed to manage risk’’. In this consultation roundeach expert was asked to provide scores for categories definedwithin each indicator, to define weights among the indicators sothey could be aggregated in the screening tool and to quantify the

uncertainty in their knowledge base. Results for the latter point arepresented in Hagedoorn et al. (2008).

2.1. Identification of fields

In The Netherlands there are over 500 potential oil and gasfields and structural traps in aquifers that are potentially useful forstoring CO2. The total number of options has been reduced byapplying threshold values (Table 1). This pre-screening resulted in176 storage locations which will be considered in this study. Of the

Table 2Main equations used to calculate potential CO2 storage capacities.

Type Equation Nomenclature

Gas fields SCCO2¼ ðVURðstpÞ=EgÞrCO2

SCCO2¼ CO2 storage capacity (Mt)

VUR(stp) = volume of ultimate gas recovered at standard conditions (15 8C, 1 bar) (109 m3)

Eg = gas expansion factor

rCO2¼ density of CO2 at reservoir conditions (kg/m3)

Oil fields SCCO2¼ ðVoilðstpÞ=BoilÞrCO2

Voil(stp) = volume

Boil = formation volume factor


Aquifers SCCO2¼ Vr N=G EfFrCO2

Vr = bulk aquifer volume (m3)

N/G = net to gross ratio

Ef = efficiency factor (constant = 0.02)

F= porosity


4 The database contains a collection of all kinds of structural traps, like fault

trapping, anticlinal traps, combinations of faults and anticlinal traps, pinchout,

stratigraphic trapping, etc. These are the most common hydrocarbon traps in the

Netherlands. Note that screening potential traps in aquifers regional maps were

used. On this scale only fault bounded traps and anticlinal traps could be identified

as potential storage locations.5 A static geological 3D model in the Netherlands was constructed in Petrel

(software which allows 3D static model building) from depth maps of Super Group

and Group base levels, thickness maps of the sandstone and caprock of interest, and

major or regional faults.6 The value for the storage efficiency factor is still in a subject of (worldwide)

debate. Pore space between the grains of an aquifer is filled with formation water.

When injecting matter into an aquifer, water must be pushed aside to create a

volume for, in this case, CO2. However, this enforced migration of water strongly

depends on the properties of the formation from sub-pore to reservoir scale. The 2%

factor used to compute the storage potential of a structural trap is based on

reservoir simulations performed by TNO taking into account the Dutch geology and

A. Ramı́rez et al. / International Journal of Greenhouse Gas Control 4 (2010) 367–380 369

176 cases 138 are gas fields, 4 are oil fields and 34 are deep salineaquifers.1

2.2. Potential storage capacities

The CO2 storage capacities used in this project have beenestimated based on data and results of previous studies performedby TNO (e.g. TNO, 2002). In those studies, three differentapproaches were followed depending of the type of field(equations used to calculate theoretical storage capacities areshown in Table 2). In the case of depleted gas fields the mainparameters used to estimate the CO2 storage capacity were theultimate produced gas volume, the gas expansion factor and CO2

density. Values for ultimate gas recovery (UR) and historiccumulative production per individual field from before 2003 areconfidential in The Netherlands, making it impossible to estimateUR figures based on historic production data, unless the operatorprovides the data. The volume of recovered gas per field wasestimated from the total future production estimate and the ratiobetween areal extent per field and the total area of gas fields. Thegas expansion factor and CO2 density are based on depthdependent relations (TNO, 2007).

The main parameters to determine the CO2 storage capacity of adepleted oil field are the ultimate oil recovery volume, theformation volume factor2 and the CO2 density at reservoirconditions. For the calculations, it has been assumed that theamount of CO2 stored in the reservoir after enhanced oil recovery isapproximately 30% of the oil initially in place. Since the ultimaterecovery of most oil fields is in the order of 30–35%, the storagecapacity can be approximated by the ultimate reserves. Further-more, given the limited amount of oil fields meeting our criteria onminimum storage capacity (at least 4 Mt) and the relatively smallstorage capacity represented by those oil fields, CO2 density atreservoir conditions is set at 0.70 t/m3 and the formation volumefactor at 1.2. The possible effects of water invasion are notaccounted for in the storage capacity calculations of hydrocarbonfields.3

The assessment of storage capacity in aquifers focused onsandstones of Permian, Triassic, Upper Jurassic and Lower

1 The gas field ‘‘Slocheteren’’ with an estimated potential capacity of 7 Gt is

excluded because according to its operators it will not be available for storage

before 2050.2 The formation volume factor brings the oil volume from standard conditions to

in situ conditions.3 The subsurface of the Netherlands is heavily faulted and production from gas

and oil fields show that depletion is mainly the result of the reduction of pressure.

Assuming that no water (or aquifer) support occurs seems valid as 85–90% of the

Dutch fields are not water (or aquifer) supported.

Cretaceous age. Sandstone members, with small lateral extensionsand limited local deposition, were not included in the assessment.In this study only structural traps are accounted for. This includes4-way dip closures (anticline), compartments like horst andgrabens, or dip-closures comparable to structural gas/oil traps.4

The areal extent of a potential structure is determined from thelocation of spill points from cross sections and elevation contourlines. Aquifer thickness is obtained from well data when present or,alternatively, from extrapolated thicknesses from a 3D model.5

Volumes are calculated by multiplying the areal extent with theaquifer thickness, assuming an average thickness based on welldata or extrapolated thicknesses from the model. For the efficiencyfactor it was chosen to use a value of 2%.6 This is an assumedaverage value for structures in the faulted subsurface of TheNetherlands where the CO2 injection, besides the size of theconnected aquifer, depends on the water and rock compressibility.Average porosities and permeabilities of the aquifer weredetermined from well data on the specific stratigraphic unitwithin a 20–40 km radius from the structure midpoint. Note thatthis approach strongly depends on the availability of plug datawithin the radius and on which level a plug has been taken in thelithology.

reservoir characteristics. Collected data from Dutch gas and oil fields indicate that

many faults in the subsurface are sealing. Exploration maps from producing fields

show that the production from most gas and oil fields ceases as a result of pressure

depletion instead of water invasion. This holds for 85–90% of the existing fields.

Assuming that this is applicable for the injection of CO2 in aquifer traps, the

injection of CO2 into a structural trap can be compared with injecting into a closed

container, resulting in lower efficiency factors (e.g., 0.5–1%). It is likely however that

the trap is hydraulically connected to some (limited) part of the aquifer and

therefore pore water can ‘‘escape’’ allowing the storage efficiency to increase to 2%,

according to reservoir calculations. The 2% is an average value for a trap that is in

pressure communication with a large aquifer.

Table 4Average CO2 injection rate of hydrocarbon fields and saline aquifers per stratigraphic unit, in Mt/y per well.

Formation Hydrocarbon field Saline aquifer

Lower Cretaceous Group Vlieland Sandstone Fm 1 0.5

Lower Germanic Trias Group Lower Buntsandstein Fm 0.4 0.2

Niedersachsen Group Friese front Fm (sandstone members) 0.4 0.2

Upper Rotliegend Group Zechstein Fm (carbonate members) 0.2 0.1

Slochteren Fm (sandstone members) 1 0.5

Limburg Group 0.4 0.2

Table 3Cost figures used in this study.

Hydrocarbon fields onshore Hydrocarbon fields offshore Aquifers onshore Aquifers offshore

Drilling costs per new well (euro/m) 2750 (depth<3000 m)

3980 (depth>3000 m)

3830 (depth<3000 m)

5890 (depth>3000 m)

2750 (depth<3000 m)

3980 (depth>3000 m)

3830 (depth<3000 m)

5890 (depth>3000 m)

Cost of reusing an existing well (Meuro) 1 2 – –

Site development costs (Meuro)a 3 3 24 24

Surface facilities (Meuro)b 1.5 15 1.5 61

Monitoring costs (Meuro) 1 1 1.5 1.5

O & M costs (% investment, cost per year) 5 5 5 5

a Aquifer site development costs are higher than those of hydrocarbon fields due to the exploration costs. A main reason is that data on the geological structure and

reservoir properties of hydrocarbon fields are available, but are scarce for aquifers.b The surface facility costs for offshore aquifers are four times higher than those for offshore hydrocarbon fields because there are no platforms that can be reused.


2.3. Storage costs

Table 3 shows an overview of the cost values used in this study.Site characterization and development include investigation costs(geo-characterization), preparation of drilling site and equipment,environmental impact assessments, engineering, licensing, andlease costs. The drilling costs depend on the number of wellsneeded, hence on the injection rates per well, possibility to useexisting wells and project lifetime. Injection rates are site-dependent and as data are not available for each site, averageinjection rates were used that depend on the stratigraphic unit(Table 4). Drilling costs also depend on the depth and thickness ofthe reservoir. The costs of a well increase linearly with length ofdrilling up to a depth of about 3 km.7 After 3 km, costs increaseexponentially with depth. Therefore, drilling costs are representedby two segments (<3000 and>3000 m). For simplicity the relationbetween costs and depth in each segment is taken as linear. This ispartly justified because most reservoirs in The Netherlands areshallower than 4 km. Furthermore, it is assumed that a part of thecurrent production wells can be used for CO2 injection. The actualpercentage of reusable wells depends very much on site-specificfactors. Based on a recent study (Van der Velde et al., 2008), it isassumed that two-thirds of the existing wells that are still in usetoday could be reused for CO2 injection and that wells that havealready been plugged and abandoned already cannot be reused.

To account for price changes since the publication of the studiesused as sources of information, prices have been adapted using theUpstream Capital Cost Index (UCCI). Clearly, the costs as displayedin this study are rough estimates. They should mainly be regardedas relative numbers, distinguishing between various storagelocations instead of absolute numbers.

2.4. Effort needed to manage risk

This third indicator is a semi-quantitative proxy of the effortneeded (material and personnel resources) to develop a safe andeffective storage site. This means that in this research, we aim to

7 Directional drilling is not taken into account, because this parameter is very

site-specific and because it would make no distinction between different storage

options.

quantify the effort needed to manage risk, but not quantify the riskas such. Quantifying risk requires that both the cause and theeffects of a possible event are assessed (risk = probability of anevent � impact). The effort needed to manage risk, as defined here,focuses on reducing the likelihood of the hazardous eventoccurring and does not include measures needed to avoid orminimize escalation of the event into a larger consequence. Forexample, the presence of a large number of relatively old wellsimplies that more management effort will need to be done toincrease the certainty of safe storage of CO2, since old wellsrepresent a potential leakage path. Selecting reservoirs with theless possible number of old wells therefore reduces the effortneeded to manage risk.

Furthermore, in this study CO2 leakage is considered the mainrisk of CO2 storage in terms of likelihood of occurrence,magnitude, and impact. Therefore the effort needed to managerisk in this study focuses on managing/reducing CO2 leakage. CO2

leakage can occur in various ways. CO2 can migrate through thereservoir to areas were caprock is absent or weak. At places wherethe cap rock is not sufficiently sealing, CO2 can leak through theseal, either through the upper or lower bounding seal. Whenentering geological formations outside the storage reservoir, it ispossible that the CO2 will be trapped by secondary seals, or thatthe rate of migration through the outside geological formations isso slow that CO2 storage is effectively permanent. A larger effort isneeded to manage risk of leakage when there are pathwaysthrough which CO2 can reach the surface. Earlier studies haveshown that those pathways are related to faults and fractures,wells and insufficiently sealing cap rock (e.g., Benson et al., 2002;Damen et al., 2006; Holloway, 1997; Tsang et al., 2007). Aliterature survey and consultation with the expert panel resultedin a selection of five leakage paths and twelve indicators that willbe used here to rank potential storage sites (Table 5). The rationalebehind the selection of each indicator and main methodologicalaspects for their determination are highlighted in the rest of thissection.

2.4.1. Category: faults. Indicators: fault displacement, number of

faults

Many gas and oil reservoirs and potential aquifer traps in TheNetherlands are bound or transected by one or more faults with a

Fig. 2. Example of the spreadsheet used in the consultation to experts to gather scoring values.


throw of 50 m or more (defined here as major faults). These faultsmay extend upwards to younger formations at shallow depth orrock towards the surface or to permeable layers in the overburden.Faults transecting geologically young formations are expected topose a higher risk than faults transecting only older formations.The Netherlands is almost completely covered by Miocene andyounger sedimentary rock, making the presence of a fault in theseyoung sediments an important risk factor.

TNO has mapped the main geological formations and faults ofThe Netherlands on a regional scale based on 2D and 3D seismicdata. For each geological formation (Permian, Zechstein, Triassic,Jurassic, Lower and Upper Cretaceous, Tertiary and Base

Table 5Indicators and paths used to screen storage options according to the effort needed

to manage risk of leakage.

Leakage path Indicators used

Leakage through faults Fault displacement in or above reservoir

Number of major faults in or above reservoir

Leakage because of natural

(or induced) seismicity

Seismicity zone

Leakage through wells Wells abandoned before 1967

Wells abandoned between 1967 and 1976

Wells abandoned after 1976

Wells not abandoned

Accessibility of wells

Leakage through the seal Thickness of primary seal

Seal composition

Proven sealing capability

Leakage through the

overburden

Reservoir depth

Miocene) group fault maps have been compiled.8 By plottingall fault maps and outlines of hydrocarbon reservoirs andaquifers on top of each other, fault displacement can bevisualized.9 With this approach it is possible to quantify thenumber of (major) faults that confine a potential storage site anddetermine to which formation a fault extends. The number ofmajor faults per storage field is considered therefore anindicator of the effort needed for risk management e.g.,characterization, pressure tests. It is important to note thatoffshore faults are currently less well mapped and therefore anunderestimation of the number of offshore faults is possible.

2.4.2. Category: natural seismicity. Indicator: seismicity type

Together with fault maps, well data and exploration maps,the onshore Netherlands has been subdivided in ‘‘stable,’’‘‘slightly unstable,’’ and ‘‘unstable’’ tectonic zones. Tectonicallyunstable regions increase the effort needed to manage risk. Inthe case that there is evidence of several faults transectingPleistocene rocks, a zone is defined as slightly unstable. A zonewith more recent seismic activity is classified as unstable. Azone is stable when seismic activity has not occurred in thePleistocene. A similar, but somewhat less detailed approach was

8 Fault maps show faults with a throw of 50 m or more. Faults with a throw of less

than 50 m are not mapped and for this reason not taken into account in our

database. When the throw of a fault is large enough (e.g. larger than the total

thickness of the cap rock) the storage reservoir could be truncated against one or

more porous layer(s) in the overburden, posing a relatively larger risk of leakage. It

should be noted, however, that faults with less throw could still pose a hazard as

they could act as pathways for gas/fluids to migrate, for instance through the cap

rock. It strongly depends on whether a fault is impermeable.9 Faults with a displacement of at least 50 m (visible on seismic reflections lines)

were mapped. When displacement decreases (at the tip of a fault) it may not be

visible any more on seismics. In these cases, we extrapolated the interpret fault

lines to the next horizon.


performed for this study to take offshore seismicity intoaccount, since this data were not included in the primarydatabase. In order to do so we took into account mapped faults,literature review, seismicity measures and knowledge fromexperts from the Dutch National Center for Weather, Climateand Seismology (KNMI) and measured seismicity. The resultsshowed that the Dutch North Sea area is a fairly stable seismicarea with the exception of an area known as the Dogger Bank,which is marked as unstable (in 1930 an earthquake occurredhere with a magnitude of 6.0 on the Richter scale).

Fig. 3. (A) Map of potential storage locations by CO2 capacity of storage, ty

2.4.3. Category: wells. Indicators: wells drilled before 1967, between

1967 and 1976, and after 1976, well status, well accessibility

Several wells may have been drilled in gas and oil fields forexploration appraisal, water injection, or production. Some ofthese wells are abandoned. Degradation of cement plugs orinadequate plugging of abandoned wells may pose a risk of CO2

leakage. In The Netherlands legislation on cementing and pluggingof wells was not in place before 1967; thus the degradation risk isassumed to be higher for wells drilled and abandoned before 1967.The legislation enforced in 1967 was amended in 1976, which

pe of field. (B) Frequency distribution of potential storage capacities.

Fig. 3. (Continued ).


again led to higher quality plugs and cementation. In this study, itis assumed that a well drilled for exploration or production shouldfulfill the regulations defined at that moment. Assuming that thewell has not been worked over since, the completion date is used togroup the wells according to the periods when legislation changed(1967, 1967–1976 and after 1976). To obtain the number of wellsby period that are abandoned and the number of wells that are stillin use (wells not abandoned) a compilation had to be made of threedifferent types of data namely:

� End depth. To select the wells that pierce a reservoir or aquifer,field outlines from GIS maps compiled by TNO in the past andcoordinates of the end point of a well from the existing (DINO)database10 were used. It was decided to use the end point of awell as subsurface coordinates may be located outside a fieldoutline, which does not necessarily mean that a well does notpierce a reservoir (deviate drilling).� Age of the well. The project was faced with a practical problem as

specific information on the technical status of the well is notavailable in a useful form. Gathering data of the exactabandonment date, possible work over of a well and totalcompletion (casing and cemented) would take significant effortas it concerns about 5000 well reports, which is beyond the scopeof the current project. However, as the completion date of a wellis available from the DINO database, this date is used instead asan indication for the abandonment date of a well. The maindrawback of this assumption is that it does not take into accountpossible degradation of the cement after completion, i.e., eventhough a well could have been completed in a time when highstandards were required, a combination of chemical and geo-mechanical effects can degrade the cement so that, from theperspective of leakage potential, the well would pose a risksimilar to a well completed decades earlier.� Well status. A well can consist of several boreholes. Based on

the end depth of the primary well or sidetrack and the topdepth of the reservoir, each part of the well system isevaluated. Wells that have the status closed, suspended,

10 DINO stands for Data and Information on the Dutch Subsurface. For more

information see: http://www.dinoloket.nl/en/DINOLoket.html.11 The NLOG website (http://www.nlog.nl/nl/home/NLOGPortal.html) provides

information about oil and gas exploration and production in the Netherlands and

the Dutch sector of the North Sea continental shelf.12 In the Netherlands, when data is delivered by an oil or gas company the end

result of a well must be clearly stated. In case a well is drilled into a reservoir that

contains oil or gas, but is not economically valuable, a ‘gas shows’ or ‘oil shows’

status is assigned to it. These ones are not included in the category ‘dry’.

producing, or water injection are considered to be accessibleand can be worked over before CO2 is injected into a reservoir.Wells with status Plugged and Abandoned (PAA) and FAS(failure and sidetracks) have been plugged with cement. Thesewells can potentially function as a bypass to the surface in casecement plugs and casings have been disintegrated or corrodedover time. When a technical failure occurs part of a well willbe plugged and a sidetrack can be drilled. It is possible that thesidetrack also fails and a new sidetrack will be drilled. When awell with a status PAA or FAS ends in the overburden (i.e.,depth less than cap rock) it is not considered a risk for leakagein this study. When there are indications that a well or one ofits sidetracks or both, are drilled in the caprock (but notnecessarily in the reservoir itself) it is considered a potentialrisk. Hence, the number of wells considered equals the numberof well sections drilled through the caprock and reservoir. Datafrom wells with construction year more recent than 2003 arestill confidential. These wells have the status ‘‘unknown’’. It isassumed that these wells are used for production and are stillaccessible. In case well status is classified as unknown for awell older than 2003 the NLOG-website11 and productionplans were consulted. In the event that no data were availablefor a well, which was completed before 2003 and could not betraced by any other means, the well was assumed to beabandoned. Wells near a hydrocarbon field that have a status‘‘Dry’’ were not considered.12 It is assumed that these wellsections missed the gas or oil reservoir.

The accessibility of wells was determined by plotting theoutlines of hydrocarbon fields, well data, and a topographic map ofThe Netherlands. Each field is quantitatively evaluated based onthe number of wells that are located in an urban or rural area. Ingeneral, offshore abandoned wells are harder to locate andtherefore more difficult to access, as they are often covered bysediments. Onshore abandoned wells may also be hard to accessdue to, for instance, buildings in urban areas. For onshore fields,wells in a populated area, such as a city, were classified as urban.Wells that are located in open areas (national parks, agriculturalland) were classified as rural.

2.4.4. Category: caprock. Indicators: caprock thickness, caprock

composition, proven sealing capability

Gas and oil reservoirs in The Netherlands are mostly trapped bya caprock at least 10 m thick. CO2 can leak through the caprock, forexample through fractures. The effort needed to manage risk isreduced when the cap rock is thicker. For most fields, productionplans were used to find out which geological members act as seals.When a production plan was not available the first geologicalmember on top of the reservoir rock was considered as caprock.Gas fields are predominantly fault-confined, i.e., gas is trapped byfaults or lateral seals. We considered only top seals, becauselateral seals of a reservoir are not reported in production plans.However, lateral seals have commonly the same composition asthe top seal.

Besides thickness, sealing performance depends on perme-ability of the rock, which is related to its composition. Caprock

composition is determined from production plans and stratigraphydescriptions. In our database a caprock is classified as salt, shale,13

claystone, anhydrite, or marl. As explained before, the caprock can

13 It is necessary to elaborate on the definition of shale used in our database. In the

petroleum industry, shale is defined as a rock member that is composed of sandy silt

and clay (sandy or silty clay). In geology, shale is a fine-grained sedimentary rock

whose original constituents were clay minerals or muds and has hardened due to

(heavy) compaction. By this latter definition shale is considered to have better

sealing properties than claystone, which is less compacted. In this study we used

the geology definition.

http://www.nlog.nl/nl/home/NLOGPortal.html

http://www.nlog.nl/nl/home/NLOGPortal.html


also be a mixture of these components. Due to the regional scaleinventory in this study, homogeneity of the rocks cannot be provenexplicitly. This means that when the caprock is a mixture ofcomponents, the composition in the database refers to thecomponent most present. The risk management effort decreaseswhen the composition of the seal contains on average rocks whichare more impermeable. Sandstone, siltstone, carbonate/limestoneand dolomite are not regarded as a seal at all. Finally, the indicatorproven sealing capability is based on the type of storage location and

Fig. 4. (A) Map of potential storage locations by CO2 costs of storage an

the evidence of having trapped a gas or fluid before. The followingclassification has been used: field evidence of gas; field evidence ofoil; no field evidence. Former gas fields have proven that thesestructures can sufficiently trap gas. Oil fields on the other handhave proven to trap a viscous fluid, but not necessarily gas, whichincreases the risk management effort. Structures that do notcontain any hydrocarbon have no proof of the ability to trap CO2.This is also the case for aquifers.

d type of field. (B) Frequency distribution of potential storage cots.

Table 6Average weights (over the experts) used in this study.

Leakage path Indicators Average

weight (%)

Leakage through faults Fault displacement in or above

reservoir

12

Number of major faults 7

Leakage because of natural

(or induced) seismicity

Seismicity zone 6

Leakage through wells Wells abandoned before 1967 12

Wells abandoned between 1967

and 1976

10

Wells abandoned after 1976 9

Wells not abandoned 7

Accessibility of wells 10

Leakage through the seal Seal thickness 7

Seal composition 8

Proven sealing capability 7

Leakage through the

overburden

Reservoir depth 5



2.4.5. Category: reservoir depth. Indicator: reservoir depth

Reservoir depth, from the top of the reservoir to the surface(overburden thickness), is considered an indicator of the presenceof secondary seals above the storage reservoir. A typical over-burden in The Netherlands consists of an alteration of aquifers andaquitards. Aquitards could serve as a secondary seal. Theoverburden may reduce the risk when unexpected leakage throughthe top seal or a fault occurs. Impermeable rock in the overburdenmay block or slow down the upward migration of CO2. When CO2 issufficiently slowed down by impermeable layers in the over-burden, mineral or solubility trapping may lower the likelihood ofCO2 leakage to the surface. From the stratigraphy data that werecollected to determine the reservoir and caprock thickness, thetotal average overburden thickness was determined.

2.4.6. Additional data

� Reservoir thickness. Reservoir thickness was not classified as anindicator, but is used for the computation of costs as itdetermines the length of a well. The reservoir thickness enteredinto the database states the gross thickness because the netthickness is unknown for most hydrocarbon fields. Based on thestratigraphy from well interpretations the true vertical thicknessof a reservoir rock can be determined. When several wells aredrilled in a reservoir the average thickness was computed.� Estimated year of depletion. These data are collected from the

production plans. For this exercise the most recent plans wereused (dating from 2003 to 2005). The estimated depletion year ofa hydrocarbon field depends on, for instance, the oil or gas price,unexpected production of more or less gas or oil, and geologicaleffects that may force production to stop (e.g., production ofundesirable formation water) and may result in a revision of thedepletion year in future reports.

2.5. Development of the screening tool

To develop a relative ranking of potential storage options, it isnecessary to aggregate and score the values provided by thedifferent criteria and indicators. The output for the criteriastorage capacity and costs per storage field will consist of twovalues expressed in Mt and euro/t CO2, respectively. Ranking theoptions according to storage capacity or costs is thereforestraightforward. The criterion effort needed to manage risk, onthe other hand, is made up of qualitative and quantitativeindicators. Each indicator has been divided into categories. Thecategories are set in quantitative (e.g. categories for tectonicseismic risk are >7, 6–7, 4–6, 2–4, <2) or in qualitative terms(e.g. categories for the primary seal composition are Carbonate,Anhydrite, Clay, Shale, Halite). To obtain a ranking of the

reservoirs it is necessary to translate the categories into scores.These scores reflect the relative importance of the categorieswithin a given indicator. Then, in a second step, the scores of thedifferent indicators for each field are summed up into a uniquevalue. Since all indicators may not be equally important, it isnecessary to assign weights that reflect the relative importanceof the different indicators in terms of risk management effort. Asecond consultation with a (inter)national panel of eight expertswas performed to obtain the scoring and weighting values. Theconsultation made use of a spreadsheet tool containing threetypes of entries: scoring categories, evaluation of the knowledgebase and weights for the indicators. As an example Fig. 2 showshow data were gathered in the first entry type. The inputgenerated in the tool is then used to calculate an average scoreper site. The average weights used to obtain the average scorefor the criterion are shown in Table 6. Note that the expertsconsidered the relative importance of the indicators to be at thesame level. The basic calculation is a simple linear aggregationusing the scores and weights between categories and indicators.The resulting scores per site from the assessment are repre-sentative for the relative scoring and do not indicate an absolutesite performance.

3. Results

Potential storage capacity. The total potential capacity of CO2

storage in The Netherlands is calculated at 3.2 Gt (the Slochterengas field which has a potential of around 7 Gt is not included sinceit is not expected to be available for CO2 storage before 2050). Fig. 3shows the screening of the fields according to capacity.

The results show that about 52% of the storage locations(accounting for roughly 20% of the total capacity) is composed ofrelatively small fields (<10 Mt). Fields with larger capacities aregas reservoirs, while oil fields and aquifers have lower capacities.However, the methodology used to calculate storage capacities ofdeep aquifers is considered preliminary. Since there was nocommercial interest in these fields until a few years ago, the dataavailable are limited. Several projects in The Netherlands are beingcarried out to address storage capacity estimations, and it isexpected that better data and approaches for calculation of storagecapacities will be made available in the next 2 years.

In terms of time availability, 70% of the storage locations willbecome available before 2020, representing 74% of the total


storage capacity. Roughly half of those storage locations arealready available (before 2010); these fields represent roughly 25%of the total storage capacity. Two-thirds of the storage locationsthat are available before 2010 are fields smaller than 10 Mt, whichexplains the difference between the amount of storage locationsand storage capacity of the ‘‘early fields’’.

CO2 storage costs. Fig. 4 shows the screening by location and afrequency distribution according to the costs of CO2 storage.Around 39% of the fields (representing 68% of the total potentialstorage capacity) have estimated storage costs lower than 3 s

Fig. 5. (A) Screening of potential storage locations by effort ne

per tonne of CO2. These fields are mainly onshore gas fields(about 70%). Most offshore gas fields show prices in the rangesof 3–14 s per tonne of CO2. Aquifers on the other hand show thehighest prices (17–107 s per tonne of CO2), being located at theright tail of the histogram in Fig. 4B. This is not surprising sincestoring CO2 in these fields will imply not only that completeseismic studies have to be done from scratch but also that thereis not any infrastructure that can be reused (e.g., wells orplatforms). It is important to point out that less than 10% of thefields that become available before 2010 have estimated costs of

eded to manage risk. (B) Frequency distribution of scores.



lower than 3 s per tonne of CO2. The storage locations thatbecome available before 2020 have a higher price range becausethese include most of the aquifers. The percentage of storagelocations with estimated costs of less than 3 s per tonne of CO2

increases to 25% when storage locations are considered thatbecome available before 2020.

Effort needed to manage risk. For this criterion the results arepresented according to categories, instead of scores, as they aremore appropriate given the character of the data and the scores.14

The three categories used are (the average highest score was 94and the lowest 26):� Category A: composed of fields with the highest scores (�82).

These fields relatively require the least effort to manage risk. Itcorresponds to the third interquartile of the sample.� Category B: intermediate.� Category C: composed of fields with the lowest scores (<70). It

corresponds to the first interquartile of the sample.

The results (see Figs. 5 and 6) indicate that:

� 43 fields score in Category A. These are gas fields representing apotential storage capacity of 541 Mt (about 17% of the totalpotential capacity). 54% of the total capacity in this category ismade up of fields with potential storage capacities smaller than15 Mt (30% are smaller than 10 Mt, though no fields have acapacity lower than 5 Mt). Larger fields (e.g.,>25 Mt) account foronly 16% of the total capacity. Of the total potential capacity,about 60% is available before 2020. In terms of location (onshorevs. offshore), 60% of the fields located in this category areonshore.� Most fields (83) are found in category B. This category is

composed by a mix of gas fields, oil and some aquifers. Thepotential storage capacity amounts to 1837 Mt (58% of the totalpotential capacity). In this category larger fields (>40 Mt)account for about 40% of the total capacity. 68% of the capacityin this category will be available before 2020.� The rest of the fields (50) are found in category C. Their potential

storage capacity amounts to 801 Mt. 45% of the fields in thiscategory have categories larger than 40 Mt. Of the 801 Mt, 96%

14 Given the current assumptions used, the uncertainty in the data and in the

knowledge base, it cannot be stated that a field located in the ranking position as 24

is indeed better than field located at position 25 or worse than field located at

number 23. What can be assured is that fields in positions 23, 24 or 25 require fewer

efforts to manage risks than those in positions 100, 160 or 173.

will be available before 2020. It is important to highlight thatmost aquifers are located in this category (about 83%), the rest islocated in category B.

The results can also be analyzed by looking at the categories andthe costs of storage. Frequency distributions of the costs bycategory are depicted in Fig. 7. Note that the width of thehistograms increases from category A to C. Although the costs, ascalculated in this study, do not account for the costs that wouldhave to be made in order to minimize risk of leakage (which arelarger for category C than A), they do reflect (some of) thecharacteristics of the fields in the categories. For instance, asexplained before, the large majority of the aquifers fall undercategory C. Storing in aquifers require new platforms and wells(which is not always the case with hydrocarbon fields) as well ascomplete seismic studies (which have been done for hydrocarbonfields) and are therefore on average more expensive. Also, a relativelarger number of smaller fields are located in category C (comparedto A and B). These fields are more expensive per tonne of CO2

stored.

4. Discussion

This research aimed to develop a methodology to screen storagefields that used publicly available data. The results of such anexercise provide insights into the potential capacity of TheNetherlands once considerations on geological characteristics thatcould limit the potential leakage of CO2 are taken into account. Thiskind of information could allow a better understanding of thefeasibility of CO2 deployment at large scale under differentscenarios (e.g., what would be the impact of a given CO2

implementation path if all fields with lower scores for riskmanagement were not considered?). The results are however notto be used as a selection guide for specific storage places. Before apotential storage location can be marked as sufficiently safe, localvariations in lithology of both the reservoir (aquifer) and caprockshould be examined by site-specific feasibility studies. Such afeasibility study should address, among other things, the localstress at faults (geo-mechanical state), small-scale faulting andheterogeneity of both the cap and reservoir rock, reservoirsimulations, and variations in caprock thickness. Geologicalvariance will become clear during such a study.

An additional result of this project was the development of adetailed database where geological information at a field levelwas gathered in a systematic and consistent way. Such a databasecan be further improved, especially regarding aquifers andoffshore fields. Furthermore, while in The Netherlands, oil andgas companies are obliged to supply data of their hydrocarbonfields15 (e.g., permeability, porosity, stratigraphy, pressuremeasurements, and temperature), availability of this datadepends on confidentiality, the number and quality of measure-ments performed during drilling, and processing of the data by theDINO database. It is therefore important to develop ways in whichthe data can be used for, for instance, potential CO2 storagecalculations or screening exercises of the type made in thisresearch.

Further, it is recognized that the results of the project may bebiased in the sense that the confidence level is going to be biasedtowards the sites at high risk than the ones that show low risk (i.e.,absence of proof is not proof of absence). Unfortunately this kind ofissue can only be solved by gathering extra data that would allowfields to be assessed under ‘‘equal’’ conditions.

15 Also data from exploration wells that did not encounter gas or oil have to be

provided.

Fig. 6. Locations of fields according to effort needed to manage risk, storage costs and time availability.


Another area for further development is the (possible)dependence among variables. In this study the indicators usedwere taken as independent. Therefore it is possible that some ofthe effects are under or over estimated. Also it should be notedthat the methodology for the development of the indicators,scores and weights for the criteria ‘‘effort needed to managerisk’’ were based on expert elicitation. CO2 storage is a relativelynew field with relatively large uncertainties due to lack of dataand scientific controversy. The consultation rounds allowed usto make explicit the knowledge of experts, based on accumu-lated experience and expertise, including their insights into the

limitations, strengths, and weakness of the published knowl-edge and available data. The relations between categorieswithin the indicators and their scores need therefore to becorroborated. This is only possible by carrying out experimentalwork.

Finally, there is a relation between the effort needed to managerisk and costs (a high risk level usually results in higher costs tobring down the risk again to acceptable levels). In this research weconsidered the dependency between both criteria to be low andtherefore they are treated as independent. This point should beexplored in further research.

Fig. 7. Frequency distributions of fields according to effort needed to manage risk (category A, B or C), and storage costs.


5. Conclusion

This project aimed to develop a methodology that allowed thescreening of CO2 storage options in The Netherlands. In this studythree criteria have been used: potential storage capacity, costs ofstorage, and effort needed to manage risk. The methodologyprovides quantitative results for the first two criteria and isqualitative with respect to risk. It uses geological proxies forunderstanding the level of effort that would have to be made inorder to manage a safe storage place.

For the development of the methodology a detailed database for176 storage locations has been developed. This allowed us toassure consistency in data compilation and interpretation, to theextent that this is possible given the variability in the extent andquality of geological and geophysical data. A spreadsheet wasdesigned to provide an assessment of each of the criteria throughan evaluation of the fields present in the database and a set ofscores provided by a (inter)national panel of experts. Theassessment is sufficiently simple and allows others to review it,re-do it or expand it. The results of the methodology show thatplausible comparisons of prospective sites with limited character-ization data are possible.

Several extensions to the methodology are possible. First, moredetailed data could be used, especially concerning offshore fieldsand aquifers. Second, further knowledge on the influence of aparameter on the risk of CO2 leakage and on how it interacts withother parameters/indicators could be gathered. This knowledgecould then be reflected in new data, indicators, or criteria beingadded into the tool. Third, by experimental verification of therelations between geological characteristics and scores for riskmanagement effort (best, worst and intermediate categories)within a given indicator could be attempted. In this paper, theserelations are based on the knowledge of the experts consultedwhich in many cases are based on analogous situations. Fourth,the methodology could be extended by including multipledependencies among the data and indicators and by includingadditional risk drivers (e.g., displacement of brine into potablewater). Finally, data uncertainty could be explicitly included inthe methodology.

Though the results of this study are not to replace detailed riskassessments that would need to be carried out for specific siteselection, they can help policy and decision makers to understandthe influence of several criteria in the suitability and availability ofpotential storage locations. For instance, our results indicate that25% of the theoretical potential storage capacity in The Nether-lands falls under the category with the lowest scores regarding thecriterion effort needed to manage risk. Since 96% of these fields willbe available before 2020, the effects of not using these fields for the(short term) national strategy on CO2 storage should be examinedin detail.

Acknowledgements

For their feedback and input into this project, the authors aredeeply grateful to John Bradshaw (Greenhouse Gas StorageSolutions), Marjeta Car (Geoinzeniring), John Gale (IEA-GHG),Sam Holloway (British Geological Survey), Jerome Le Gouvec(OXAND), Stefan Bachu (Alberta Energy and Utilities Board),Margriet Kuijper (NAM), Isabel Czernicchowski-Lauriol (BRGM),Bill Gunter (Alberta Research Council), C.R. Geel, T. Benedictus,A.N.M. Obdam and E. Simmelink (TNO).

This project is part of the National Programme on CarbonCapture and Storage in The Netherlands (CATO). This programme isfinanced by The Netherlands Ministry of Economic Affairs. Formore information see: http://www.CO2-CATO.nl.

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Screening CO2 storage options in The Netherlands