Seismic Hazard and Risk Assessment
Groningen Field
update for Production Profile
GTS - raming 2019

March 2019

By Jan van Elk, Assaf Mar-Or, Leendert Geurtsen, Jeroen Uilenreef and Dirk Doornhof

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Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
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© EP2019

Dit rapport is een weerslag van een voortdurend studie- en dataverzamelingsprogramma en bevat de stand
der kennis van januari 2019. Het copyright van dit rapport ligt bij de Nederlandse Aardolie Maatschappij B.V.
Het copyright van de onderliggende studies berust bij de respectievelijke auteurs. Dit rapport of delen daaruit
mogen alleen met een nadrukkelijke status-en bronvermelding worden overgenomen of gepubliceerd.

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Contents
Samenvatting van de Dreigings- en risicoinschatting ............................................................................. 6
Gevolgen van de operationele strategieën ............................................................................................. 6
Volumeverdeling per cluster voor warm, gemiddeld en koud jaar .................................................... 6
Dreigings- en risicoanalyse .................................................................................................................. 6
Beschrijving van de verwachte bodembeweging ............................................................................ 7
Beschrijving van aard en omvang schade........................................................................................ 9
Beschrijving van de risico’s als gevolg van de verwachte bodembeweging ................................. 10
Analyse van individueel aardbevingsrisico van gebouwen ........................................................... 11
Overzicht van gebouwtypologieën met een LPR > 10-5/jaar ..................................................... 13
Analyse van regionale productiefluctuaties ...................................................................................... 13
Vergelijking en samenvatting van operationele strategieën ............................................................ 15
1

Introduction ................................................................................................................................... 17
Previous Hazard and Risk Assessment Reports ................................................................................. 17
Winningsplan 2016 ........................................................................................................................ 17
Hazard and Risk Assessment November 2017 .............................................................................. 17
Complementary production profiles ............................................................................................. 17
Basispad Kabinet (29/3/2018) ....................................................................................................... 17
Verwachtingenbrief (Expectation Letter) (2/5/2018) ................................................................... 19
Kamerbrief - Voortgang maatregelen gaswinningsbrief (6/6/2018) ............................................. 19
Production Profile GTS-raming February 2019 ............................................................................. 20

2

HRA-Model Improvements ............................................................................................................ 22
Introduction....................................................................................................................................... 22
Exposure Database ............................................................................................................................ 22
Recent activities to improve the expose database ....................................................................... 23
Conclusions and general results of the studies ............................................................................. 26
Fragility and Consequence Models for building typologies .......................................................... 26
Study activities following assurance meeting ............................................................................... 27
Summary of main improvements to the fragility curves – Version 6............................................ 31

3

Production Profile.......................................................................................................................... 32
Production profile: Demand profiles GTS-raming 2019 .................................................................... 32
Spatial distribution of production (Operational Strategy) ................................................................ 34
Optimisation of production distribution to minimize seismic hazard and risk ............................. 34
Strategy definition ......................................................................................................................... 34
Production regions ........................................................................................................................ 36
Model implementation ................................................................................................................. 36
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Modelling setup................................................................................................................................. 37
Dynamic reservoir model (Mores model V5) ................................................................................ 37
Production data 1/1/2019 to 30/9/2019 ...................................................................................... 37
Surface network model (Genrem) ................................................................................................. 37
Production considerations ............................................................................................................ 37
Production Fluctuations .................................................................................................................... 38
Production profiles ............................................................................................................................ 40
Reference case (IB2018) ................................................................................................................ 40
Strategy 1 (pwPGV) – Cold temperature year ............................................................................... 47
Strategy 1 (pwPGV) – Warm temperature year ............................................................................ 50
Strategy 2 (Event count) – Average Temperature......................................................................... 53
Strategy 2 (Event count) – Cold temperature year ....................................................................... 56
Strategy 2 (Event count) – Warm temperature year .................................................................... 59
4

Event Rate and Hazard Assessment .............................................................................................. 62
Event rate forecast ............................................................................................................................ 62

5

Hazard Assessment........................................................................................................................ 65
Hazard metrics................................................................................................................................... 65
Risk Assessment ............................................................................................................................ 65
Building Damage Assessment........................................................................................................ 65
Hazard Map for Peak Ground Acceleration................................................................................... 66
Hazard Assessment ........................................................................................................................... 68
Hazard for gas-year 2019 / 2020 ................................................................................................... 95

6

Risk Assessment ............................................................................................................................ 99
Risk Metrics ....................................................................................................................................... 99
Individual Risk Metrics................................................................................................................... 99
Object-related Individual Risk and Individual Risk .................................................................... 99
Inside and Outside Local Personal Risk ..................................................................................... 99
Current Practice in Risk Assessments ...................................................................................... 101
Proposed improvement of the Risk Assessment ..................................................................... 102
Residence Time Estimates ....................................................................................................... 102
Number of buildings compared to the safety norm........................................................................ 103
Assessment of Local Personal Risk (LPR) ..................................................................................... 103
Number of years above the norm ............................................................................................... 115
Individual Earthquake Risk (OIA) ................................................................................................. 116
Assessment of Object-related Individual Risk ............................................................................. 116
Maps of Buildings compared to the Meijdam-Norm Risk Levels .................................................... 117
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Insights into the development of the buildings above the norm.................................................... 131
Introduction ................................................................................................................................. 131
Comparing the results of risk assessments ................................................................................. 132
Update to buildings above the norm .......................................................................................... 133
Improvements to Exposure Model (EDB V6) ............................................................................... 135
Risk for gas-year 2019 / 2020 .......................................................................................................... 137
Number of buildings above the norm ......................................................................................... 137
Buildings above the norm – areal maps ...................................................................................... 137
Structural upgrading program ......................................................................................................... 143
7

Damage Assessment.................................................................................................................... 144
Classification of Building Damage; Building Damage States ........................................................... 144
European Seismological Commission, EMS-1998 ....................................................................... 144
Forecast for Damage State 1 (DS1) aesthetic damage .................................................................... 146
Earthquake catalogue of events ...................................................................................................... 146
Exposure model ............................................................................................................................... 146
Results ............................................................................................................................................. 147
Forecast for Damage State 2 (DS2) and Damage State 3 (DS3) ...................................................... 150

8

References ................................................................................................................................... 156

Appendix A – Correspondence ............................................................................................................ 159
Verwachtingenbrief (Expectation Letter) ........................................................................................ 159
Letter Advies hooglerarenpanel over berekening aardbevingsrisico (7-3-2019) ............................ 165

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Samenvatting van de Dreigings- en risicoinschatting
Deze Nederlandstalige samenvatting van dit rapport met de dreigings- en risicoinschatting is
opgenomen in de Operationele Strategie als hoofdstuk 6. Deze is hier herhaald zodat dit rapport
ook als een zelfstandig rapport gelezen kan worden.

Gevolgen van de operationele strategieën
Volumeverdeling per cluster voor warm, gemiddeld en koud jaar
In de GTS-dataset zijn de Groningen productievolumes opgenomen voor een warm (referentiejaar
2006-2007), gemiddeld (referentiejaar 2011-2012) en koud (referentiejaar 1995-1996) jaar. Nadat
GasTerra de inzet van UGS Norg en PGI Alkmaar voor deze productiescenario’s heeft verwerkt tot de
noodzakelijke Groningenveldvolumes, zijn de clustervolumes op dag-basis gemodelleerd volgens de
opstartvolgorde zoals in hoofdstuk 5 van de operationele strategie beschreven. Voor het warme,
gemiddelde en koude referentiejaar zijn de volumes uit de clusters als percentage van het totale
productievolume weergegeven in Figuur 1.

Figuur 1

Cluster volume verdeling voor Operationele Strategie 1 en Operationele Strategie 2 voor een warm (20062007), gemiddeld (2011-2012) en koud (1995-1996) jaar.

Dreigings- en risicoanalyse
In dit document “Seismic Hazard and Risk Assessment Groningen Field update for Production Profile
GTS - raming 2019” (verder: de HRA 2019) is conform de eisen uit artikel 1.3a.2 Mijnbouwregeling het
volgende opgenomen:
x
x
x
x
x

een beschrijving van de verwachte bodembeweging als gevolg van de wijze waarop de
clusters worden ingezet (HRA 2019 – Hoofdstuk 4);
een beschrijving van de mogelijke omvang en verwachte aard van de schade door
bodembeweging als gevolg van de wijze van de inzet van de clusters (HRA 2019 – Hoofdstuk
7);
een beschrijving van de risico’s als gevolg van de verwachte bodembeweging als gevolg van
de wijze van de inzet van de clusters (HRA 2019 – Hoofdstuk 6);
een analyse van het aantal gebouwen dat een individueel aardbevingsrisico met zich
meebrengt dat groter is dan 10-5 per jaar, waarbij het individueel aardbevingsrisico wordt
berekend met toepassing van de verwachtingswaarde (HRA 2019 – Hoofdstuk 6); en
een analyse van de ontwikkeling voor de komende 10 jaar ten aanzien van het aantal
gebouwen (HRA 2019 – Hoofdstuk 6).

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Conform de Verwachtingenbrief is hierbij – naast het referentiescenario - uitgegaan van de twee
operationele strategieën die zijn voorgeschreven door de minister, zodat een directe vergelijking
mogelijk is tussen deze operationele strategieën.
Voor de 10-jaarsverwachting wordt verwezen naar de HRA 2019, de relevante hoofdstukken staan
hierboven genoemd in de opsomming. In dit hoofdstuk wordt specifiek in gegaan op de effecten die
de operationele strategieën hebben voor het gas-jaar 2019-2020. Omdat in de HRA 2019 – net als de
voorgaande jaren – is uitgegaan van een analyse per kalenderjaar, worden daarbij de jaren 2019 en
2020 inzichtelijk gemaakt. De figuren die in dit document zijn opgenomen voor de kalenderjaren 2019
en 2020 zijn daarnaast voor het gas-jaar 2019-2020 opgenomen in de HRA 2019 (hoofdstuk 6).

Beschrijving van de verwachte bodembeweging
Bodembeweging kan worden opgesplitst in twee componenten: bodemdaling en seismiciteit.
Bodemdaling
Op dit moment is NAM nog bezig de gevolgen te onderzoeken van de nieuwe productiescenario’s in
combinatie met de resultaten van meest recente bodemdalingsmetingen, maar aangezien de
productievolumes voor de komende jaren niet hoger zijn dan de uitgangspunten van het rapport
“Assessment of Subsidence based on Production Scenario “Basispad Kabinet” for the Groningen Field”
uit juni 2018, kan het verloop van de bodemdaling in tijd weliswaar enigszins anders worden dan in
het rapport (paragrafen 5.1, 5.2, 5.6) aangegeven, maar worden geen significante wijzigingen verwacht
in de conclusies betreffende omvang en aard van de schade door bodemdaling, de te nemen
maatregelen en de monitoring (paragrafen 5.3, 5.4, 5.5, 5.7).
Seismiciteit
Voor wat betreft seismiciteit geven de onderstaande figuren aan waar welke seismische dreiging
(hazard) ten gevolge van de gaswinning uit het Groningenveld zich voordoet bij de uitvoering van de
twee operationele strategieën.

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Figuur 2

Dreigingskaarten voor a) Operationele Strategie 1, b) Operationele Strategie 2 en c) het verschil in dreiging
tussen beide strategieën. In c) geeft de rode kleur een lagere dreiging weer, de blauwe kleur een hogere
dreiging. Voor 2019 is de “delta” minder significant omdat tot en met 1 oktober voor beide analyses een
identieke operationele strategie (IB 2018) wordt gehanteerd. Het verschil in dreiging wordt slechts voor 3
maanden door de alternatieve strategieën beïnvloed.

In Figuur 2 a) en b) zijn de ruimtelijke dreigingskaarten weergegeven. Op basis van deze
dreigingskaarten is geen onderscheid waarneembaar tussen Operationele Strategie 1 en 2. Om het
verschil inzichtelijk te maken is ook het “delta” (Figuur 2 c)) tussen beide dreigingskaarten opgenomen
(Figuur 5.8 in de HRA 2019). Hoewel Operationele Strategie 2 meer dreiging in het zuidwesten tot
gevolg heeft in vergelijking met strategie 1, zijn de verschillen nauwelijks significant (<0,004g in 2019
en <0,016g in 2020). Het verschil komt voort uit de hogere bevolkingsdichtheid in deze regio door
onder andere de aanwezigheid van de gemeente Groningen. Bij een optimalisatie van de
productieverdeling over het veld op basis van PwPGV zal daarom uit het zuidwesten relatief minder
gas geproduceerd worden waardoor de persoonsgewogen dreiging lager blijft.
Figuur 3 3 maakt inzichtelijk hoeveel seismiciteit te verwachten is in de vorm van het aantal
aardbevingen met een magnitude groter dan 1.5 voor de verschillende operationele strategieën
(Figuur 4.3 in de HRA 2019).

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Figuur 3

Aantal aardbevingen (M >= 1.5) uitgedrukt in het verwachte aantal bevingen/events per jaar (“Event rate”)
voor Operationele Strategie 1 (links) en Operationele Strategie 2 (rechts).

Voor 2019 en 2020 is in Tabel 1 een overzicht opgenomen met de waarschijnlijkheid waarop een
beving met een bepaalde magnitude plaats kan vinden voor de twee operationele strategieën in 2019
en 2020. In hoofdstuk 4 van HRA 2019 staan de resultaten voor latere jaren weergegeven.

Tabel 1

Jaar

Operationele
Strategie:

M>3.6

M>4.0

M>4.5

M>5.0

2019

1 – “PwPGV”

12.57%

4.69%

0.97%

0.18%

2020

1- “PwPGV”

10.62%

3.93%

0.86%

0.15%

2019

2 – “Event Count”

12.25%

4.63%

0.99%

0.20%

2020

2– “Event Count”

9.99%

3.78%

0.77%

0.13%

Overzicht van de waarschijnlijkheid waarmee een beving boven een bepaalde magnitude zich zal voordoen
voor Operationele Strategie 1, Operationele Strategie 2 en voor 2019 en 2020 – uitgaande van een gemiddeld
jaar.

In de volgende paragrafen wordt – in lijn met de volgorde van artikel 1.3a.2. Mijnbouwregeling – nader
ingegaan op de risico’s die deze seismische dreiging met zich mee brengt voor de omgeving.

Beschrijving van aard en omvang schade
In de Verwachtingenbrief is aangegeven dat bij de uitwerking van artikel 1.3a.2, lid 3 sub b,
Mijnbouwregeling een schadeprognose dient te worden gemaakt voor de schadegrenstoestanden
DS1, DS2 en DS3 uit het EMS-98, European Seismological Commission, 1998. NAM dient daarbij een
kwantitatieve analyse van de DS1-schades evenals een verwachting van DS2- en DS3-schade
categorieën in te dienen bij dit document1.
In de HRA 2019 staan de gevraagde schadeprognoses beschreven in hoofdstuk 7. De schadeprognose
voor DS1 zijn weergegeven in Figuur 4 (figuur 7.4 in de HRA 2019)

1

In de Verwachtingenbrief staat aangegeven dat NAM een kwalitatieve analyse van de DSl-schades evenals een
verwachting van DS2- en DS3-schades 15 maart dient toe te sturen. De kwantitatieve prognoses van de drie
genoemde schades bij het gegeven productiescenario mochten vanwege de omvang uiterlijk 12 april worden
ingediend. Deze latere datum van 12 april bleek niet nodig te zijn, alle gevraagde informatie is opgenomen in dit
document.

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Figuur 4

“Mean” en “P50” voorspelling van DS1 schade voor de periode 2018-2028 voor a) Operationele Strategie 1 en
b) Operationele Strategie 2.

Concreet laten de figuren zien dat er geen materieel verschil is in voorspelling van DS1 schades voor
de beide operationele strategieën.
Ten aanzien van de verwachte DS2 en DS3 schades geeft de HRA 2019 aan dat er geen materieel
verschil (< 1%) is tussen beide operationele strategieën. De resultaten van de vergelijking staan
weergegeven in Figuur 5 (Figuur 7.8 in de HRA 2019).

Figuur 5

Risico voor DS2 (grijze lijn) en DS3 (zwarte lijn) schade voor Operationele Strategie 1 (vast lijn) en Operationele
Strategie 2 (onderbroken lijn) voor de 2019-2028 op basis van een gemiddeld jaar.

Beschrijving van de risico’s als gevolg van de verwachte bodembeweging
Het risico ten gevolge van de gaswinning uit het Groningenveld kan op verschillende wijzen worden
beschreven. In de HRA 2019 is in tabel 6.1 een overzicht opgenomen van de mogelijke wijze waarop
risico’s kunnen worden gekwantificeerd. Deze risico’s zijn:
1. Objectgebonden Individueel Aardbevingsrisico (OIA)
Het objectgebonden individueel aardbevingsrisico, is het risico dat een individu om het leven komt
in een jaar als gevolg van instorting van of vallende objecten van een gebouw waar een individu
zich in de directe nabijheid van bevindt ten gevolge van een aardbeving. Hierbij wordt het risico
gewogen met een statistisch bepaalde gemiddelde verblijfsduur in het gebouw. Op basis van de
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Verwachtingenbrief, en aanvullende e-mail, dient NAM in lijn met het advies van de commissie
Meijdam en conform het advies van het hooglerarenpanel, het OIA aanvullend te rapporteren in
een technische bijlage (HRA 2019).
2. Individueel Aardbevingsrisico (IAR)
Het individuele aarbevingsrisico is het jaarlijkse risico waar een individu aan wordt blootgesteld in
de diverse gebouwen waar hij of zij zich in bevindt, dan wel in de nabijheid waarvan hij/zij verblijft.
De verblijfsduur wordt bepaald door middel van kennis over de aanwezigheid van iedere inwoner
op ieder moment van de dag. Doordat dit technisch niet uitvoerbaar is wordt dit risico niet verder
beschouwd.
3. Plaatsgebonden Persoonlijk Risico Binnen (“ILPR”)
De waarschijnlijkheid dat een fictief onbeschermd persoon die permanent aanwezig is in een
gebouw komt te overlijden.
4. Plaatsgebonden Persoonlijk Risico Buiten (“OLPR”)
De waarschijnlijkheid dat een fictief onbeschermd persoon die permanent aanwezig is in de
nabijheid van een gebouw komt te overlijden.
5. Plaatsgebonden Persoonlijk Risico (“LPR”)
De waarschijnlijkheid dat een fictief onbeschermd persoon die permanent aanwezig is in, dan wel
in de nabijheid van een gebouw komt te overlijden. Bij LPR wordt uitgegaan van een permanente
verblijfduur in het gebouw. NAM dient op grond van de Verwachtingenbrief, en aanvullende email, in de risicoberekeningen aan te sluiten bij de eerder uitgevoerde Hazard and Risk Assessment
van juni 2018 waarbij ook LPR gehanteerd is. De LPR dient ook te worden gerapporteerd in dit
document.

Analyse van individueel aardbevingsrisico van gebouwen
In de Verwachtingenbrief is in aanvulling op de toepasselijke wettelijke kaders aangegeven dat NAM
de volgende informatie moet aanleveren voor het gas-jaar 2019-2020:
x
x
x
x

Ruimtelijke kaart met de locaties van de gebouwen waar het OIA2 groter is dan 10-5/jaar voor
het gas-jaar 2019/2020.
Ruimtelijke kaart met de locaties van de gebouwen waar het OIA groter is dan 10-4/jaar voor
het gas-jaar 2019/2020.
NAM zal deze gegevens ook in de vorm van een tabel opnemen in haar rapportage (zie als
voorbeeld: tabel 5.1a & b uit "Seismic risk assessment for production scenario "Basispad
Kabinet" for the Groningen field, June 2018").
Tabel met alle gebouwtypologieën waarvan het risico >10-4/jaar en > 10-5/jaar is voor het
gasjaar 2019-2020.

Figuur 6 geeft een ruimtelijke kaart met de locaties van de gebouwen waar het LPR groter is dan 10-5
/jaar voor het jaar 2019 en 2020 voor de twee operationele strategieën.

2

Op 14 maart 2019 is door het ministerie van EZK bevestigd dat de bewoording in de Verwachtingenbrief
aangaande OIA/IAR/LPR verkeerd zijn opgenomen. Op plaatsen waar OIA genoemd stond in de
Verwachtingenbrief dient LPR te worden gelezen, daar waar IAR stond was OIA bedoeld. Dit document zal dus
verder de risico-analyses weergeven voor het LPR risico, in Appendix A kan zowel LPR als OIA gevonden worden.

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Figuur 6

Ruimtelijke kaarten met de locaties van gebouwen waarvan het LPR groter is dan 10-5/jaar. Links: locaties voor
Operationele Strategie 1, Rechts: Operationele Strategie 2, Boven: 2019, Onder 2020. Voor deze ruimtelijke
kaarten is uitgegaan van een gemiddeld jaar.

Voor het gas-jaar 2019-2020 en de jaren daaropvolgend zijn er geen gebouwen met een LPR noch met
een OIA groter dan 10-4/jaar.
Tabel 2 geeft voor de jaren 2019 en 2020 een overzicht van het aantal gebouwen met een LPR > 10-5/
jaar bij een gemiddeld jaar. Ter vergelijking zijn ook het aantal gebouwen opgenomen met een OIA
groter dan 10-5/jaar.

Tabel 2

Overzicht van het aantal gebouwen met een LPR en OIA > 10-5/jaar voor 2 operationele strategieën voor 2019
en 2020 bij een gemiddeld jaar3.

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Voor een analyse van bodembeweging, schade, risico’s en gebouwen voor de koude en warme jaren
wordt verwezen naar hoofdstuk 6 van de HRA 2019. Dit hoofdstuk bevat ook een gedetailleerde
beschrijving van het aantal woningen, per type en een vergelijking met de resultaten voor HRA-analyse
van gas-jaar 2018-2019.

Overzicht van gebouwtypologieën met een LPR > 10-5/jaar
Voor 2019 zijn er nog een viertal gebouwtypologieën te onderscheiden met een LPR > 10-5/jaar. Deze
typologieën zijn:
-

URM1_F – Typische boerderij met een aangelegen schuur
URM3M_U – Metselwerk appartementengebouwen met een spouwmuur en betonnen
vloeren van minimaal 3 verdiepingen met beperkte sterkte in 1 richting
URM4L – Rijtjeswoning met een spouwmuur, betonnen vloeren en grote openingen in de
gevel(s) van de begane grond.
URM3L – Vergelijkbaar met typologie URM4L maar met een lager percentage aan opening in
de begane grond gevel(s)

De gebouwen die in deze risico inschatting niet voldoen aan de Meijdam-norm, komen voor een groot
deel overeen met de gebouwen die ook in juli 2018 niet voldeden aan de norm. In de afgelopen
maanden is de volledige gebouwenvoorraad in Groningen opnieuw geëvalueerd om te bepalen of er
gebouwen zijn die mogelijk meer kwetsbaar zijn dan tot nu toe werd aangenomen. In deze zoektocht
naar de zogenaamde “false negatives” zijn een aantal gebouwen geïdentificeerd die in deze inschatting
niet aan de norm voldoen die eerder wel als veilig waren gekwalificeerd. Hierbij zijn de laatste inzichten
en opgedane kennis van de gebouwen in Groningen en aanbevelingen van het HRA assurance panels
meegenomen. Een beschrijving van de ontwikkeling van het aantal en typologieën van de gebouwen
boven de norm met een vergelijking van de resultaten uit 2018 is beschreven in hoofdstuk 6 van de
HRA 2019.

Analyse van regionale productiefluctuaties
In dit hoofdstuk worden de resultaten gerapporteerd betreffende de te verwachten
productiefluctuaties in de clusters van het Groningenveld voor gas-jaar 2019-2020. Hierbij wordt
tevens het aantal overschrijdingen van de fluctuatiebandbreedte, zoals vastgelegd in de
Verwachtingenbrief, inzichtelijk gemaakt. In de dataset van GTS zijn de Groningen productievolumes
opgenomen voor 30 temperatuurscenario’s. Nadat GasTerra de inzet van UGS Norg en PGI Alkmaar
voor deze scenario’s heeft verwerkt tot resterende Groningenveldvolumes, worden de
productielocatie- en clustervolumes op dag-basis gemodelleerd volgens de operationele strategieën
zoals in hoofdstuk 5 van de operationele strategie beschreven.
Het aantal overschrijdingen van de fluctuatiebandbreedte is gedefinieerd als het aantal maanden dat
een overschrijding van de fluctuatiebandbreedte plaats vindt op basis van alle 30 geanalyseerde
temperatuurscenario’s, uitgedrukt als fractie van het totaalaantal “clustermaanden”. Op basis van de
GTS-dataset met hierin dertig temperatuurscenario’s zitten 30 (scenario’s) x 12 (maanden) x 5
(clusters) = 1800 clustermaanden. Onderstaande figuren geven grafisch weer welke fluctuaties
plaatsvinden in de vijf clusters en of er sprake is van overschrijdingen.

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Figuur 7

Resulterende fluctuaties voor Operationele Strategie 1 en Operationele Strategie 2 voor relatieve
maandvolume veranderingen en ten opzichte van de gemiddelde productie over de 12 voorgaande maanden
voor de verschillende clusters.

Het aantal overschrijdingen voor de operationele strategieën bedraagt:
x
x

Operationele Strategie 1: 380 van de 1800 clustermaanden ofwel 21%
Operationele Strategie 2: 834 van de 1800 clustermaanden ofwel 46%

Een alternatieve operationele strategie waarbij de regionale productiefluctuaties worden
geminimaliseerd door alle clusters gelijkmatig op en af te regelen is momenteel niet opgenomen in dit
document. Bij een dergelijke operationele strategie is de relatieve clustervolumeverdeling constant en
dus niet afhankelijk van het temperatuurscenario. Daarentegen zal zowel de event count als de
PwPGV, op basis van een kwalitatieve inschatting op basis van de resultaten in het Bouwstenen
document in 2018, toenemen. Voor een volledig HRA-analyse van deze operationele strategie was
onvoldoende tijd beschikbaar.
Voor de Operationele Strategieën 1 en 2 ligt het aantal te verwachten overschrijdingen aanzienlijk
hoger dan de in het Bouwstenen document 2018 gerapporteerde aantallen. Dit is een gevolg van de
volgende aspecten:
-

-

Voor de operationele strategie 2019-2020 worden ook maand-op-maand fluctuaties
meegenomen in het bepalen van het aantal overschrijdingen. Voor de analyse van het gas-jaar
2018-2019 zijn alleen de overschrijdingen ten opzichte van het 12 maanden voortschrijdend
gemiddelde beschreven in het Bouwstenen document.
Het benodigde volume uit het Groningenveld is ~25% lager dan de volumes opgegeven voor
de analyses voor gas-jaar 2018-2019. Dit komt voornamelijk door de hogere inzet en
uitbreiding van conversiemiddelen van GTS waarbij Groningen nog wel steeds op momenten
van hoge vraag moet produceren ten behoeve van de leveringszekerheid. Op deze momenten
zullen met name clusters die met de laagste prioriteit worden ingezet alsnog een bijdrage
moeten leveren, hetgeen zal leiden tot relatief grotere fluctuaties ook buiten de in de
Verwachtingenbrief opgegeven bandbreedtes.
14

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

In het algemeen geldt dat bij een lager volume uit Groningenveld de fluctuaties toe zullen nemen in
aantal en grootte daar de absoluut toegestane volume variaties lager zullen zijn. Verder zal bij een
sterkere preferentiële onttrekking uit bepaalde clusters, zoals het geval is onder Operationele
Strategie 2, ook de kans op het aantal overschrijdingen van de in de Verwachtingenbrief opgegeven
bandbreedtes toenemen. Deze overschrijdingen treden dan met name voor de clusters die alleen
ingezet worden bij een hogere gasvraag.

Vergelijking en samenvatting van operationele strategieën
De operationele strategieën kunnen als volgt worden samengevat:
Operationele Strategie 1:
-

-

-

Optimalisatie op bevolkingsdichtheid gewogen grondsnelheid risico resulteert in een
inzetvolgorde met voornamelijk onttrekking uit de productielocaties in de clusters Zuidwest
en Zuidoost bij een vlakke inzet van cluster Bierum.
De clusteropstartvolgorde die hoort bij deze Operationele Strategie sluit aan bij de in het
instemmingsbesluit voor gas-jaar 2018-2019 gekozen inzetstrategie. Vooralsnog blijkt dat deze
Operationele Strategie operationeel goed uitvoerbaar is.
Het aantal overschrijdingen van de fluctuatiebandbreedte is kleiner dan het aantal
overschrijdingen onder Operationele Strategie 2.
In Operationele Strategie 1 wordt onder gemiddelde condities de capaciteitsvraag over meer
clusters verdeeld ten opzichte van Operationele Strategie 2, waardoor er meer operationele
flexibiliteit is in het geval van geplande of ongeplande productie-uitval.

Operationele Strategie 2:
-

-

-

Optimalisatie op het minimaal aantal te verwachten bevingen resulteert in een inzetvolgorde
met voornamelijk onttrekking uit de productielocaties in de clusters Zuidwest en Zuidoost.
Doordat cluster Centraal-Oost én Bierum opgeregeld worden in momenten van hoge vraag,
zal de kans op overschrijding van de fluctuatiebandbreedtes groter zijn dan bij Operationele
Strategie 1. Door de wijze waarop cluster Bierum in deze Operationele Strategie wordt ingezet
zal veelal niet voldaan kunnen worden aan de bandbreedtebeperking van 20%.
Doordat nagenoeg alle volumes in een gemiddeld jaar uit slechts 2 clusters zal komen, zullen
compressoren op de productielocaties op een relatief hoge inzet draaien waardoor bij
ongeplande uitval en onderhoud de regionale fluctuatieoverschrijdingen zullen toenemen
door het verschuiven van productie naar overige clusters.
Doordat de compressoren op de productielocaties op een hoge inzet draaien, zal het
stroomverbruik van de compressoren voor deze Operationele Strategie het hoger liggen dan
in Operationele Strategie 1 en hiermee ook de hoogste CO2 intensiteit hebben.

Tussen de verschillende operationele strategieën is geen verschil in de volumes die geproduceerd
worden in het gas-jaar 2019-2020 en tussen de inzetbare capaciteit. Ook zijn dreiging, risico en het
aantal gebouwen dat niet aan de Meijdam-norm voldoet vergelijkbaar.
In Tabel 3 is een kwalitatieve beoordeling opgenomen tussen de operationele strategieën. Een “+”teken geeft een positief effect weer, een “-“-teken een negatief effect en een “+/-“-teken een neutraal
of geen effect. Daarbij is de beoordeling relatief ten opzichte van de andere strategie.

15

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Tabel 3

Kwalitatieve vergelijking van de operationele strategieën.

16

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

1

Introduction

Previous Hazard and Risk Assessment Reports
Winningsplan 2016
In April 2016, NAM submitted the Groningen Winningsplan 2016 (Ref. 1) to the Minister of Economic
Affairs and Climate Policy. This Winningsplan was accompanied by a Technical Addendum (Ref. 2)
providing further background to the Hazard and Risk Assessments supporting the Winningsplan. The
Mining Law requires that winningsplannen are approved by the Minister of Economic Affairs and
Climate Policy. The approval was granted in the Instemmingsbesluit Winningsplan Groningenveld,
issued on the 30th of September 2016 (Ref. 3).

Hazard and Risk Assessment November 2017
In response to the specific obligation in the Instemmingsbesluit, NAM prepared the report “Induced
Seismicity in Groningen, Assessment of Hazard, Building Damage and Risk – November 2017” (Ref. 5),
which was submitted to the Minister of Economic Affairs and Climate Policy and to SodM on 1st
November 2017. This describes the full Hazard and Risk Assessment for induced seismicity in
Groningen, starting from the production of gas (the cause) to the effects on people and buildings
(damage and risk).
The Wijzigingsbesluit of 24th May 2017 (Ref. 4), limited the production in an average temperature year
to 21.6 Bcm/year. Because in the Wijzigingsbesluit special circumstances were identified that could
require an increase in the production from the field, the Hazard and Risk Assessment of November
2017 (Ref. 5) was prudently based on an average annual production level of 24 Bcm/year gas
production, which covered these eventualities.

Complementary production profiles
To assess the effect of different production profiles on seismic risk, a complementary set of production
profiles covering a wide range of production levels was presented in the addendum to the November
2017 Hazard and Risk Assessment (Ref. 6), issued March 2018. The set of production profiles analysed
included the production aspirations as outlined in the Regeerakkoord (10/10/2017) and several
production profiles as included in reports by GTS, which were based on different utilisation of the
existing nitrogen blending plant and the construction of an additional nitrogen blending plant.

Basispad Kabinet (29/3/2018)
The letter sent by the Minister of Economic Affairs and Climate Policy to Parliament (Kamerbrief) on
29th March 2018 (Ref. 7) announced the ambition of the cabinet to reduce the production from the
Groningen field as soon as possible, leading to cessation of production around 2030. It contained
annual production volumes for the period 2018-2031, which was labelled “Basispad Kabinet” (Fig. 1.1
and 1.2). Different production profiles were presented for cold, average and warm temperature years.

17

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 1.1

Production profile prepared by GTS (including construction of a nitrogen blending plant) in orange and
production profile “Basispad Kabinet” in blue from reference 7. Both these production profiles are for a
sequence of cold ambient temperature years.

Figure 1.2

Production profile “Basispad Kabinet” for a sequence of cold temperature years (in blue), average temperature
years (in green) and of warm temperature years (in orange) from reference 7.

18

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Verwachtingenbrief (Expectation Letter) (2/5/2018)
A verwachtingenbrief (Expectation Letter) was sent to NAM on 2nd May 2018 (Ref. 8) by the Minister
of Economic Affairs and Climate Policy. It detailed the expectations for further NAM technical studies
in preparation of a new Winningsplan decision (due by 15th November 2018 latest). NAM was
requested to perform a Hazard and Risk Assessment for the “Basispad Kabinet” production profile, to
indicate the impact of the strong reduction of production on safety risk and the scope of the structural
upgrading needed to comply with the Meijdam-Norm (Ref. 9 to 11). With the verwachtingenbrief
(Expectation Letter) the Minister of Economic Affairs and Climate Policy has provided the Groningen
gas-quality demand production profile dataset (Fig. 1.3) to NAM which served as basis for the Hazard
and Risk Assessment for the production profile “Basispad Kabinet” (Ref.12). In an addendum to the
verwachtingenbrief (Expectation Letter), the request was further described (Ref. 8):

Figure 1.3

“Basispad Kabinet” for the annual production from the Groningen field, Kamerbrief (29/3/2018) (Ref. 7
(dashed lines) versus Verwachtingenbrief (Expectation Letter) (2/5/2018) (Ref. 8) (solid lines). Note small
differences in the first two gas-years.

Following the report on the Hazard and Risk Assessment for “Basispad Kabinet” (Ref. 12), three
supplementary reports were published, on subsidence (Ref. 13), building damage (Ref. 14) and impact
of tectonic stresses on the hazard and risk (Ref. 15). The Hazard and Risk Assessment November 2017
(Ref. 5) and the following addenda to this report (Ref. 12 to 15) to assess the impact of the production
profile “Basispad Kabinet” were all based on the same workflow and version of the Hazard and Risk
Model.

Kamerbrief - Voortgang maatregelen gaswinningsbrief (6/6/2018)
On 6th June 2018, the Minister of Economic Affairs sent a letter to Parliament informing on the progress
of the measures to end production from the Groningen field (Ref.16). In this letter, a number of
additional measures are referenced that were not yet incorporated in the “Basispad Kabinet” as
presented on 29th March 2018. The risk impact of a profile based on the maturation of these additional
measures to reduce Groningen gas demand was not assessed but would directionally have reduced
19

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

the risk further as compared to the Hazard and Risk Assessment based on the production profile
“Basispad Kabinet” (Ref. 12).

Production Profile GTS-raming February 2019
Actual production realised in gas-year 2018-2019 was 18.8 Bcm compared to 19.4 Bcm in the
production profile of “Basispad Kabinet”. This 0.6 Bcm lower production has been included in this
Hazard and Risk Assessment.
On 12th February 2019, NAM received the verwachtingenbrief (Expectation Letter) with the updated
production profile prepared by GTS: “GTS-raming 2019” (Ref. 17). In figure 1.4 the annual production
rates for the three production profiles (Basispad Kabinet March 2018 Letter, Basispad Kabinet
Expectation May 2018 Letter and verwachtingenbrief (Expectation Letter) February 2019) are
compared. The comparison is shown in this figure for cold, average and warm year gas demand.

20

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Basispad Kabinet (March 2018)
Verwachtingenbrief (May 2018)
Verwachtingenbrief (Feb. 2019)

Figure 1.4

Comparison of the production profiles “Basispad Kabinet” from Kamerbrief (29/3/2018) in blue (Ref. 7),
“Basispad Kabinet” from the verwachtingenbrief (Expectation Letter) (2/5/2018) in red (Ref. 8) and the new
production profile GTS-raming 2019 in green (Ref. 17). The upper graph shows comparison for cold (koud)
year gas demand, the middle for average (gemiddeld) year gas demand and the bottom for warm (warm) year
gas demand.

In the first three years, the new GTS-raming 2019 is considerably lower than the other production
profiles. For a cold temperature year demand, the GTS-raming 2019 is approximately 3 Bcm below the
Basispad Kabinet (verwachtingenbrief) for this period. For the average temperature year demand, this
difference is approximately 2.5 Bcm per year.

21

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

2

HRA-Model Improvements

Introduction
A number of improvements and changes have been implemented in this Hazard and Risk Assessment
relative to the previous version based on production profile Basispad Kabinet (Ref.12). These
improvements and changes are:

The software implementation of the HRA-tool based on the programming code in the Clanguage has been used (Ref. 18). Previously often the implementation using the Pythonprogramming language was used with the implementation based on the C-programming
language used for validation. Due to the tight deadline for this report (6 weeks after the
production profile GTS-raming 2019 was received), the faster implementation of the HRA-tool
using programming code in the C-language was used in the preparation of this report. The
impact of this change is very small.

To capture the epistemic uncertainty, the logic tree with 7 branches for the maximum
magnitude of the earthquakes was used. In the report on the Hazard and Risk Assessment based
on production profile Basispad Kabinet (Ref.12), the assessment was based on a condensed 3branch description of this uncertainty, with the results for the 7-branch description of this
uncertainty in the logic tree described in an appendix.

The Exposure Database, containing the description of the houses in the Groningen region, was
continuously updated throughout 2018. The current hazard and risk assessment is based on
version 6 of the exposure database. The improvements are described later in this section.

The fragility curves describing the chance of partial and full collapse for buildings in a typology
was further refined for several typologies. This further development of the fragility curves was
based on the recommendations made in the Assurance Workshop (Ref. 19).
The last two improvements will be further described in this section.

Exposure Database
To be able to assess the risk for the buildings and community in Groningen resulting from induced
earthquakes, knowledge of the occupied building stock in the region of the Groningen field is required.
To assign unique building typologies to each individual building in the earthquake area, a program of
building inspections was initiated in 2013. The program consists of the collection of building data from
existing databases and data sources. This is supplemented by building data gathered from public
sources (e.g. observation from public areas (street level) and Google Street View) and engineering
drawings of buildings, publicly available at the municipality office. The taxonomy of building typologies
of GEM (Global Earthquake Model) is used to assign typologies, based on the structural system of each
building.
For practical reasons the Groningen field area has been divided in two areas4. The core area consists
of the seismically most active area and contains some 20,000 buildings. Additionally, data on the use
of the buildings and occupancy are collected. The data on the buildings in the Groningen field area are
stored in the exposure database (EDB). An earlier version of this database (V2) (Ref. 20) was used for
the Hazard and Risk Assessment of November 2015 (Ref. 21) and Hazard and Risk Assessment for
Winningsplan 2016 (Ref. 1). Early 2017 and mid-2018, updated versions of the database were issued

4
These areas have been introduced by the NCG based on a hazard map of KNMI. The 0.2 g contour of the 2015 KNMI hazard map was chosen
as the boundary between these areas.

22

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

(Ref. 22, 23 and 24). The exposure database of mid-2018 (Ref. 22) was used in the Hazard and Risk
Assessment for the production profile “Basispad Kabinet”, which was issued June 2018.
The exposure database combines many data sources (BAG, AHN, Deltares top soil, etc.) together with
inference rules to assign typologies to individual buildings. The datasets used for the EDB are
categorised as follows:

Source data Datasets which have been received and maintained by external sources such as
government departments.

Project data Datasets which have been produced within the project such as inspection datasets
and desktop studies. This includes project information produced by ARUP and external
consultants.

Processed data Datasets which ARUP has created utilising source datasets, assumptions and
analysis to provide information that is not available from external sources.
This leads to a non-unique typology description for many buildings. In the core area, almost every
building has a unique typology assigned. Away from this area, the typology of many buildings is based
on inference rules, reflecting the experience of local engineers with the knowledge of the development
of local building methods. These inference rules are also updated in light of the on-going building data
gathered. The Hazard and Risk (HRA) model applies the assessed earthquake hazard to the buildings
and the population in the exposure database to assess the earthquake risk. The inference rules will in
most cases not be able to establish the building typology uniquely and will assign a number of
typologies to the building, each with a probability. On a regional level this provides a reliable
assessment of the number of buildings where the safety-norm is exceeded and a risk-based ranking of
all building in the Groningen field area.

Recent activities to improve the expose database
The exposure database is continuously improved. For this hazard and risk assessment version 6 of the
exposure database has been used. This section describes the improvements implemented in version
6.
NAM has published reports on the progress of this activity in July and September 2018 (Ref. 23 and
24). Especially for the buildings high on the risk-based ranking the typology has now been assigned
with confidence. This improvement program of building inspections executed primarily by ARUP has
continued with the release of the Exposure Database version V6, ready for use in this update of the
Hazard and Risk Assessment.
1.
Existing data has been gathered through, 14,000 Rapid Visual Screening (RVS), 800 Extended
Visual Screening (EVS) and 15,000 Arcadis damage inspection records.
2.
CycloMedia, HORUS companies provided a service whereby images from the building stock were
used (or specifically gathered) and computer processed to determine properties of the building
façade. This can be used to determine similarities between buildings, window surfaces in the
façade (% or m2), height, aspect ratio, degree of tilt etc. The effort was further extended in the
second half of 2018 by Ticinum Aerospace which has, based on analysis of publicly available
photo’s, further improved the assessment of building characteristics such as number of floor
levels and window openings (Fig. 2.1).
3.
Collection of Building Drawings to validate and confirm knowledge of buildings. Focus was
recently on the collection of data on apartment buildings and buildings with any probability of
having higher risk (see also item 5 below).

23

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

4.
5.

Neighbourhood check – Buildings with similar geometric properties and construction year will
be compared.
Re-evaluate buildings with low probability of belonging to a vulnerable typology. This exercise
has led to identification of additional vulnerable buildings, also in the core area. Especially,
buildings with a typology with a mixed structural system or belonging to multiple typologies (one
of which is a vulnerable typology) have been assessed in detail.

Figure 2.1

The CountFloor service of Ticinum can automatically extract building features by analysing street-level pictures

As part of the efforts to improve the Exposure Database some 190,000 documents have been collected
primarily from municipality archives, building associations and owners (Tab. 2.1) on various building
aspects (Tab. 2.2).
Source

Table 2.1

Number of
Documents

Municipalities
Building Associations
Owners
Other Sources

177,390
4,348
15
7,373

Total

189,126

Number of documents collected to improve the Exposure Database split by source.

24

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Document

Others

Calculations
Secondary Buildings
Soundings
Details
Reckoning Calculations
Floors
Foundations
Others
Building Requests
Renovations
Technical calculations
Situations
N/A
Undefined
Table 2.2

Municipality

16
19

350

9,629
1,044
2,304
3,269
33,351
14,208
17,130
3,447
15,502
37,753
15,105
10,941
4,707
9,000

7,373

177,390

114
1,001
1,207
589
3,052
319
14
141
551

Building
Associations

Owners

Total

1

9,792
1,063
2,375
3,849
34,916
15,707
17,944
8,500
15,901
37,799
15,373
11,834
4,723
9,350

146
71
466
561
290
225
2,001
80
24
126
342
16

3
2

8
1

4,348

15

189,126

Number of documents collected to improve the Exposure Database split by building aspect.

More than 350 visits have been made to the municipality archives (Tab. 2.3) to collect this building
data.
Municipalities
Appingedam
Delfzijl
Hoogezand
Slochteren
Loppersum
Eemsmond
Ten Boer
Bedum
De Marne
Aanvullend
Groningen
Winsum
Oldambt
WoCo
Total
Table 2.3

Appartment
7
3
4
2
2
4
1

23

Terraced
Buildings
20
19
6
15
13
14
3
1
5

96

Detached
Building
37
39
1
27
54
36
29
2

Total

5
1
1
2

64
61
5
35
71
53
44
5
1
5
5
1
1
2

234

353

Number of visits to municipality archives split by studies on Apartments, Terraced Buildings and Detached
Buildings.

An important source of information are the results of the Engineering inspections carried out on behalf
of NCG/CVW for the strengthening campaign. Unfortunately, this data source is not available to NAM.

25

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Conclusions and general results of the studies
For the vast majority of the buildings high on the risk-prioritised list of buildings in the Groningen area,
the unique typology has been established. This is the direct result of all activities described above.
Figure 2.2, which is similar to figure 2 in “Exposure Database (EDB) voor het gebied van het Groningen
veld - Stand van Zaken - september 2018” (Ref. 24), shows the data sources available to assign each
typology. Further improvements are difficult to realise because they would require inspection inside
the buildings.

Figuur 2.2

Data sources used to assign Structural Systems to buildings of the “Mijnraad 1500” list, based on production
profile “Basispad Kabinet”. The figure shows that more deterministic building specific data has been used than
before.

Fragility and Consequence Models for building typologies
A full overview of the development of the fragility curves describing the response of buildings for each
building typology and the further development of these during 2018 is provided in the January 2019
version of the “Study and Data Acquisition Plan induced seismicity Groningen” (Ref. 25) and in the
specific report on the topic [Ref. 49]. Although the results of experiments carried out in 2018 have
contributed to the further development of the fragility curves, in this report we’ll focus on the
development of the fragility curves themselves.
As with the other components of the hazard and risk assessment, the fragility and consequence models
have been regularly updated and documented. Version 2 of the fragility and consequence models was
used for the hazard and risk assessment supporting the Winningsplan 2016 (Ref. 26). This version was
shared with experts in structural modelling, fragility and risk assessment in a first assurance review
that took place in November 2015.

26

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

The previous version of the fragility and consequence models, version 5, uses SDOF models calibrated
using the dynamic analysis results of index buildings, as presented previously (and documented in Ref.
27). Elastic springs and dashpot dampers at the base of the SDOF account for the effects of soilstructure interaction (i.e. foundation-soil flexibility and damping) (Ref. 28). The SDOF models are
subjected to hundreds of accelerograms (cloud analysis) and regression analysis is undertaken to relate
the characteristics of the accelerograms (spectral acceleration at varying periods of vibration,
significant duration) with the nonlinear displacement response.
Fragility functions that describe the probability of exceeding a given threshold of damage, conditional
on a level of ground shaking can then be developed from the aforementioned regression analysis and
by identifying the value of displacement at which different damage and collapse states occur. The
thresholds for damage states DS2 and DS3 of URM and reinforced concrete structures have been
obtained from the experimental activities described previously, whereas the collapse state thresholds
are obtained via explicit collapse modelling within the numerical software used to model the index
buildings.
In addition to structural collapse, chimney collapse fragility functions have also been developed using
empirical data from a number of earthquakes including Liege (1983) and Roermond (1992) (Ref. 29,
30). Consequence models (i.e. the probability of loss of life inside or outside the building, given
collapse) for both structural and chimney collapse were also developed considering the percentage of
internal/external floor area covered in collapsed debris (Ref. 27).

Study activities following assurance meeting
The experimental and numerical work described above, which led to version 5 of the fragility and
consequence models, was subjected to a second assurance review that took place in February 2018.
The recommendations laid out by the Review Panel in their Assurance Letter (Ref. 19) played an
important role in the definition of the further activities currently being carried out or planned for 2019.
Below, such activities are first listed, and then further discussed, where pertinent.












Shake-table testing of full-scale structural subassemblies under triaxial input motions (i.e.
simultaneous application of two horizontal components plus the vertical one), so as to validate
the accuracy of the employed structural modelling approaches under such loading conditions.
Use of the outputs of the blind predictions to quantify the fidelity of the structural models
employed in the fragility functions derivation, and thus constrain the uncertainty bounds used
in the associated logic tree.
Undertaking of sensitivity and parametric studies to understand the impact of modelling
assumptions regarding issues such as e.g. wall-to-wall and wall-to-diaphragms connections,
foundations flexibility, openings, non-structural partition walls.
Use of hazard consistent ground motions (conditional on spectral acceleration at specific periods
of vibration as well as Average Spectral Acceleration, AvgSa) for both the modelling of index
buildings and the development of fragility functions.
Employment, in the SDOF analyses used to derive the fragility functions, of a more advanced
Soil-Structure-Interaction (SSI) model, so that effects such as nonlinear soil response and failure
are taken into account.
Validation of the SDOF approach employed to derive the fragility functions for the entire set of
structural systems, through a comparison, for one or two structural systems, against fragility
functions developed directly from multi-degree-of-freedom (MDOF) models.

27

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019


Scrutiny of fragility and consequence models through history checks on damage and fatalities
(by repeating all earthquake events with local magnitude greater than 2.5 that have been
measured in the field), and through comparisons against other published models from around
the world (with a critical evaluation of the differences).

With regards to the first of the further activities listed above, it is noted that shake-table tests
conducted so far have highlighted and confirmed how the out-of-plane (OOP) behaviour of loadbearing walls may be influenced by boundary conditions and how these may vary due to effects of
multi-directional input. The impact of the vertical acceleration on the out-of-plane performance of
slender walls, parapets and chimneys will hence be investigated through tests on similar subassemblages/structures subjected to unidirectional and multidirectional motions. Further, the tests
previously carried out have also highlighted that laterally supported walls subjected to OOP behaviour
(i.e. two-way-bending) resulted to be very sensitive to the damage state of the panel itself and of its
lateral connections; undamaged panels had a low vulnerability while it increased considerably for
damaged ones. Hence, relatively complex assemblages will be tested to study the combined effect of
in- and out-of-plane excitation and interaction with perpendicular elements (damage due to flange
effect). The influence of vertical motion will be studied also in these cases.

1D motion
Pure OOP oneway bending
behaviour with
variation of
element boundary
condition

Study of the OOP behaviour
of chimneys and parapets

Study of in plane behaviour of
piers
Study of the flange effect and
two-way bending behaviour

2D motion
OOP one-way
bending
behaviour with
variation of
element boundary
condition also due
to in-plane
deformation

Study of the 2D OOP behaviour
of chimneys and parapets

Study of combined in-plane and
OOP behaviour
Study of the OOP behaviour facilitated by
by possible in-plane cracking

28

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

3D motion
OOP one-way
bending
behaviour with
variation of
element boundary
condition also due
to in-plane
deformation and
vertical
acceleration

Study of the influence of the vertical
acceleration on the OOP behaviour of
chimneys and parapets

Study of combined in-plane and
OOP behaviour
Study of the OOP behaviour facilitated by
by possible in-plane cracking

Figure 2.3

Rationale and objectives for the envisaged further multi-direction shake table tests

For what concerns the second of the further activities listed above, regarding the analysis of the blind
predictions outcomes in order to assess the fidelity of the structural models currently employed in the
fragility model (and to then constrain the uncertainty bounds used in the logic tree), the plan is to
systematically compare the predicted collapse displacements (from each given software/modelling
approach) with those observed in the tests, so to quantity the bias and variability in the predictions.
An example of such an exercise is shown in Fig. 2.4 below, regarding the blind predictions carried out
for the testing of EUC-BUILD6 specimen.

Figure 2.4

Comparing blind-predictions with experimental results for EUC-BUILD6

Finally, for what concerns instead the planned improvements on the SSI modelling approach employed
in the SDOF analyses used to derive the fragility functions, this involves a review and verification of
alternative approaches, including e.g. lumped parameter elastic models (Fig. 2.5), nonlinear macroelement models (Fig. 2.6), soil box analyses under MDOF models, etc. In addition, the now available
140.000 soil profiles created within the framework of the Ground Motion Model development are also
to be considered in the derivation of the stiffness and strength input properties for the SSI models.

29

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 2.5

Figure 2.6

The lumped parameter elastic SSI model

Example of literature-available validation of the nonlinear inelastic macro-element SSI model.

30

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Summary of main improvements to the fragility curves – Version 6
The following activities, as recommended by the International Expert Review Panel (Ref. 19) have been
undertaken:












Further validation of the SDOF models using the MDOF models has been made.
The SDOF model has been used in the blind prediction of the EUC-BUILD6 test (which represents
the typology with one of the largest number of buildings).
The impact of foundation failure on the MDOF models has been investigated.
The simple spring/dampener used to model soil-structure interaction has been replaced by a
more advanced macro-element model that more directly accounts for nonlinear soil response
and failure.
Hazard consistent records have been selected for the development of fragility functions.
The records are conditioned on different levels of AvgSa, an intensity measure that is common
for all building typologies and that now allows direct comparisons between fragility functions to
be made (to aid validation).
The fragility functions have been derived in terms of PGA and compared with other models from
the literature (for further validation).
The damage state thresholds used for the damage fragility functions have been updated based
on the latest experimental test results.
History checks have been undertaken to estimate the expected damage/loss using ShakeMaps
from the largest events as well as the full event catalogue.

In addition, more index buildings have been studied and used in fragility function development, in
particular:







URM1L and URM3M typology divided in sub-typologies recognising the fact that the variation
with respect to seismic behaviour within these typologies was still relatively large
URM3M_D (drive-in buildings) now explicitly modelled with 2 index buildings (rather than
mapped to URM3M_U: 3 storey town house with cavity walls and concrete floor).
URM5L (terraced house with timber floors and cavity walls) is now explicitly modelled (rather
than mapped to URM8L, detached house with cavity walls and timber floors).
URM3L (terraced house with concrete floors and cavity walls and low % of openings) is now
represented by two index buildings.
PC3L (pre-cast terraced houses) have now been modelled with 2 index buildings.
URM9L (URM building with steel frames at ground floor) is now modelled with an index building.

31

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

3

Production Profile

Production profile: Demand profiles GTS-raming 2019
Demand profiles were provided by the Ministry of Economic Affairs and Climate Policy, by means of a
verwachtingenbrief (Expectation Letter) dd 12th of February 2019, representing the Groningen-quality
gas demand in excess to the other L-gas supply sources. The demand profiles are presented on a daily
level during either a cold, average or warm temperature gas-year for the individual gas-years in the
period up to the 30th of September 2029. The appendix “uitgangspunten volumeberekeningen” to the
GTS document “Raming benodigd Groningenvolume en capaciteit gas-jaar 2019/2020 en verder”
states that the average utilisation of the GTS nitrogen plants Ommen, Wieringermeer and Zuidbroek
(if available) is assumed to be 92.5%. Hence the subset of the full dataset, identified as “G+N+A 92.5%”
is selected to represent the demand profiles for the Hazard and Risk Assessment (see Figure 3-1).
The demand profiles do not distinguish between gas produced from Groningen field, UGS Norg or PGI
Alkmaar, nor does it recognise the volumes required for injection in UGS Norg. Pre-processing of the
dataset was required to redistribute contribution between UGS Norg, PGI Alkmaar and Groningen field.
Redistribution processing is performed by GasTerra, as they have knowledge on the L-gas market
demand throughout the year and determine the use of the L-gas resources in its portfolio and the
deployment of the Groningen field to allow the L-gas market to function. It assumes the underground
gas storages UGS Norg to be volume neutral over the gas-year, because it is filled with gas from the
Groningen field in summer which gets produced during cold periods in winter. Furthermore, it is
assumed that the PGI Alkmaar facility is available for production in the period October till March and
is filled with pseudo-G-gas during the period April – September.
The applied methodology to determine the utilisation of Groningen system assets is based on perfect
insight on the future temperature profile (e.g. weather conditions are upfront known for every single
day in the future). This perfect foresight assumption is a deterministic approach and is similar to the
methodology applied by GTS. This Groningen system assets utilisation outcome is therefore to a degree
theoretical and does not cater for certain market uncertainties.
GasTerra has reported the daily volumes required from the Groningen field for each of the individual
gas-years and the 3 temperature profiles (cold, average and warm). As the hazard and risk assessment
requires monthly time steps, the daily volumes have been converted to monthly volumes to be
produced from the field. The graphs below show both the full G-gas demand and the Groningen field
production volumes on a monthly basis. The requirement to fill Norg UGS in the summer has a
flattening effect on the Groningen field production profile (see Figure 3-1).

32

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 3-1 Monthly G-gas demand based on GTS estimate (blue line) and Groningen field volumes after reprocessing by
GasTerra (in green) for warm, average and cold gas-year.

The resulting net production from the Groningen field is given in Figure 3-2 and Figure 3-3.

Figure 3-2:

Groningen field production profile by month

33

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 3-3:

Groningen field production by Gas-year

Spatial distribution of production (Operational Strategy)
Optimisation of production distribution to minimize seismic hazard and risk
On 1/10/2018 NAM issued the 2018 update of the Production Optimisation study to SodM (Ref. 31).
In this study, NAM investigated whether the seismic hazard and risk in Groningen could be influenced
by the distribution of production across the production locations and at which distribution of the
determined production volume the seismic risks would be minimized as much as possible over the
period 2018-2022. Various optimisation metrics were investigated (e.g. event count, maximum Peak
Ground Acceleration, etc).
In a letter to the Ministry of Economic Affairs on 16/10/2018, SodM advised the Minister to use NAM’s
2018 optimisation study to steer the production distribution in the field (Ref. 32). Production
distribution as calculated for the optimisation metric “population weighted Peak Ground Velocity” was
judged to minimize the seismic risks over the entire Groningen gas field in a socially responsible
manner. This distribution resembles “Operational Strategy 1” in NAM’s 2018 “Bouwstenen document”,
the document which outlines options for the Operational Strategy of Gas-year 2018/2019 (Ref. 34).
“Operational Strategy 1” was adopted as the operational strategy of choice in the 14/11/2018
Ministerial Instemmingsbesluit (Ref. 33).
For this 2019 HRA update, NAM was requested by the Ministry of Economic Affairs (Ref. 17) to define
two Operational Strategies, based on two specific volume distribution strategies (spatial distribution
of production) as described in the 2018 NAM production optimisation study (Ref. 31), being the
Populated weighted peak ground velocity strategy and the Event count strategy. These two strategies
are requested to be evaluated for three temperature profiles.

Strategy definition
x

Strategy 1 – Population weighted Peak Ground Velocity
Strategy 1 distributes the production in order to minimize the population weighted Peak Ground
Velocity (see spatial overview of production start-up order in of production clusters, Figure 3-4
left-hand side). Gas is produced preferentially from the South-East, if more production is
required clusters are opened in South-West and Central-East region. Cluster Bierum is kept at a
stable rate whereas cluster Eemskanaal is used as capacity provider. This strategy resembles the
strategy as selected by the Minister in Instemmingsbesluit 2018 and in gas-year 2018/2019
operationalized by NAM.

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Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

x

Strategy 2 – Event count
Strategy 2 distributes the production in a way to minimize Event count. Gas is preferentially
produced from the South of the field (see spatial overview of production start-up order in of
production clusters, Figure 3-4 right-hand side). Starting in the South-East, opening-up
additional clusters from South-West and cluster Eemskanaal. Clusters in the region Central-East
and cluster Bierum are opened only at a higher production demand.

In order to be able to control production distribution a cluster start-up order is being applied in the
model. For both strategies a different sequence is used, see Table 3-1. The modelled cluster utilisation
(monthly times steps) might differ from the day-to-day cluster utilisation because of daily production
fluctuations and operational constraints.

Figure 3-4:

Spatial overview of production start-up sequence when optimising for pwPGV (left-hand side) and for Event
count (right-hand side). Source: Ref.31

Temperature profiles
As per the updated Mining Law (Article 1.3a.2), the verwachtingenbrief requested evaluation for three
temperature profiles:
x
x
x

Average temperature
Cold temperature in gas-year 2019/2020, followed by average temperatures for subsequent
years
Warm temperature in gas-year 2019/2020, followed by average temperatures for subsequent
years

These demand profiles have been constructed from the data as provided by the Ministry of Economic
Affairs and Climate Policy, by means of the verwachtingenbrief (Expectation Letter) dd 12th of February
2019.
Hence in total 6 profiles were requested by the Ministry.

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Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Production regions
In Article 1.3a.1 of the updated Mining Law, the production regions are defined:
x
x
x
x
x
x

East-Central (clusters Amsweer, Tjuchem, Oudeweg, Schaapbulten, Siddeburen)
South-East (clusters Scheemderzwaag, De Eeker, Zuiderpolder)
South-West (clusters Kooipolder, Slochteren, Spitbergen, Tusschenklappen, Zuiderveen)
Loppersum (clusters Leermens, Overschild, Ten Post, De Paauwen, ’t Zandt)
Eemskanaal cluster
North (Bierum cluster)

Similar to the June 2018 hazard and risk assessment, for this HRA update further granularity was
applied within regions East-Central and South-West. This additional granularity allows for optimisation
of production within the (larger) regions and reflect operational conditions (lower number of clusters
in operation when low demand), see Figure 3-5.

Production regions

Figure 3-5:

Production controls

Production regions and control groups as used in the start-up list

Model implementation
Start-up order
To control the volume off-take for the regions (spatial distribution) a production cluster start-up
sequence has been implemented in the model (see table 2.2). The surface network model sequentially
opens-up (groups of) clusters following the start-up sequence until the total required production
demand is achieved.

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Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Table 3-1:

Production start-up list for achieving total required field production. Starting from the top of this list, groups
of clusters are sequentially opened-up by the surface network model until the total required production can
be achieved.

Load Factor
The second parameter to control volume off-take per region (spatial distribution) is the Load Factor.
The Load Factor is the ratio of cluster production to maximum cluster capacity. It is calculated for each
individual cluster at every timestep and a maximum value can be set as a constraint in the surface
network model. A high maximum load factor will maximize volume withdrawal from clusters high in
the start-up sequence, but at the same time also increase production fluctuations from clusters low in
the start-up sequence (due to fluctuating demand).
A pre-set maximum load factor of 70% has been used in the model, in order to reflect the daily
operational situation. This load factor assumption is considered a challenging achievement as it
includes all scheduled and unscheduled production deferments. Daily production fluctuations have not
been encountered for in this analysis, as hazard and risk assessment is based on monthly time step.

Modelling setup
Dynamic reservoir model (Mores model V5)
For establishing the reservoir pressure response to the various production profiles, the V5 Mores
dynamic reservoir model was used (Ref.35). This is the same model as was used for the June 2018 HRA
(Ref.12) and for the 2018 Production Optimisation study (Ref.31). The history match was updated with
actual production data up to 31/12/2018.

Production data 1/1/2019 to 30/9/2019
All profiles have a common starting point, the start of gas-year 2019/2020. It is assumed that up to
1/10/2019 production will take place as per the 14/11/2018 Instemmingbesluit for average
temperature.

Surface network model (Genrem)
The capabilities of the surface facilities are reflected through the Genrem surface network model (as
implemented for the June 2018 HRA).

Production considerations
Loppersum production
In line with the 14/11/2018 Instemmingsbesluit, the Loppersum clusters are not used for production.

37

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Eemskanaal production
The Eemskanaal cluster is used as capacity provider in Operational Strategy 1. It is only used to meet
capacity demand. The Eemskanaal cluster is produced at an annual total of 100 mln Nm3 in winter
months only (on a stand-by rate), and shut-in over summer. It is assumed the Eemskanaal cluster is
shut-in from gas-year 2022/2023 onwards.
For strategy 2, the Eemskanaal cluster production is led by the start-up list.
Bierum production
In strategy 1, the Bierum cluster production is kept at a base-load rate of 6 mln m3/d in gas-year
2019/2020, and in subsequent years proportional scaled down with total annual volume. From gasyear 2022/2023 onwards Bierum is assumed to be fully shut-in.
For strategy 2, the Bierum cluster production is utilised as per the start-up list.

Production Fluctuations
For both operational strategies (see Strategy Definition) a fluctuation analyse has been performed for
gas-year 2019/2020. GTS has provided the Groningen system demand (Groningen plus UGS Norg) for
30 historical temperature profiles for gas-year 2019/2020. Groningen field demand has been
calculated in a post-processing by GasTerra (see Demand profiles GTS 2019).
Two indicators to monitor production fluctuation are compared to the average produced monthly
volume over the preceding 12 months and month-on-month production fluctuation. The bandwidth
of the fluctuation limits for both indicators is set at +/-50% for the regions South-East, South-West and
Central-East. For the Bierum region a bandwidth of +/-20% applies to both indicators.
The production fluctuation analysis is performed in daily steps. For 30 temperature profiles the daily
Groningen field demand is distributed over the production clusters following the production start-up
list (see Table 3-1).
The production fluctuation indicator based on the average produced monthly volume over the
preceding 12 months describes the difference of volume produced during one month in a region with
the average monthly volume over the 12-month period preceding the relevant month for the
respective region. This difference is expressed in a percentage with the average monthly volume over
the 12 preceding months as a reference. An overrun of the fluctuation bandwidth occurs if the volume
is not within that bandwidth in one month.
A month-on-month production fluctuation is the difference of volume produced during one month in
a region with the volume produced in that same region in the preceding month. This difference is
expressed in a percentage with the volume of the previous month as a reference.
Fluctuations are reported in region months with 5 regions and an analyse period of 30 we have 5 * 12
* 30 = 1800 region months.

38

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

x

Strategy 1 – Population weighted Peak Ground Velocity

Figure 3-6

Strategy 1 production fluctuations for the regions Bierum, Central-East, Eemskanaal, South-East and SouthWest for both rolling 12 month average and month-to-month indicator. The line shows monthly volume and
the area indicates the allowed bandwidth. Exceedance is of bandwidth is indicated with marker (triangle
relates to month-to-month, square relates to rolling 12 month and dot relates to both).

In this operational strategy 403 of the 1800 region months (or 22%) are found with an exceedance of
the fluctuation limits. The re-occurring month-to-month exceedance in Bierum is caused by the
production stop scheduled in October 2019. The frequent exceedances in region Central-East are
caused by the start-up sequence in this strategy.
x

Strategy 2 – Event count

Figure 3-7

Strategy 2 production fluctuations for the regions Bierum, Central-East, Eemskanaal, South-East and SouthWest for both rolling 12 month average and month-to-month indicator. The line shows monthly volume and
the area indicates the allowed bandwidth. Exceedance is of bandwidth is indicated with marker (triangle
relates to month-to-month, square relates to rolling 12 month and dot relates to both).

In this operational strategy 828 of the 1800 region months (or 45%) are found with an exceedance of
the fluctuation limits. The frequent exceedances in Bierum and Central-East are related to the startup sequence, as these regions are only used for production in periods with higher Groningen gas
demand.
Production fluctuations are (mainly) caused by variation in Groningen volume demand, every
operational strategy investigated shows a certain level of occurrences of exceedance. The production

39

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

fluctuations could be minimized or even set to zero by increasing the volume offtake of the
Groningen field.

Production profiles
Reference case (IB2018)
As a reference case for the new production profiles, the Basispad Kabinet is used as defined by EZ in
the 2/5/2018 Verwachtingenbrief and approved on 14/11/2018 in the Ministerial InstemmingsBesluit
(IB2018), Figure 3-8. Note that the history match of the dynamic reservoir model was updated to
reflect the actual production up to 31/12/2018. From 1/1/2019 onwards the exact same production
(distribution) was imposed on the model. This introduces small differences with respect to the 2018
evaluation of the same profile5.
Figure 3-9 gives the reservoir pressure at 1/1/2019, and the depletion over the next 5 years (1/1/2019
to 1/1/2024). The pressure starting point has a reasonable gradual gradient within the gas closure
(black outline) and lagging depletion within the lateral aquifer. Due to the reducing offtake rates over
the next 5 years, pressure depletion in the vicinity of the field is allowed to catch-up a little with respect
to the gas closure. There is no production from the FRB/KPD/SLO clusters, nor from the EKL cluster.
This allows the higher pressured South-Western Periphery (EKL area) to recharge the South-West area,
resulting in a notable absence of depletion in the latter area over the five-year period, Figure 3-10.

5

As explained in Reference 12, there are small differences between the Basispad Kabinet as issued by the
Ministry on 29/3/2018, and the Basispad Kabinet as issued by the Ministry on 2/5/2018 with the
Verwachtingenbrief. Specifically for gas-year 2018/2019 at average temperature, a Groningen production
volume of 19.4 N.Bcm is quoted on 29/3/2018, based on an average of 85% and 100% nitrogen utilization by
GTS. In the supporting GTS analysis (Advies GTS leveringszekerheid middels scenario analyse, 27/3/2018) a
volume of 20.6 N.Bcm is quoted at a 85% nitrogen utilization. The 2/5/2018 Verwachtingenbrief quotes a volume
of 20.4 N.Bcm. The actual volume used in this analysis is 20.7 N.Bcm, because the models are updated with the
actual production for the period October-December 2018 (from January 2019 onwards, the production profile is
exactly as per the 2/5/2018 Verwachtingenbrief).

40

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 3-8:

Production as per 14/11/2018 Instemmingsbesluit

41

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Reservoir Pressure (1/1/2019)

Figure 3-9:

Depletion (1/1/2019 to 1/1/2024)

Reservoir pressure at 1/1/2019

42

Figure 3-10:

Cumulative depletion from 1/1/2019 for the next 5 calendar years, top left hand graph to 1/1/2020, bottom-centre graph to 1/1/2024

43

Strategy 1 (pwPGV) – Average Temperature
A production overview for Strategy 1 is given in Figure 3-11. Figure 3-12 shows the gas production
versus the production capacity by region, and their ratio (Load Factor). It clearly brings out that the
South-East area (EKR/SZW/ZPD) is utilized at its maximum assigned Load Factor.
When comparing the associated pressure maps from Strategy 1 (pwPGV) to the reference case
(IB2018), the reduction in total volume offtake dominates the reservoir pressure response. Field-wide,
there is some 1 bar less depletion by 1/1/2024.

Figure 3-11:

Production distribution for Strategy 1 (pwPGV), Average temperature

44

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 3-12:

Utilisation of the various production regions for the population weighted PGV, average temperature
(16_pwPGV_avg)

Figure 3-13:

Reservoir pressure at the production clusters for Strategy 1 (pwPGV), average temperature.

45

46

Figure 3-14:
Difference in depletion between Reference case (14/11/2018 Instemmingsbesluit) and Raming GTS 2019 for Strategy 1 (production distribution optimised for pwPGV).
Cumulative difference in depletion given from 1/1/2019 for next 5 calendar years, top left-hand graph to 1/1/2020, bottom-centre graph to 1/1/2024.

Strategy 1 (pwPGV) – Cold temperature year
For the cold temperature year in gas-year 2019/2020, Strategy 1 starts to call more upon the westernmost clusters within the South-West region to meet the production demand (clusters FRB/KPD/SLO).
This clearly stands-out in Figure 3-18 for 1/1/2019 and 1/1/2020. In later years, the additional
depletion in that area dissipates over the greater gas closure with respect to the average temperature
profile.

Figure 3-15:

Production distribution for Strategy 1 (pwPGV), cold temperature year.

47

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 3-16:

Utilisation of the various production regions for the population weighted PGV, cold temperature year.

Figure 3-17:

Reservoir pressure at the production clusters for Strategy 1 (pwPGV), cold temperature year.

48

Figure 3-18:

Pressure slices comparing Strategy 1 (pwPGV) for the cold temperature year versus the average temperature profile.

49

Strategy 1 (pwPGV) – Warm temperature year
For the warm temperature year profile, Strategy 1 utilizes the South-West and East-Central regions
less as compared to the average temperature profile, Figure 3-19 to Figure 3-22.

Figure 3-19:

Production distribution for Strategy 1 (pwPGV), warm temperature year.

50

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 3-20:

Utilisation of the various production regions for the population weighted PGV, warm temperature year.

Figure 3-21:

Reservoir pressure at the production clusters for Strategy 1 (pwPGV), warm temperature year.

51

Figure 3-22:

Pressure slices comparing Strategy 1 (pwPGV) for the warm temperature year versus the average temperature profile.

52

Strategy 2 (Event count) – Average Temperature
Strategy 2 optimises for Event count, and targets production along the Southern area of the field,
Figure 3-23. It starts production from the South-East and with increasing production demand gradually
ramps up towards the South-West. The difference in production strategy clearly stands out from Figure
3-26, showing the increase in depletion in the South-West versus the reduction in depletion in the
North-East as compared to Strategy 1 (both for average temperature production).

Figure 3-23:

Production distribution for Strategy 2 (Event count), average temperature.

53

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 3-24:

Utilisation of the various production regions for Strategy 2 (Event count), average temperature.

Figure 3-25:

Reservoir pressure at the production clusters for Strategy 2 (Event count), average temperature.

54

Figure 3-26:

Pressure slices comparing Strategy 2 (Event count optimised) to Strategy 1 (pwPGV optimised) for the average temperature production profile

55

Strategy 2 (Event count) – Cold temperature year
For the cold temperature profile, production from all Southern clusters is maximized up to the 70%
load factor, after which the East-Central clusters are opened up (OWG/SCB). The differences in
depletion with respect to Strategy 1 are quite distinct, see Figure 3-30. Especially the significant
production from the Eemskanaal cluster yields some additional 5 bar of depletion in that area as
compared to Strategy 1.

Figure 3-27:

Production distribution for Strategy 2 (Event count), cold temperature year

56

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 3-28:

Utilisation of the various production regions for Strategy 2 (Event count), cold temperature year.

Figure 3-29:

Reservoir pressure at the production clusters for Strategy 2 (Event count), cold temperature year

57

Figure 3-30:

Pressure slices comparing Strategy 2 (Event count optimised) to Strategy 1 (pwPGV optimised) for the cold spell temperature production profile.

58

Strategy 2 (Event count) – Warm temperature year
For the warm temperature year, the requested production rates do not require utilization beyond
the western-most group of clusters within the South-West region from the start-up list, Figure 3-31.
The Eemskanaal cluster is not produced, leaving the South-West Periphery unchanged with respect
to Strategy 1, Figure 3-34.

Figure 3-31:

Production distribution for Strategy 2 (Event count), warm temperature year

59

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 3-32:

Utilisation of the various production regions for Strategy 2 (Event count), warm temperature year.

Figure 3-33:

Reservoir pressure at the production clusters for Strategy 2 (Event count), warm temperature year

60

Figure 3-34:

Pressure slices comparing Strategy 2 (Event count optimised) to Strategy 1 (pwPGV optimised) for the warm spell temperature production profile.

61

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

4

Event Rate and Hazard Assessment

Event rate forecast
Based on the production profiles GTS-raming 2019, the number of earthquakes with a magnitude
larger than or equal to M=1.5 have been forecasted. Figure 4.1 shows the annual number of
earthquakes forecasted until 2032 for Groningen field volume offtake for the “GTS-raming 2019”
average temperature profile. After an initial plateau of about 16 earthquakes per year until 2020, the
seismic activity rate starts to decline. This is a consequence of the decreasing gas production, which
accelerates after the new nitrogen blending plant comes on stream.

Figure 4-1

Seismic Activity Rate of earthquakes for the period 2012 to 2032 (production profile GTS-raming 2019 –
average temperature year and production distribution optimisation based on minimisation of the event
count). The dark grey line indicates the expected number of earthquakes in each year and the grey area the
uncertainty band. This figure is based on the central branch of the Mmax distribution for the Average
temperature profile.

The seismic activity rate declines to an expected 3 earthquakes per year in 2032, with an uncertainty
range of 0 to 9 earthquakes per year. The seismic activity rate beyond 2025 is primarily driven by the
pressure equilibration in the field, between the high-pressure area North-West of Loppersum and the
lower-pressure area South-East of the field (Ref. 6).
The expected impact of temperature uncertainty is within the uncertainty band for event rate of the
average temperature profile. In figure 4.2 the seismic activity rate for three profiles is shown; the
average temperature profile, an average temperature profile with gas-year 2019-2020 a cold year and
an average temperature profile with gas-year 2019-2020 a warm year. Especially in calendar year 2020
the activity rate is higher for the cold year profile (16 earthquakes) than for the average temperature
profile (14 earthquakes) and lower for the warm year profile (12 earthquakes).

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Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 4-2

The seismic activity rate for three production profiles; (left) the average temperature profile, (middle) an
average temperature profile with gas-year 2018-2019 a cold year and (right) an average temperature profile
with gas-year 2018-2019 a warm year.
These differences in seismic activity rate between the temperature profiles are smaller than the uncertainty
band for the average temperature profile.

The seismological model is used to forecast the seismicity in terms of the number, location and
magnitude of future earthquakes. The probability of an earthquake with a magnitude exceeding a
given magnitude can be assessed. In table 4.1 the annual probability of an earthquake occurring with
a magnitude exceeding the specified magnitude is given. For instance, the probability of an earthquake
occurring in 2019 with a magnitude exceeding ML=3.6 (the magnitude of the Huizinge earthquake) is
equal to 13%.

Table 4.1a

Year

P(M>=3.6)

P(M>=4.0)

P(M>=4.5)

P(M>=5.0)

2019
2020
2021
2022
2023
2024
2025
2026
2027
2028

12.57%
10.62%
9.74%
7.84%
6.64%
6.01%
5.52%
4.94%
4.36%
4.21%

4.69%
3.93%
3.70%
3.01%
2.53%
2.24%
2.15%
1.90%
1.57%
1.56%

0.97%
0.86%
0.76%
0.64%
0.53%
0.48%
0.45%
0.40%
0.36%
0.32%

0.18%
0.15%
0.14%
0.14%
0.11%
0.08%
0.08%
0.08%
0.07%
0.07%

Table with annual probabilities for occurrence of earthquakes exceeding a set magnitude. This table is for
production profile GTS-raming 2019, average temperature and operational strategy 1.

Year
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
Table 4.1b

P(M>=3.6)
12.25%
9.99%
9.00%
7.62%
6.57%
6.11%
5.76%
5.09%
4.92%
4.52%

P(M>=4.0)
4.63%
3.78%
3.28%
2.86%
2.51%
2.24%
2.15%
1.88%
1.88%
1.72%

P(M>=4.5)
0.99%
0.77%
0.74%
0.65%
0.56%
0.48%
0.46%
0.42%
0.37%
0.38%

P(M>=5.0)
0.20%
0.13%
0.14%
0.12%
0.10%
0.09%
0.09%
0.09%
0.08%
0.05%

Table with annual probabilities for occurrence of earthquakes exceeding a set magnitude. This table is for
production profile GTS-raming 2019, average temperature and operational strategy 2.

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Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

The event rate for both operational strategies are compared in figure 4.3. The mean event rate is very
similar for both operational strategies. The uncertainty band around the mean event rate shows slight
differences.

Operational Strategy 1
Figure 4.3

Operational Strategy 2

The seismic event rate for the average temperature profile of GTS-raming 2019 for both operational strategies.

64

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5

Hazard Assessment

Hazard metrics
Different metrics have been proposed to describe the hazard resulting from seismic activity. Most
commonly used are the peak ground velocity (PGV) and peak ground acceleration (PGA). Because the
focus of previous hazard studies was the assessment of risk, acceleration (PGA and spectral
acceleration) was used as the prime metric for the hazard assessments. For the prediction of building
damage, additional hazard metrics will be assessed (Ref. 5).
In the current report, the hazard assessment is based on Ground Motion Prediction Methodology
(GMM) Version 5 (Ref. 36). This version of the GMM incorporates the minor comments from the
assurance committee for ground motion prediction (see Table D.3 in Appendix D) on the previous
release of the GMM version 4 (Ref. 37), which was prepared and assured May 2017.

Risk Assessment
Peak Ground Acceleration (PGA) is a widely used metric for ground shaking intensity and was chosen
as the most appropriate hazard metric for the seismic hazard assessment in support of the assessment
of risk. Figure 5.1 shows the measured acceleration near the epicentre during the Huizinge earthquake
of 16th August 2012. For the assessment of the response of a building to ground shaking spectral
acceleration (SA) is used. This takes into account the response period of the building being considered.
The duration of the seismic event is less important for the seismic risk. Ground Motion Prediction
methods have therefore focused on prediction of PGA and spectral acceleration at several periods.
These are the most important hazard parameters for the prediction of full or partial building collapse,
failure of building elements and hence for personal risk.

Building Damage Assessment
For the assessment of the potential to cause building damage at lower damage states (see section 7 of
this report), velocity-based hazard metrics such as PGV (Peak Ground Velocity) are also important.
Empirical evidence elsewhere has shown that building damage at lower damage states (damage states
DS1 and DS2) correlates strongly with PGV. A Groningen-specific (induced) Ground Motion Prediction
method to estimate the value of PGV at specific locations has therefore been developed as part of the
Ground Motion Prediction Methodology Versions 4 and 5. The assessment of PGV is primarily in
support of assessment of building damage due to historical earthquakes and expected future damage.
The official Dutch guidelines for assessing the impact of vibrations on buildings, as presented in the
document “Building Damage: Measurement and Assessment” by the SBR (Ref. 38), are based on the
ground velocity metric VTOP. To ensure consistency with the SBR Guidelines, apart from the geometric
mean velocity also a Ground Motion Prediction method for the VTOP parameter (the ‘maximum’ value
of PGV in any direction) was developed.

65

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

PGA [cm/s2]

Vertical Component

Huizinge Event 16-8-2012 (Westeremden station)

PGA [cm/s2]

Transverse Component

Time [s]

PGA [cm/s2]

Radial Component

Time [s]

Time [s]
Figure 5.1

Accelerogram of the earthquake near Huizinge recorded at the 16th August 2012 by the accelerometer located
near Westeremden (near the epicentre).

Hazard Map for Peak Ground Acceleration
For the probabilistic description of the ground accelerations (PGA, or generalised to Pseudo Spectral
Acceleration, PSA), a hazard map is used. On this map for each location the acceleration is plotted that
could occur, with a prescribed annualised probability of exceedance (exceedance level), during a
prescribed analysis period. Hazard levels are shown using a gradual colour scale.
The hazard maps shown in this document were constructed according to the following procedure. Each
location in the analysis area during the analysis period is subjected to ground motion accelerations
resulting from induced earthquakes. At some locations at the centre of the field, e.g. near Loppersum,
66

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

the chance of exceeding a given peak ground acceleration threshold is higher than at the periphery of
the field, e.g. in Groningen city (Fig. 5.2).

Figure 5.2

Hazard curves for two different locations in the Groningen area. Left for de village of Loppersum. Here the
probability of being exposed to an acceleration exceeding larger than 0.1 g is 0.2% per year. On the right the
hazard curve for the city of Groningen, the acceleration with an exposure of 0.2% per year is lower at 0.05 g.

Equally, at any one location, the chance of exceeding some value of peak ground acceleration
decreases with increasing peak ground acceleration. A set of hazard curves is shown for a number of
locations in figure 5.3. Each declining line indicates the hazard curve for a single location in the field.

Figure 5.3

A set of hazard curves showing average annual exceedance rate for peak ground acceleration at different
locations in the field. Each line corresponds to a location in the field. The bold line indicates the maximum
PGA anywhere within the field for a given exceedance level (bounding envelope). In this figure, the red line
indicates that for an exceedance level of 0.2%/year the highest PGA in the field is 0.134 g. This plot was
prepared based on the average temperature production profile of GTS-raming 2019 for the period 2019 to
2024 and Operational Strategy 2.

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Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

To prepare a hazard map, an exceedance level needs to be chosen. This is not a purely technical choice.
However, inspired by Eurocode 86, part of the current technical standards for structural design in
Europe, it has become common practice to prepare hazard maps for an exceedance level of 0.2%/year.
This exceedance level is equivalent to a 475-year return period for stationary seismicity. The same
exceedance level is also used by KNMI for their hazard maps, which allows for comparison of these
hazard maps. The choice of the exceedance levels (or return period) is only for the representation of
the hazard. This choice of exceedance level does not affect the subsequent assessment of risk. Hazard
maps can also be prepared for spectral acceleration at a specified period. The standard PGA hazard
map is the same as the spectral acceleration hazard map at shortest period, which for this assessment
was chosen at 0.01 s.

Hazard Assessment
Hazard maps have been prepared for each year of the next ten calendar years and for the next two 5year periods. Separate hazard maps are available for the “GTS-raming 2019” at average temperature
profile, cold temperature profile and warm temperature profile.
The hazard map for the average temperature profile for each year of the period 2019 to 2028 is shown
in figure 5.4 a, b, c. The hazard is, as expected based on the declining gas production profile, also
decreasing over this period. The trend in the largest PGA in these annual hazard maps is shown in
figure 5.7. However, this reduction in PGA is not evenly spread over all areas of the field. In the later
years, the hazard is primarily located in the area North-West of Loppersum. This is consistent with the
equilibration of reservoir pressures during these later years. The gas from the higher-pressure area to
the North-West of Loppersum will continue to flow to the lower pressure South-Eastern area, causing
a continued decrease of pressure in the former area. This effect of gas flow within the reservoir due
to equilibration of pressure differences is referred to as the “Remweg Effect”. In theoretical remweg
production profiles this effect (Ref. 6) has also been demonstrated.
The effect can also be seen in Figure 5.6 and 5.6, showing hazard maps of the “GTS-raming 2019”
production profile for the next two 5-year periods (2019 to 2013 and 2013 to 2028 respectively), at a
larger format.

6

The Eurocodes are the current technical standards for structural design in Europe, and it is now compulsory for the 28 countries in the Eurocode zone to adopt

these. Eurocode 8 specifically deals with earthquake-resistant design of structures (CEN, 2006). Each country adopting Eurocode 8 must develop a National Annex
to indicate how the code is implemented; the National Annex for the Netherlands is being developed. Eurocode 8 uses a standard practice to represent seismic
hazard via PGA maps associated with ground motions having a 10% probability of exceedance during 50 years, equivalent to 0.2%/year for a stationary process,
or a return period of 475-years.

68

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 5.4a

2019

2020

2021

2022

Hazard Maps for the average temperature weather profile for the years 2019 (top – left), 2020 (top – right),
2021, (bottom – left) and 2022 (bottom – right). The production profile for these hazard maps is “GTS-raming
2019, for an average temperature year and optimisation of the distribution of the production to minimise the
event count (Operational Strategy 2). Note that water-bodies, such as the Schildmeer, are masked in these
hazard maps.

69

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 5.4b

2023

2024

2025

2026

Hazard Maps for the average temperature weather profile for the years 2022 (top – left), 2023 (top – right),
2024, (bottom – left) and 2025 (bottom – right). The production profile for these hazard maps is “GTS-raming
2019, for an average temperature year and optimisation of the distribution of the production to minimise the
event count (Operational Strategy 2).

70

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

2027
Figure 5.4c

2028

Hazard Maps for the average temperature profile for the years 2022 (left), 2023 (right), 2024, (bottom – left)
and 2025 (bottom – right). The production profile for these hazard maps is “GTS-raming 2019, for an average
temperature year and optimisation of the distribution of the production to minimise the event count
(Operational Strategy 2).

71

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 5.5

Hazard Maps for the average temperature weather profile for the period from 2019 to 2024. The production
profile for these hazard maps is “GTS-raming 2019, for an average temperature year and optimisation of the
distribution of the production to minimise the event count (Operational Strategy 2).

72

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 5.6

Hazard Maps for the average temperature weather profile for the period from 2024 to 2028. The production
profile for these hazard maps is “GTS-raming 2019, for an average temperature year and optimisation of the
distribution of the production to minimise the event count (Operational Strategy 2).

73

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Production Scenarios 'GTS-raming 2019'
Average/Cold/Warm Temperature
Largest PGA in Hazard Map [fraction of g]

0,16
0,15
0,14
0,13
0,12
0,11
0,1
2019

2020

2021

2022

2023

2024

2025

2026

2027

2028

Figure 5.7

Development over time of the largest PGA in the hazard maps. The production profile for these hazard maps
is “GTS-raming 2019 and optimisation of the distribution of the production to minimise the event count
(Operational Strategy 2.
The grey solid line denotes the largest PGA for each year in the hazard map for the reference profile.
The blue solid line denotes the largest PGA for each year in the hazard map for the GTS-raming 2019 cold temperature profile.
The green solid line denotes the largest PGA for each year in the hazard map for the GTS-raming 2019 average temperature
profile.
The orange line denotes the largest PGA for each year in the hazard map for the GTS-raming 2019 warm temperature profile.
Hatched lines denote the five-year average of the largest PGA in the hazard map.

74

distribution of the gas production based on population
weighted PGV

distribution of the gas production to minimise the
event count

2019

Operational Strategy 1 – Optimisation of the

Operational Strategy 2 – Optimisation of the

Difference
(Operational Strategy 2 – Operational Strategy 1)

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

75

distribution of the gas production based on population
weighted PGV

distribution of the gas production to minimise the
event count

2020

Operational Strategy 1 – Optimisation of the

Operational Strategy 2 – Optimisation of the

Difference
(Operational Strategy 2 – Operational Strategy 1)

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

76

distribution of the gas production based on population
weighted PGV

distribution of the gas production to minimise the
event count

2021

Operational Strategy 1 – Optimisation of the

Operational Strategy 2 – Optimisation of the

Difference
(Operational Strategy 2 – Operational Strategy 1)

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

77

distribution of the gas production based on population
weighted PGV

distribution of the gas production to minimise the
event count

2022

Operational Strategy 1 – Optimisation of the

Operational Strategy 2 – Optimisation of the

Difference
(Operational Strategy 2 – Operational Strategy 1)

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

78

distribution of the gas production based on population
weighted PGV

distribution of the gas production to minimise the
event count

2023

Operational Strategy 1 – Optimisation of the

Operational Strategy 2 – Optimisation of the

Difference
(Operational Strategy 2 – Operational Strategy 1)

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

79

distribution of the gas production based on population
weighted PGV

distribution of the gas production to minimise the
event count

2024

Operational Strategy 1 – Optimisation of the

Operational Strategy 2 – Optimisation of the

Difference
(Operational Strategy 2 – Operational Strategy 1)

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

80

distribution of the gas production based on population
weighted PGV

distribution of the gas production to minimise the
event count

2025

Operational Strategy 1 – Optimisation of the

Operational Strategy 2 – Optimisation of the

Difference
(Operational Strategy 2 – Operational Strategy 1)

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

81

distribution of the gas production based on population
weighted PGV

distribution of the gas production to minimise the
event count

2026

Operational Strategy 1 – Optimisation of the

Operational Strategy 2 – Optimisation of the

Difference
(Operational Strategy 2 – Operational Strategy 1)

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

82

distribution of the gas production based on population
weighted PGV

distribution of the gas production to minimise the
event count

2027

Operational Strategy 1 – Optimisation of the

Operational Strategy 2 – Optimisation of the

Difference
(Operational Strategy 2 – Operational Strategy 1)

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

83

(Operational Strategy 2 – Operational Strategy 1)

Difference

84

Annual hazard maps for the two optimised Operational Strategies compared. These maps are based on the production profile “GTS-raming 2019” for an average temperature

2028

distribution of the gas production based on population
weighted PGV

distribution of the gas production to minimise the
event count

Figure 5.8
year.

Operational Strategy 1 – Optimisation of the

Operational Strategy 2 – Optimisation of the

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Cold Temperature

Average Temperature
2019

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Warm Temperature

85

Cold Temperature

Average Temperature
2020

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Warm Temperature

86

Cold Temperature

Average Temperature
2021

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Warm Temperature

87

Cold Temperature

Average Temperature
2022

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Warm Temperature

88

Cold Temperature

Average Temperature
2023

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Warm Temperature

89

Cold Temperature

Average Temperature
2024

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Warm Temperature

90

Cold Temperature

Average Temperature
2025

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Warm Temperature

91

Cold Temperature

Average Temperature
2026

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Warm Temperature

92

Cold Temperature

Average Temperature
2027

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Warm Temperature

93

Figure 5.9

Average Temperature
2028

Warm Temperature

94

Annual hazard maps for the three temperature years compared. These maps are based on the production profile “GTS-raming 2019” for an optimisation of distribution of the gas
production to minimise the event count (Operational Strategy 2).

Cold Temperature

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Hazard for gas-year 2019 / 2020
In this section the hazard for the gas-year 2019 – 2020 is presented. Figure 5.9 shows the hazard maps
for both Operational Strategies together with a map of the difference between these strategies. This
is shown for an average temperature year, a cold temperature year and a warm temperature year.

95

Figure 5.9a

Operational Strategy 1

(Operational Strategy 2) – (Operational Strategy 1)

96

Hazard maps for the production profile GTS-raming 2019 for the average temperature year. Both Operations Strategies and the difference between these strategies are shown.

Operational Strategy 2

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 5.9b

Operational Strategy 1

97

(Operational Strategy 2) – (Operational Strategy 1)

Hazard maps for the production profile GTS-raming 2019 for the cold temperature year. Both Operations Strategies and the difference between these strategies are shown.

Operational Strategy 2

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 5.9c

Operational Strategy 1

(Operational Strategy 2) – (Operational Strategy 1)

98

Hazard maps for the production profile GTS-raming 2019 for the warm temperature year. Both Operations Strategies and the difference between these strategies are shown.

Operational Strategy 2

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

6

Risk Assessment

Risk Metrics
The results from the probabilistic seismic Hazard and Risk Assessment (HRA) are summarised via risk
metrics, which are related to the annualised probability of fatality for an individual person or for groups
of people, taken as an average across the forecast period of the Hazard and Risk Assessment.
When assessing risk, it is important to select a risk metric that is appropriate given the purpose of the
risk assessment. In many cases there is more than one option available as to which metric to use. An
advisory committee, Commissie Meijdam, was established in early 2015 to advise the Minister of
Economic Affairs and Climate Policy on risk policy related to Groningen earthquakes, including the
selection and definition of the appropriate risk metrics. In December 2015, the Commissie Meijdam
shared its third and final advice with the Minister of Economic Affairs (Ref. 9 to 11). The selection of
risk metrics for this Hazard and Risk Assessment is based on the final advice published by Commissie
Meijdam.

Individual Risk Metrics
Object-related Individual Risk and Individual Risk
The Commissie Meijdam, introduced two individual risk metrics; Individual Risk (IR) and Object-related
Individual Risk (OIA). Table 6.1 lists the definitions of the individual risk metrics used in the assessment
of risk for induced seismicity in the Groningen field area. The fundamental principle of the advice of
the Commission is that living and working in Groningen must be as safe as elsewhere in the
Netherlands. In Groningen the same safety standards must apply as elsewhere in the Netherlands.
Based on this principle the Committee Meijdam established the norm that Individual Earthquake Risk
(IR) should be below 10-5/year.
For buildings with an OIA above 10-4/year, immediate action is required. In principle these buildings
need to be strengthened immediately or vacated. Buildings with an OIA between 10-4/year and
10-5/year need to be strengthened within a reasonable period.

Inside and Outside Local Personal Risk
To perform the calculations, NAM uses as an intermediary result, the individual risk metric LPR (Local
Person Risk) consisting of two components; Inside Local Personal Risk (ILPR) and Outside Local Personal
Risk (OLPR). The use of LPR is analogous to safety assessment domains like those used for industrial
activities and pipelines. “Local Personal Risk” (LPR) is generally defined as the annual probability of
fatality for a fictional person, who is continuously present, without protection, at a specific at-risk
location. For Groningen earthquakes, LPR is defined as follows: “the probability of death of a fictional
person who is permanently in or near a building”. The location of the person within the building is
uniformly and randomly distributed inside the building. This means that if 10% of the building collapses
there is also a 10% probability that the fictional person will be in the collapsed part of the building.

99

Individueel
Aardbevingsrisico
(IAR)

Plaatsgebonden
Persoonlijk Risico
Binnen
Plaatsgebonden
Persoonlijk Risico
Buiten
Plaatsgebonden
Persoonlijk Risico

Object-related
Individual Risk

Individual
Earthquake Risk

Inside Local
Personal Risk
(ILPR)
Outside Local
Personal Risk
(OLPR)
Local Personal
Risk (LPR)
The probability of death of a fictional unprotected
person who is permanently present in or near a
building. This person is thought to be inside the
building 99% of the time and outside near the
building 1 % of the time.

The probability of death of a fictional unprotected
person who is permanently present near a building.

The probability of death of a fictional unprotected
person who is permanently present in a building.

Local individual risk metric to measure fatality risk due to
structural and non-structural collapse (LPR, see below), weighted
by the average residence times of the individuals in/around the
building (OIA), relative to norm of 10-5/year overall individual risk.
Check if any buildings have occupants with an average OIA above
10-4/year (high priority for immediate action).

The Objectgebonden individual earthquake risk is
the risk that an individual dies in a year due to
collapse or falling objects (as a result of an
earthquake) of a building in which or in the direct
vicinity of which this person is present. The
residence time in/around that building is therefore
taken into consideration.
The individual earthquake risk is the annual risk that
an individual is exposed to in the various structures
in or near which this individual is present.

Local risk metric to measure fatality risk due to collapse of a given
building and its non-structural elements both inside (ILPR) and
outside (OLPR) the building, relative to the norm of 10-5/year
overall individual risk.
Check if any buildings have Local Personal Risk above 10-4/year
(high priority for immediate action).

100

Individual risk metric that is not considered at present (as requires
knowledge of the presence of all members of the Groningen
community throughout the day, in order to sum up all their objectbound individual risks over a 24-hour period).

Purpose(s)

Definition

Overview of the individual risk metrics used in the assessment of risk for induced seismicity in the Groningen field area.

Objectgebonden
Individueel
Aardbevingsrisico
(OIA)

Table 6.1

Dutch Name

Risk Metric

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Inside Local Personal Risk is the probability of fatality for an individual continuously present in a
building. It is associated with partial or full collapse of the building. Outside Local Personal Risk is the
probability of fatality for an individual continuously present in the direct vicinity of a building. It is
primarily associated with failure of non-structural elements, the so-called falling objects7 (chimneys,
balconies, parapets, etc.). In this context the vicinity of a building is taken as within 5 m from the
building.
The Inside Local Personal Risk and Outside Local Personal Risk are aggregated to Local Personal Risk
(LPR) assuming a fictional person is 99% of the time inside a building and 1% of the time outside the
building, but in the direct vicinity of the building. The definition of these risk metrics is also listed in
table 6.1.
As Local Personal Risk applies to a fictional unprotected person who is permanently present
(everywhere) in a building, it is a property of this building. It is independent of the actual occupancy
of the building; how many people are present in the building and the duration of their presence are
not taken into account, when assessing the LPR of a building. LPR is presented as a cumulative
distribution (of buildings versus risk level), which provides an estimate of the number of buildings that
do not comply with the norm.

Current Practice in Risk Assessments
However, the Meijdam-norm applies to Individual Risk. To assess Individual Risk for a person in a
rigorous manner knowledge of the buildings the person visits during the day and the duration the
person is present in these building is required. The Individual Risk of a person is the duration weighted
sum of the LPR of the buildings visited during the day.
Typically, a person spends more than half her time in her house, some eight hours during week-days
in an office (or workplace building), some time in shops or other public buildings and the remaining
hours in the open air or in her car (where earthquake related risk is in general very low). Calculation
of Individual Risk for all members of the full Groningen community using this method is not practically
feasible as it requires, beside knowledge of all buildings in Groningen, also knowledge of the presence
of all members of the Groningen community throughout the day. This detailed residence data, NAM
does not have access to. Additionally, an assessment of IR for all members of the Groningen
community does not directly suggest which buildings do not comply with the norm.
In previous risk assessments, NAM has therefore used a practical approach, whereby the number of
buildings with a mean LPR above the norm level was evaluated and compared to the threshold safety
levels of the Meijdam-norm. The underlying principle was that if all buildings have a mean LPR below
the norm, no persons can be exposed to an IR above the norm. The LPR inherently assumes a full-time
(100%) residency of the building. In the Hazard and Risk Assessment, the mean LPR is the primary
metric used to compare against the 10-5/year individual risk norm (as recommended by Commissie
Meijdam, which requires the individual risk for a person to be less than 10-5 per year). Note that
individual risk metrics that account for the proportion of time a person spends in the building will yield
a lower calculated individual risk (IR) than LPR (particularly for buildings occupied a small proportion
of the time). The method used by NAM based on mean LPR instead of IR is conservative (overestimates the number of buildings above the risk norm).

7

Falling Objects are sometimes also referred to as High Risk Building Elements (HRBE) or Potential High Risk
Building Elements (PRBE).

101

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Proposed improvement of the Risk Assessment
The panel of professors has pointed out that this is a conservative approach (Ref. 39 to 41), which
inherently assumes that for each building individuals spend their full time there. The panel therefore
proposed to assess OIA based on mean residence periods and compare this to the norm level set by
the Committee Meijdam. This is a preferred implementation of the norm set by the Committee
Meijdam and is less conservative.
The use of OIA to compare to the safety-norm inherently assumes that the time an individual spends
in other buildings does not significantly add to his IR. Inspection of the list of buildings that do not
meet the mean LPR norm (consisting of some 1,500 buildings) shows that it primarily contains buildings
with a residence functionality and few office buildings, schools or other public buildings. Since the
fraction of buildings exceeding the norm is relatively small compared to the total building stock, it is
reasonable to take the LPR of a dwelling multiplied with the average residence time of the occupants
as the IR of its occupants.

Residence Time Estimates
To be able to implement the Object-related Individual Risk (OIA) including the residence times of the
people living and present in a building, we need to know the mean residences times for the buildings.
This depends on the usage of the building. The residence time for residential buildings will be most
important as most buildings on the building risk ranking are residential buildings.
The report “Met het oog op de tijd” (“With an eye on the time”) van het Social Planning Bureau (Ref.
42) provides information on how the Dutch spend their time. Based on the time spent on various
activities, the time people spend in their own home can be estimated. Table 6.3 gives an overview of
the time the Dutch engage in various activities during the week taken from this report. The report
provides time estimates for the activities; verplichte tijd, persoonlijk tijd en vrij tijd (obligatory time,
personal time and leisure time). These time estimates have been copied from the report (in the green
section of the table). The references to the pages of the report are provided. The report also gives an
overview of the time spent travelling to engage in these activities (also in green in the table). In the
red section of the table the activities are allocated to a location; at home, at the workplace, at school
and in the car and open space. In the blue section of the table time-fractions at these locations are
calculated based on the time data. It shows that on average the residence time for a person in her/his
own home is 75%.
For residential buildings, the mean OIA of the building will, when including the mean residence time,
be 75% of the mean LPR.
Mean residence times for office buildings are more easily assessed. For a work place like an office
building this is 24% based on a 40 hr per week work week. Working over-time is balanced by an
average work-week of 36 hour per week for many people. This residence time is applied to all buildings
with a usage associated with work; commercial business, agricultural, educational and industrial. Table
6.2 showing data on working hours from “Met het oog op de tijd” (“With an eye on the time”, Ref. 42)
shows this is a conservative approach.
Average hours spend working

Participation

39,6
25,6
33,2

83 %
72 %
78 %

Men
Women
Overall
Table 6.2

Time spent working and participation.

102

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

The residence time of Health Case buildings is set to 100% based on the presence of boarding patients.
The residence time for religious buildings is 2% based on 3,5 hours religious practice in the religious
building. Table 6.4 shows the mean residence time fractions for the different building usage
categories.
Building Use
Woonfunctie
Logiesfunctie
Industriefunctie
Winkelfunctie
Kantoorfunctie
Bijeenkomstfunctie
Overige gebruiksfunctie
Sportfunctie
Onderwijsfunctie
Celfunctie
Gezondheidszorgfunctie
<blank> -- anything unknown is
assumed to be Residential
Table 6.4

Residence Time
Fraction
75%
50%
24%
24%
24%
24%
24%
24%
24%
100%
100%
75%

Residence times for the building usage categories.

Some buildings have both a primary and secondary building use. An example is a building with a shop
(commercial business) at the ground floor and apartments on the first and higher floors (residential).
In this case, a commercial business use combined with a residential use, the larger of the two
residential time fractions will be assigned to the building. In general, the residence time fraction is the
larger of the residence time for the primary and the secondary use.

Number of buildings compared to the safety norm
In this section of the report, the number of houses where the risk exceeds one of the two risk safety
levels of the Meijdam safety-norm is discussed, without addressing which of the two levels applies for
an individual building, as such is the domain of the NCG, who currently directs the strengthening effort.
Both mean LPR and mean OIA of a building will be calculated and reported. The mean OIA is calculated
as the product of the LPR and the residence time fraction. These fractions are treated as fixed. Both
in the cumulative LPR-plots and the cumulative OIA-plots uncertainty is indicated by a grey band.

Assessment of Local Personal Risk (LPR)
Figures 6.1a and 6.1b show the number of buildings exceeding an annual mean Local Personal Risk
(LPR) for each year of the 10-year period 2019 to 2028, based on the average temperature year and
the optimised Operational Strategy to minimise the event rate. The grey bands in these LPR-graphs
indicate the uncertainty range. Figure 6.2 shows the LPR-graphs for the two five-year periods 2019 to
2023, and 2024 to 2028. The impact of the buildings already strengthened to date has not been
incorporated in this assessment.

103

Table 6.3

5,3
8,9

3,6

pg. 43
pg. 43

2,3
3,6
47,5

pg. 143
pg. 143
pg. 143
pg. 143

pg. 143

pg. 34
pg. 34

pg. 43
pg. 43
pg. 43

20,9
7,2
13,5

pg. 41 en 42
pg. 41 en 42
pg. 41 en 42
Anders
binnenshuis
uithuizig

Op school
Onderwijs mobiliteit

op werk plek
verplichtetijdsmobiliteit

thuis
Huishouden + zorgtaken
mobiliteit

32,1
15,7
47,8

pg. 46
pg. 46

100% huis
100% buiten

100% huis
100% huis
100% huis

100% school
100% buiten

100% werkplek
100% buiten

100% buiten

2,2
17,9
17
2,6
19,6
3,2
0,5
3,7

100% huis

pg. 143

Verwijzing in
MHOODT

15,7

Tijd (uren)

74%

72,4%

120,7

32,1

59,5
10,2
6,2

12,7

Huis

9%

11,2%

18,7

1,7

17

Kantoor

13%

12,6%

15,7
21

0,5

2,6

2,2

Buiten

2%

1,9%

3,2

3,2

School

2%

1,8%

3

3

Winkel

100%

100%

47,8
166,6

77,6

41,2

Totaal

104

Table of time the Dutch spend on various activities. From this time data the mean residence time for her/his own home is estimated. The following assumptions are used (but
these have only a small impact) (1) Care duties include 3 hours outside the home (i.e. shopping), (2) All worktime excluding travel is spent in an office and (3) Once a week people
eat outside the home.

2,2
0,5
2,6

166,7
1,3
168
9

Gespecificeerd
Ongespecificeerd

Onderweg tijd
vrijetijdsmobiliteit
huishouden en
zorgtaken
onderwijs
betaald werk
verplichtetijdsmobiliteit

47,8

Vrije tijd
media gebruik
sociale contacten
recreatief + ontspanning
maatschappelijke
participatie
vrijetijdsmobiliteit

59,5
11,9
6,2
77,6

pg. 34 en 35

41,2

77,7

Persoonlijke tijd
slapen
eten/drinken
persoonlijke verzorging

pg. 34 en 35

3,7

onderwijs

pg. 34 en 35

19,6

betaald werk

pg. 34 en 35

Verwijzing in
MHOODT

17,9

Tijd
(uren)

Verplichte tijd
huishouden +
zorgtaken

Tijd
(uren)
41,2

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

The development of the mean LPR for the Groningen building stock over the period 2019 to 2028 is shown
in figure 6.3. The number of buildings exceeding the Meijdam-norm of mean LPR 10-5/year shows a
declining trend. This is particularly evident for the years 2019 to 2022 the number of buildings exceeding
this norm declines noticeably. For each year in the period 2019 to 2028, tables 6.5a to 6.5d, show the
number of buildings for four different probabilistic assessments:


The number of buildings with LPR exceeding the 10-5/year level



The number of buildings with LPR exceeding the 10-4/year level



The number of buildings with OIA exceeding the 10-5/year level



The number of buildings with OIA exceeding the 10-4/year level

During the period 2021 to 2023, the number of buildings where the 10-5/year norm is not met is assessed
to decrease from just over 826 in 2019 to about 208 in 2023 and less than one hundred in 2027, for
production profile “GTS-raming 2019” for an average temperature profile and Operational Strategy 2.
The data captured in tables 6.5a to 6.5d is also shown in figures 6.4 and 6.5, which shows number of
buildings where the LPR and OIA respectively exceeds the 10-4/year and 10-5/year, for different profiles.
The LPR results can be disaggregated to show the separate contributions of the different building
typologies (shown in figure 6.6) as well as their collapse states contributing to the LPR. Collapse State 1
refers for most typologies to partial collapse of façade walls, typically out-of-plane and generally to the
outside of the building. Collapse State 2 and 3 are typically more severe, with collapse State 3 leading to
global collapse of a significant part of the building.

105

Figure 6.1a

2023

2022

2024

2021

106

Local Personal Risk graphs for the years 2019 to 2024. These show the number of houses that are exposed to a LPR. The black lines denote the mean and the dark
grey areas the uncertainty bands. The two horizontal bands in light grey denote the LPR levels of the Meijdam-Norm.

2020

2019

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 6.1b

2026

2027

107

Local Personal Risk graphs for the years 2025 to 2028. These show the number of houses that are exposed to a LPR. The black lines denote the mean and the dark
grey areas the uncertainty bands. The two horizontal bands in light grey denote the LPR levels of the Meijdam-Norm. The assessment is based on production profile
“GTS-raming 2019” for an average temperature year using the optimisation to minimise the event count (Operational Strategy 2).

2028

2025

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 6.2

2024 - 2028

108

Local Personal Risk graphs for the two 5-year periods (2019 to 2023 and 2024 to 2028). These show the number of houses that are exposed to a LPR. The black lines
denote the mean and the dark grey areas the uncertainty bands. The two horizontal bands in light grey denote the LPR levels of the Meijdam-Norm. The assessment
is based on production profile “GTS-raming 2019” for an average temperature year using the optimisation to minimise the event count (Operational Strategy 2).

2019 - 2023

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 6.3a

Mean Local Personal Risk graphs for the years 2019 to 2028. These show the number of buildings that are exposed
to an LPR. The uncertainty bands have been left out of this graph but are shown in figures 6.1a and 6.1b. The
years are colour coded. The assessment is based on production profile “GTS-raming 2019” for an average
temperature year using the optimisation to minimise the event count (Operational Strategy 2).
Note that the number of buildings exceeding the mean LPR norm of 10-5/year decreases over time.

Figure 6.3b

Comparison of the mean Local Personal Risk graphs for the year 2019. Production profile “Basispad Kabinet” and
“GTS-raming 2019” are shown.

109

Average Year
Average Year

Event rate
Event rate
Event rate
Event rate
Event rate
Event rate
Event rate
Event rate
Event rate

GTS-raming 2019
GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

Average Year
Average Year
Average Year
Average Year
Average Year
Average Year
Average Year
Average Year

ReferenceCase (Basispad Kabinet)

ReferenceCase (Basispad Kabinet)

ReferenceCase (Basispad Kabinet)

ReferenceCase (Basispad Kabinet)

ReferenceCase (Basispad Kabinet)

ReferenceCase (Basispad Kabinet)

ReferenceCase (Basispad Kabinet)

ReferenceCase (Basispad Kabinet)

Table 6.5a

Average Year

ReferenceCase (Basispad Kabinet)

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2028

2027

2026

2025

2024

2023

2022

2021

402
224
211
169
108
80
53
33
6
4
420
382
296
216
115
84
59
25
11
6

Mean OIA
10-5 /year

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

Mean OIA
10-4 /year
780
385
338
265
204
171
143
113
77
52
916
788
434
345
213
173
152
117
77
57

Mean LPR
10-5 /year

0

0

0

0

0

0
0

0

0

0

0

0

0

0

0

0

0

0

0

0

Mean LPR
10-4 /year

110

explanation. These are shown for each year of the period 2018 to 2027 for the production profile “GTS-raming 2019” for an average weather year and the reference
case of “Basispad Kabinet”.

Number of buildings with mean LPR exceeding 10-5/year and 10-4/year level for LPR, for different production and temperature profiles. See main text for further

Average Year

ReferenceCase (Basispad Kabinet)

Average Year

Average Year

Average Year

Average Year

Average Year

Average Year

Average Year

2019

Average Year

Event rate

GTS-raming 2019
2020

Year

Optimisation Temperature
Profile

Production Profile

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Event rate
Event rate
Event rate
Event rate
Event rate
Event rate
Event rate
Event rate
Event rate
Event rate
Event rate
Event rate
Event rate
Event rate
Event rate
Event rate
Event rate
Event rate

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019
Warm Year

Warm Year

Warm Year

Warm Year

Warm Year

Warm Year

Warm Year

Warm Year

Warm Year

Warm Year

Cold Year

Cold Year

Cold Year

Cold Year

Cold Year

Cold Year

Cold Year

Cold Year

Cold Year

Cold Year

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

Year
460
304
220
170
124
90
64
51
10
6
391
171
201
153
126
66
43
28
6
2

Mean OIA
10-5 /year

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

Mean OIA
10-4 /year
801
547
353
282
222
188
147
137
85
62
786
281
325
249
217
161
139
105
56
31

Mean LPR
10-5 /year

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

Mean LPR
10-4 /year

111

Number of buildings with mean LPR exceeding 10-5/year and 10-4/year norm for LPR, for different production and temperature profiles. See main text for further
explanation. These are shown for each year of the period 2018 to 2027 for the production profile “GTS-raming 2019” for cold weather and warm weather years.

Event rate

GTS-raming 2019

Table 6.5b

Event rate

Optimisation Temperature
Profile

GTS-raming 2019

Production Profile

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Average Year

pwPGV
pwPGV
pwPGV
pwPGV
pwPGV
pwPGV
pwPGV
pwPGV

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

Table 6.5c

Average Year

pwPGV

GTS-raming 2019
GTS-raming 2019

2028

2027

2026

2025

2024

2023

2022

2021

403
277
234
185
112
66
45
17
5
2

Mean OIA
10-5 /year

0

0

0

0

0

0

0

0

0

0

Mean OIA
10-4 /year
796
434
373
286
213
169
146
97
59
43

Mean LPR
10-5 /year

0

0

0

0

0

0

0

0

0

0

Mean LPR
10-4 /year

112

Number of buildings with mean LPR exceeding 10-5/year and 10-4/year level for LPR, for different production and temperature profiles. See main text for further
explanation. These are shown for each year of the period 2018 to 2027 for the production profile “GTS-raming 2019” for an average weather year and the reference
case of “Basispad Kabinet”.

Average Year

Average Year

Average Year

Average Year

Average Year

Average Year

Average Year

2019

Average Year

pwPGV

GTS-raming 2019
2020

Year

Optimisation Temperature
Profile

Production Profile

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

pwPGV
pwPGV
pwPGV
pwPGV
pwPGV
pwPGV
pwPGV
pwPGV
pwPGV
pwPGV
pwPGV
pwPGV
pwPGV
pwPGV
pwPGV
pwPGV
pwPGV
pwPGV

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019

GTS-raming 2019
Warm Year

Warm Year

Warm Year

Warm Year

Warm Year

Warm Year

Warm Year

Warm Year

Warm Year

Warm Year

Cold Year

Cold Year

Cold Year

Cold Year

Cold Year

Cold Year

Cold Year

Cold Year

Cold Year

Cold Year

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

2028

2027

2026

2025

2024

2023

2022

2021

2020

2019

Year
457
395
244
172
111
65
52
25
7
2
385
195
218
177
91
55
34
10
3
2

Mean OIA
10-5 /year

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

Mean OIA
10-4 /year
975
879
370
284
203
163
133
103
66
25
790
312
363
291
191
155
129
76
53
17

Mean LPR
10-5 /year

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

Mean LPR
10-4 /year

113

Number of buildings with mean LPR exceeding 10-5/year and 10-4/year norm for LPR, for different production and temperature profiles. See main text for further
explanation. These are shown for each year of the period 2018 to 2027 for the production profile “GTS-raming 2019” for cold weather and warm weather years.

pwPGV

GTS-raming 2019

Table 6.5d

pwPGV

Optimisation Temperature
Profile

GTS-raming 2019

Production Profile

Seismic Risk Assessment of Production Profile “GTS raming 2019” for the Groningen field
March 2019

Figure 6.4

Graphs show the Local Personal Risk associated with the production profile “GTS-raming 2019” for average, cold
weather and warm weather years, and the Reference Profile (Basispad Kabinet – 2 mei 2018), and for the period
2019 to 2028.
Right graphs:
number of buildings exceeding the norm LPR larger than 10-5/year
Left graphs:
number of buildings exceeding the norm LPR larger than 10-4/year
Top graphs:
number of buildings exceeding the norm for mean LPR
Bottom graphs:
number of buildings exceeding the norm for P90 LPR

114

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019

Number of years above the norm
Figure 6.5 gives, for buildings above the norm in 2019, an overview of the duration that these buildings
remain above the norm. For about half of them this duration is 1 year. All URM4L will drop below the norm
within 4 years and 3 years respectively. Because URM1_F is most fragile, buildings of this type will remain
above the norm for a longer period.

Figure 6.5

Overview of the duration that these buildings remain above the norm for buildings above the norm in 2019, shown
for Operational Strategy 1 above and Operational Strategy 2 below.

115

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019

Individual Earthquake Risk (OIA)
As discussed in the previous section hazard metrics, a panel of professors has in three advises to the
Minister (Ref. 39 to 41) pointed out that the use of mean LPR is a conservative interpretation of the
Meijdam Norm (Ref. 9 to 11). In this section of the report the number of buildings not meeting the safety
norm levels based on Individual Earthquake Risk are reported. For brevity, only the final results will be
reported.

Assessment of Object-related Individual Risk
The OIA of a building will be calculated as the product of the LPR and the residence time fraction. These
fractions are treated as fixed. Both in the cumulative LPR-plots and the cumulative-OIA plots uncertainty
is indicated by a grey band.

Figure 6.6

Graphs show the Individual Earthquake Risk associated with the production profile “GTS-raming 2019” for average,
cold weather and warm weather years, and the Reference Profile (Basispad Kabinet – 2 mei 2018), and for the
period 2019 to 2028.
Right graphs:
number of buildings exceeding the norm OIA larger than 10-5/year
Left graphs:
number of buildings exceeding the norm OIA larger than 10-4/year
Top graphs:
number of buildings exceeding the norm for mean OIA
Bottom graphs:
number of buildings exceeding the norm for P90 OIA

116

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019

Maps of Buildings compared to the Meijdam-Norm Risk Levels
The maps of figure 6.7 show all buildings exceeding mean LPR>10-5/year for the years between 2019 and
2028. Different colours represent different dominant building typologies. For the purpose of this risk
assessment, the Groningen building stock has not been adjusted for the ongoing strengthening operations.
The maps are shown for the production profile “GTS-raming 2019” with the average temperature profile
and the Operational Strategy for the optimisation of the areal distribution of the gas production.

117

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019

2019
118

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019

2020
119

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019

2021
120

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019

2022
121

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019

2023
122

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019

2024
123

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019

2025
124

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019

2026
125

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019

2027
126

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019

2028

127

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019
Figure 6.7

Maps of all buildings exceeding mean LPR>10-5/year for the years 2019 to 2028. Different colours indicate
different building typologies.

2018

2019

2020

2021

128

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019

2022

2023

2024

2025

129

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March 2019

2026
Figure 6.8

2027

Map indicating individual building with Local Personal Risk exceeding 10 -5/year for the years 2019 to 2028 and
production profile “GTS-raming 2019” (average temperature).

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Insights into the development of the buildings above the norm
Introduction
The Hazard and Risk assessment provides a list of buildings that are expected to meet the norm and of
buildings which are not. This section describes the evolution of this estimate between this assessment and
the previous one (Ref. 12).
This section will show that the continued decline of production and the targeted improvements to the
exposure database (describing the building stock in Groningen) and the fragility curves (describing the
response of those buildings to ground motion) have had two main effects. Firstly, the overall assessment
of risk has decreased and consequently also the assessment of the number of buildings not meeting the
norm has decreased. Secondly, the assessment has increased the focus on specific typologies that are most
deserving of attention in the efforts to further reduce risk.
The total number of buildings not meeting the 10-5/year norm has declined from 1,478 to 780 for
Operational Strategy 2 and average temperature demand. That reduction is caused by the following
developments:





The hazard has decreased because of reduced production.
The modelled response of buildings to ground motion as captured in the so called ‘fragility curves’
has changed. Fragility and consequence models were updated among others in response to advice
from the Assurance Panel that reviewed the previous Hazard and Risk Assessment (Ref. 19).
Improvements in Groningen building stock knowledge resulted in updates to the Exposure database
EDB V6.

Generally, these developments have had a net downward effect on risk, except for the typology
representing typical farm houses with barns. This typology has been reassessed as ‘more vulnerable’
compared to the previous analysis and now dominates the stock of buildings not meeting the norm.
Of the 1,478 buildings that were previously assessed as not meeting the norm:




339 buildings are still expected not to meet the Meijdam-norm.
72 buildings have been strengthened and are now expected to meet this norm.
1,067 buildings are now expected to meet this norm. Of those, 560 still have a small probability of not
meeting the norm and are now part of the so-called ‘P90 group’.

Of the 780 houses that are now assessed as not meeting the norm:





339 were also identified in the previous assessment.
228 were identified in the previous assessment as having a small probability of not meeting the norm
(the so-called P90 group).
213 are newly identified.

The following diagram illustrates the above:

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339

Figure 6.9

Sankey diagram showing developments between ‘Basispad Kabinet’ and the current Operational Strategy 2
(average temperature demand) assessment for the buildings not meeting the 10-5/year norm.

The assessment of whether individual houses are expected to meet or not meet the Meijdam norm is one
of the inputs into the risk management policy set by the Minister (Ref. 9 to 11). How this information is
used to derive inspection and/or strengthening programmes is not described in this report and is outside
the remit of NAM.

Comparing the results of risk assessments
In this section an initial comparison is presented between the Hazard and Risk Assessment for “Basispad
Kabinet”, and the Hazard and Risk Assessment for “GTS-raming 2019” Operational Strategy 2 with average
temperature demand described in this report. To illustrate, the calendar year 2019 was chosen, also
because this is the reference year used by the “Mijnraad”. For the comparison we’ll make use of Sankey
diagrams. These are a specific type of flow diagram, in which the width of the arrows is proportional to
the number of buildings.
Figure 6.10 shows a Sankey diagram summarising the overall changes (occupied buildings) per group
defined by the “Mijnraad”:
x
x
x

Buildings with meanLPR>10-5/yr – “Mijnraad 1500” Group,
buildings with more than 10% probability of having LPR>10-5/yr, but not part of the first bullet the “P90 Group”, and
buildings not part of above risk priority groups.

On the left the numbers of buildings in these three groups are represented as they were in the assessment
of June 2018 and on the right are the numbers in the current assessment. The connections between these
illustrate the movement of the buildings in these categories between these two risk assessments.
The number of buildings above the norm decreased from 1,478 to 780. The reduction represents less than
0.5% of the total building stock. While the overall number of buildings in the P90 Group has not changed
significantly, the group membership (i.e. the specific buildings in the group) has.
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Figure 6.10

Sankey diagram summarising the changes (occupied buildings) from “Basispad Kabinet” to “GTS-raming 2019”
Operational Strategy 2 with average temperature demand.

Anticipating that most attention will be drawn to buildings with highest risk profile, the following
paragraphs focus on buildings with meanLPR>10-5/year – i.e. not meeting the Meijdam-norm.

Update to buildings above the norm
The Sankey diagram in figure 6.11 shows how risk levels have changed for the building typologies
previously above the norm (bottom left), and buildings that previously did not have meanLPR>10-5/yr, but
now do (top left). The right side of the plot shows current risk levels. The flow line colours represent EDB
V6 Primary System assignment. This figure is a more detailed version of figure 6.9 above and shows in
more detail how the status of different typologies has evolved between risk assessments.

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Figure 6.11

Sankey diagram showing risk level changes for the building previously above the norm (“Basispad Kabinet”), and
buildings that previously did not have meanLPR>10-5/yr, but now do (“GTS-raming 2019” Operational Strategy 2
with average temperature demand).

As explained in Section 2, differences are the result of a combination of the following aspects:





Reduced hazard because of reduced production from the Groningen field. It should be noted that the
reduction is not equally distributed over the whole area and depends on the Operational Strategy
chosen to distribute production over the field.
Updated Fragility and Consequence models following amongst other things advice of the assurance
panel (Ref. 19).
Improvements in Groningen building stock knowledge resulting in updated Exposure database EDB
V6.

In June 2018, 1,478 buildings assessed to be above norm covered 13 different Primary Systems (above
summarised in 7 streams; bottom left). The “GTS-raming 2019” Operational Strategy 2 average
temperature demand has 780 buildings above norm covering 3 Primary Structural systems: URM1_F,
URM4L and URM3M_U (top right).

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Typology URM1_F, representing a typical farm house with barn, is now assessed as more fragile and
dominates the buildings above the norm – almost 70% are of this type. Of the updates to the fragility and
consequence models described in section 2, an important contribution leading to a more vulnerable
building type has been the use of hazard consistent records in fragility model development. This is shown
in figure 6.11, where URM1_F buildings already identified above norm remain and some URM1_F in P90
Group and outside now have higher risk.
URM4L represents terraced masonry houses with cavity walls, concrete floors and large ground floor
openings in the façade walls. The combination of reduced hazard and updated fragility/consequence
model has resulted in a reduction of the number of these buildings above the norm. In figure 6.10 some
URM4L buildings shift to the P90 Group. Note that no previously identified URM4L buildings now have risk
above the norm (see also figure 6.13).
For the other typologies the combination of aspects mentioned above has resulted in risk reduction; those
buildings no longer have meanLPR>10-5/yr.

Improvements to Exposure Model (EDB V6)
Figure 6.12 shows for the 1,478 buildings above the norm the Typology updates that have taken place
since June 18. It is clearly visible that typology URM1 and URM3M had been split in sub-typologies
recognising that the variation with respect to seismic behaviour within these was still relatively large
compared to other typologies with higher risk potential.
The other main update relates to typology URM4L, where based on new insights some buildings have been
reassigned to:
x

x

URM3L, a similar typology but with lower openings percentage in the ground floor façade walls.
Because of recent shake table tests and modelling the cut-off percentage between the 2 typologies
has been updated.
URM7L, a similar typology but with lower openings percentage in the ground floor façade walls
and more internal walls in both directions of the building. As part of the confirmation and
validation work carried out mid last year design drawings were inspected, and these internal walls
were confirmed for some buildings.

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Figure 6.12

Sankey diagram showing for the 1,478 buildings in the “Mijnraad 1500” list the Typology updates that have taken
place since June 2018.

Figure 6.13 was made after taking a closer look at the buildings that were previously not above the norm.
It shows a comparison between the Structural System classification EDB V5 and V6. The differences can
be clarified as follows:
x

x
x

For URM1_F, partial classification and related inference rules have been improved using additional
data sources, such as geometric lay-out and farm-specific information from Dataland, in
combination with improved insight into the relationship between these data sources.
In addition, the dedicated exercise to re-evaluate buildings with low probability of belonging to a
vulnerable typology has led to the identification of several URM1_F buildings.
URM3L buildings were reassigned to URM4L based on inspection information or automated image
analyses by Ticinum Aerospace.

Figure 6.13

Sankey diagram showing the Structural System classification EDB V5 and V6 compared for buildings previously not
above norm

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Risk for gas-year 2019 / 2020
The following section focuses on the upcoming 2019/2020 gas-year (i.e., consisting of the last quarter of
2019 and the first three quarters of 2020). Because of the reducing gas production, the numbers presented
are lower than those relating to calendar year 2019 and given in previous section.

Number of buildings above the norm
Table 6.6 shows the number of buildings above the Meijdam-norm in gas-year 2019/2020. These are
shown for production profiles for an average, cold and warm year and Operation Strategy 1 and 2.
Production Profile

Reference Case
(Basispad Kabinet)
GTS-raming 2019
GTS-raming 2019
GTS-raming 2019
GTS-raming 2019
GTS-raming 2019
GTS-raming 2019
Table 6.6

Optimisation
Strategy

Temperature

Mean OIA
10-5/year

Mean OIA
10-4/year

Mean LPR
10-5/year

Mean LPR
10-4/year

-

-

389

0

786

0

Average

290

0

429

0

Average

237

0

403

0

Cold

419

0

717

0

Cold

348

0

599

0

Warm

209

0

318

0

Warm

177

0

288

0

Operational
Strategy 1
Operational
Strategy 2
Operational
Strategy 1
Operational
Strategy 2
Operational
Strategy 1
Operational
Strategy 2

Number of buildings above the Meijdam-norm in gas-year 2019/2020 for production profiles for an average, cold
and warm year and Operation Strategy 1 and 2 (note that the count includes buildings already strengthened, which
are expected to meet the norm). As a reminder, Operational Strategy 1 minimises the pwPGV and Operational
Strategy 2 minimises the event-count.

Buildings above the norm – areal maps
The overall structural-system mix for the two profiles is the same, however in Operational Strategy 2, the
buildings above the norm appear to be closer to Groningen than in Operational Strategy 1. Figure 6.14
shows the maps for the buildings above the norm in gas-year 2019/2020.
Table 6.7 shows for the average temperature profile of GTS raming 2019, the number of buildings above
the Meijdam-norm (mean LPR > 10-5/year) for gas-year 2019/2020, for the different typologies.

Table 6.7

Operational Strategy

Primary System

Count

Operational Strategy 1

URM4L

26

Operational Strategy 1

URM1_F

403

Operational Strategy 1

Already strengthened and expected to meet the norm

6

Operational Strategy 2

URM4L

19

Operational Strategy 2

URM1_F

384

Operational Strategy 2

Already strengthened and expected to meet the norm

5

The number of buildings above the Meijdam-norm (mean LPR > 10-5/year) for gas-year 2019/2020, for both
operational strategies split over the different typologies.

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Number of buildings above the Meijdam-norm of 10-5/year for production profile GTS-raming 2019,
average temperature profile and Operational Strategy 1.

Number of buildings above the Meijdam-norm of 10-5/year for production profile GTS-raming 2019,
average temperature profile and Operational Strategy 2.

138

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March 2019

Number of buildings above the Meijdam-norm of 10-5/year for production profile GTS-raming 2019,
cold temperature profile and Operational Strategy 1.

Number of buildings above the Meijdam-norm of 10-5/year for production profile GTS-raming 2019,
cold temperature profile and Operational Strategy 2.

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Number of buildings above the Meijdam-norm of 10-5/year for production profile GTS-raming 2019,
warm temperature profile and Operational Strategy 1.

Number of buildings above the Meijdam-norm of 10-5/year for production profile GTS-raming 2019,
warm temperature profile and Operational Strategy 2.
Figure 6.14

Figures on previous pages shows the maps for the buildings above the norm in gas-year 2019/2020. The maps are
provided for average, cold and warm temperature production profiles and for operational strategy 1 and 2.

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Figure 6.15 shows a reconciliation of the buildings above the Meijdam norm for the average temperature
profile in gas-year 2019/2020, between the two operational strategies. Moving from operational strategy
1 (based on population-weighted PGV) to operational strategy 2 (based on event-count) adds 57 buildings
closer to Groningen (middle panel in figure 6.15) and removes 84 buildings in the eastern part (right-hand
panel of this figure).
Figure 6.16 shows the same for the cold temperature production profile in gas-year 2019/2020. Moving
from operational strategy 1 (based on population-weighted PGV) to operational strategy 2 (based on
event-count) adds 79 buildings closer to Groningen (middle panel in the figure 6.16) and removes 223
buildings in the eastern part (right-hand panel of the same figure).

Figure 6.15

The left figure shows the buildings above the norm in both operational strategies for the average temperature
profile. Base is operational strategy 1 and the target is operational strategy 2. The middle figure shows the
buildings additionally not meeting the norm for operational strategy 2, while the middle figure shows the buildings
additionally not meeting the norm for operational strategy 1. This means that the buildings above the norm in
operational strategy 2 are the buildings indicated in the left and middle figure together. The buildings above the
norm in operational strategy 1 are the buildings indicated in the left and right figure together.

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Figure 6.16

The left figure shows the buildings above the norm in both operational strategies for the cold temperature profile.
Base is operational strategy 1 and the target is operational strategy 2. The middle figure shows the buildings
additionally not meeting the norm for operational strategy 2, while the middle figure shows the buildings
additionally not meeting the norm for operational strategy 1. This means that the buildings above the norm in
operational strategy 2 are the buildings indicated in the left and middle figure together. The buildings above the
norm in operational strategy 1 are the buildings indicated in the left and right figure together.

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Structural upgrading program
The probabilistic assessment of the number of buildings that do not meet the Meijdam Norm does not
immediately translate into an estimate of the structural strengthening scope. There are three main
reasons why the scope of the structural upgrading plan will in general be larger than the probabilistic
assessment of the number of buildings that do not meet the Meijdam norm.






Efficiency of identifying buildings with LPR >10-5/year has not yet been proven.
The Hazard and Risk Assessment is a probabilistic assessment and does not directly identify each
individual building that needs to be included in the structural upgrading plan. It identifies which
buildings have the highest risk of (partial) failure based on the building features in the Exposure
Database. If a risk-based approach is to be followed, verification of the building features as used in
the Hazard and Risk Assessment (by inspection) would be required. This means that inspection results
will either confirm the building features or otherwise, which will have implications for prioritisation
(for any subsequent engineering and strengthening). A risk-based inspection program will be able to
identify which building may need strengthening with reasonable efficiency and help prioritising the
effort.
Remaining uncertainty in Hazard and Risk Assessment.
Significant progress has been made towards assessing the risk from Groningen earthquakes.
However, uncertainty remains in the estimate of the number of buildings that do not meet the norm
based on mean LPR > 10-5/year. Further studies, experiments, modelling and building inspections can
help reduce this uncertainty.
Differences between the Hazard and Risk Assessment and NEN-NPR building code.
Ultimately the structural upgrading scope will be based on the NEN-NPR building code. Improvement
of the Hazard and Risk Assessment Updating and calibration of the building code with the latest
technical insight from laboratory experiments and modelling are likely to reduce the difference.

The probabilistic estimate of the number of buildings, where the Meijdam-Norm Safety Level is exceeded,
does therefore not directly translate into an estimate of the structural strengthening scope. However, the
Hazard and Risk Assessment provides a useful tool for prioritisation of building inspections. Ultimately the
structural upgrading scope will be based on the assessment of individual buildings based on the NEN-NPR
building code.

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7

Damage Assessment

Classification of Building Damage; Building Damage States
European Seismological Commission, EMS-1998
The EMS-98, European Seismological Commission, 1998 (Ref. 43) document provides guidelines for
estimation of the intensity of an earthquake based on the damage assessment of buildings.
Damage of buildings is assessed on the basis of a damage classification. This is provided for two main
categories: unreinforced masonry buildings (URM) and reinforced concrete (RC) buildings. Figure 7.2
describes the 5 distinguished damage grades for both main categories. The description of the damage
states in this figure are purely qualitative. For instance, “negligible to slight damage” is termed DS1,
“moderate damage” DS2, “substantial to heavy damage" DS3”. The EMS scale relates DS1 to “hairline
cracks in very few walls”, DS2 to “cracks in many walls” and DS3 to “large and extensive cracks in most
walls”. The qualitative descriptions of the building damage states form a very useful, practical and
generally accepted and applied classification system for building damage.

Figure 7.1

Cover of the “European Macroseismic Scale 1998, EMS-98”by the European Seismological Commission (G.
Grünthal), 1998.

144

Figure 7.2

145

Classification of damage to masonry buildings (left) and classification of damage to reinforced concrete buildings (right). Illustration taken from EMS-98, European
Seismological Commission, 1998 (Ref. 43).

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019

Forecast for Damage State 1 (DS1) aesthetic damage
The report “Methodology Prognosis of Building Damage and Study and Data Acquisition Plan for
Building Damage” (Ref. 44), issued February 2017, describes the studies program into building damage
and the methodology for forecasting building damage. The building damage assessment of November
2017 (Ref. 5) contains an introduction into the classification of damage states and into the Monte Carlo
method used for forecasting building damage and fatality risk.
This section presents the forecast of building damage from DS1 on production profile “GTS-Raming
2019”. The higher damage states DS4 and DS5 are relevant for risk and have been addressed in the
previous sections of this report. For the assessment of DS1 building damage, empirical methods based
on analysis of historical damage data are used.
The approach to forecast DS1 based on observed damage from historical earthquakes is described in
section 8 of the report “Induced Seismicity in Groningen, Assessment of Hazard, Building Damage and
Risk – November 2017” (Ref. 5, pages 168-173). An update of that work has been prepared In June
2018 (Ref. 12, pages 9-11).
This section describes a further update and incorporate the latest information and knowledge available
in the following areas:
x
x

Production from the Groningen field “GTS-raming 2019”
Exposure database V6 (EDB)

Earthquake catalogue of events
For the forecast, a range of possible future realizations is needed that adequately represent the
anticipated earthquake distribution, both in terms of magnitude and location in the field. These have
been generated stochastically, using the hazard tool for the Operational Strategy 1 and Operational
Strategy 2 based on the average temperature demand profile. These are the same profiles as used for
the full Hazard and Risk Assessment. In the Monte Carlo simulation process, repeated random
sampling of a set of input distributions is used to create a probabilistic distribution output. So-called
‘synthetic earthquake catalogues’ (i.e. event locations and magnitudes for the period 2019-2028) are
generated from the input probability distributions of total seismic moment, number of events and
event epicentres. This forecast uses events between ML = 1.8 and 4.0.

Exposure model
The exposure database (EDB V6 Ref. 22) is an extract of a project database and consists mainly of the
building typology classifications and several other building related attributes, including the population,
arranged per building.
In addition to its use as input into the Hazard and Risk Modelling, the EDB deliverable also provides the
necessary information to assign the TNO typologies to all 257,997 Buildings (“Basisregistratie adressen
en gebouwen (BAG)” from the Kadaster) in the area considered for damage forecast.
The area of interest is the same for the Hazard and Risk Assessment and is based on the Groningen gas
field outline. The extract boundary for the EDB V6 is a 5 km buffer around the gas field outline.

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Table 7.1 shows how the different type of buildings present in the Groningen building stock have been
assigned to the typologies used by TNO.

Table 7.1

Assignment of EDB V6 typologies to the typologies used in the TNO Kalibratiestudie.

Although it has been recognized that secondary buildings representing ca. 40% of all buildings mainly
consisting of sheds, garages and other small normally unoccupied buildings could also incur damage,
they have been excluded from the forecast because damage data/reports are unavailable for such
structures. A sensitivity analysis, with assumed fragility function like Low Rise buildings after 1940,
shows that secondary buildings may perhaps add up to ca. 60% additional damage cases.
Due to the absence of damage observations in the earlier TNO studies, fragility function for Low Rise
buildings after 1940 have also been assigned to all High-Rise buildings. This is believed to be a
conservative assumption.

Results
Figure 7.3 shows results of the DS1 damage forecast in the form of an annual F/N curve for the
Groningen field area, one per year, shown for the period 2019-2028.
The median forecast (P50 or 50%) is indicated together with the 80% confidence interval (10% to 90%).
Each building in the exposure area was assigned with a relevant typology. It was assumed that any
resulting building damage is repaired after the event and before the next one (instant repair).
The figure shows that in 2019 a fifty percent chance that more than 100 buildings will be damaged
with aesthetic damage (DS1) (due to all earthquakes in that year smaller than ML=4). In 2028 there is
a fifty percent chance that more than 10 buildings will be damaged with aesthetic damage.
Figure 7.4 shows the Mean and P50 for the DS1 damage forecast per year for the period 2019-2028.
Due to the skewed distribution of building damage the mean number of damaged buildings is
considerably higher than the P50.
The DS1 damage forecasts for both operational strategies are very similar, with a maximum difference
of between 10 and 20 damaged buildings per year.

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Operational Strategy 1

Operational Strategy 2

Figure 7.3

DS1 Forecast per year for period 2019-2028 based on the middle branch of the logic tree, shown for “GTSRaming 2019” Operational Strategy 1 and 2 average temperature demand profile.

148

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Operational Strategy 1

Operational Strategy 2

Figure 7.4

Mean and P50 DS1 Forecast per year for period 2018-2028 based on the middle branch of the logic tree, shown
for “GTS-Raming 2019” Operational Strategy 1 and 2 average temperature demand profile.

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Forecast for Damage State 2 (DS2) and Damage State 3 (DS3)
Fragility functions for DS2 and DS3 have been developed for each structural system identified in the
exposure model using the extensive analytical modelling and experimental test campaign described in
(Ref. 27). F/N curves have been calculated with the Monte Carlo risk engine which show the annual
frequency of exceedance (F) of different numbers of groups of buildings (N) which simultaneously
reach DS2 or DS3. Figure 7.5 shows the F/N curve for the whole field for each of the years in the period
2018 to 2027. The F/N curves for two consecutive 5-year periods (2019 to 2024 and 2025 to 2028) are
shown in figure 7.6.
Figure 7.5 shows that in 2019, the annual frequency of exceedance of having anywhere 100 buildings
simultaneously damaged to DS2 in a given earthquake is around 5% and the chance that 10 buildings
are simultaneously damaged to DS3 in a given earthquake is a bit lower.
Figure 7.7 shows the exceedance damage count for the occurrence of the given damage state (DS).
For instance, in 2019, the chance of 10 or more buildings reaching a DS2 damage state is about 11%.
The chance that 100 buildings or more reach damage state DS3 is less than 2%. In Figure 7.8 DS2 and
DS3 damage is compared for the two operational strategies. Differences are less than 1%.

150

Figure 7.5

2025

2024

2026

2021

2027

2022

2028

2023

151

Maatschappelijk risico for building damage DS2 and DS3 (MR(S)) for the whole field for the years 2019 to the years 2028. The production is based on an average temperature
year using the “Operational Strategy 2”.

2020

2019

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019

Figure 7.6

Maatschappelijk risico for building damage DS2 and DS3 (MR(S)) for the whole field for the years 2019 to the years 2028.

2019 - 2024

2025 - 2028

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019

152

Seismic Risk Assessment of Production Profile “GTS-raming 2019” for the Groningen field
March 2019

Average Temperature Production Profile

Cold Temperature Production Profile

Figure 7.7a

Maatschappelijk risico for building damage DS2 and DS3 (MR(S)) for the whole field for the years 2019 to the
years 2028.

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March 2019

Warm Temperature Production Profile

Reference Production Profile

Figure 7.7b

Maatschappelijk risico for building damage DS2 and DS3 (MR(S)) for the whole field for the years 2019 to the
years 2028.

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March 2019

Figure 7.8

Maatschappelijk risico for building damage DS2 and DS3 (MR(S)) for the whole field for the years 2019 to the
years 2028, based on average temperature production profile of GTS-raming 2019. The results for both
operational strategy 1 and 2 are shown.

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8

References

All reports referenced in this section prepared by NAM can be downloaded from the webpage
“onderzoeksrapporten” on www.nam.nl.
1
2

3
4
5
6

7
8
9
10
11
12

13
14

15

16
17

18

Winningsplan Groningen – 2016, NAM, April 2016
Technical Addendum to the Winningsplan Groningen 2016 - Production, Subsidence, Induced Earthquakes
and Seismic Hazard and Risk Assessment in the Groningen Field, Parts I to 5, Nederlandse Aardolie
Maatschappij BV (Jan van Elk, Jeroen Uilenreef and Dirk Doornhof, eds), April 2016
Instemmingsbesluit Winningsplan Groningenveld, Ministerie van Economische Zaken, Directoraatgeneraal Energie, Telecom & Mededinging, Directie Energie en Omgeving, 30 September 2016
Wijziging Instemmingsbesluit Winningsplan Groningenveld, Ministerie van Economische Zaken,
Directoraat-Generaal Energie, Telecom & Mededinging, Directie Energie en Omgeving, 23 May 2017
Induced Seismicity in Groningen, Assessment of Hazard, Building Damage and Risk – November 2017,
NAM (Jan van Elk and Dirk Doornhof), November 2017.
Seismic risk assessment for a selection of seismic risk production scenarios for the Groningen field Addendum to: Induced Seismicity in Groningen Assessment of Hazard, Building Damage and Risk
(November 2017), Jan van Elk, Assaf Mar-Or, Leendert Geurtsen, Per Valvatne, Eddy Kuperus and Dirk
Doornhof, March 2018.
Letter to Parliament “Gaswinning Groningen”, 29th March 2018, Minister of Economic Affairs and Climate
Policy.
Letter “Verwachtingenbrief aanvulling winningsplan Groningenveld 2016” to NAM, 2nd May 2018,
Minister of Economic Affairs and Climate Policy.
Eerste advies Adviescommissie ‘Omgaan met risico’s van geïnduceerde aardbevingen’ 23rd June 2015,
Tweede advies Omgaan met hazard- en risicoberekeningen in het belang van handelingsperspectief voor
Groningen Adviescommissie ‘Omgaan met risico’s van geïnduceerde aardbevingen’ 29th October 2015,
Eindadvies Handelingsperspectief voor Groningen Adviescommissie ‘Omgaan met risico’s van
geïnduceerde aardbevingen’ (Commissie-Meijdam), 14th December 2015
Seismic Risk Assessment for Production Scenario “Basispad Kabinet” for the Groningen field - Addendum
to: Induced Seismicity in Groningen Assessment of Hazard, Building Damage and Risk (November 2017),
Jan van Elk, Assaf Mar-Or, Leendert Geurtsen, Per Valvatne, Eddy Kuperus and Dirk Doornhof, June 2018
Assessment of Subsidence based on Production Scenario “Basispad Kabinet” for the Groningen field, Dirk
Doornhof and Onno van der Wal, June 2018
Assessment of Building Damage based on Production Scenario “Basispad Kabinet” for the Groningen field
- Addendum to: Induced Seismicity in Groningen Assessment of Hazard, Building Damage and Risk
(November 2017), Jeroen Uilenreef, Jan van Elk and Assaf Mar-Or, June 2018
Sensitivity of the Hazard and Risk Assessment for Production Scenario “Basispad Kabinet” to the inclusion
of release of Tectonic Stresses - Addendum to: Induced Seismicity in Groningen Assessment of Hazard,
Building Damage and Risk (November 2017), Jan van Elk, Assaf Mar-Or and Dirk Doornhof, September
2018
Letter to Parliament “Betreft Voortgang maatregelen gaswinningsbrief”, 6 juni 2018, Minister of Economic
Affairs and Climate Policy.
Verwachtingenbrief “verzoek tot voorspellen van twee operationele strategieen voor het gas-jaar 20192020”, Ministerie van Economische Zaken en Klimaat met 13 Februari 2019 met bijlage “raming benodigd
Groningenvolume en capaciteit gas-jaar 2019/2020 en verder”, Gasunie Transport Services, Februari
2019.
Software verification against Experimental benchmark data Numerical evaluation of the seismic response
of nonmasonry (non-URM) buildings in the Groningen region, Rui Pinho, Federica Bianchi, Roberto
Nascimbene, Mosayk, NAM, July 2015.

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20
21
22
23
24
25
26
27
28
29
30
31
32
33

34
35
36

37

38
39

40

Assurance Meeting on Exposure, Fragility and Fatality Models for the Groningen Building Stock (Long
Version), Letter and Report Assurance Panel, Mar 2018.
Groningen Earthquakes - Structural Upgrading, Exposure Database V2, ARUP, Ikumi Nakanishi, Thomas
Paul, Dirk Jan Oostwoud Wijdenes, September 2015
Hazard and Risk Assessment for Induced Seismicity in Groningen, NAM, Nov 2015.
V5 Exposure Model - data documentation with Appendix post-analysis report, ARUP, Dec 2017.
Exposure Database (EDB) voor het gebied van het Groningen veld - Stand van Zaken juni 2018, Jeroen
Uilenreef, Jan van Elk en Assaf Mar-Or, NAM, July 2018.
Exposure Database (EDB) voor het gebied van het Groningen veld - Stand van Zaken september 2018,
Jeroen Uilenreef, Jan van Elk en Assaf Mar-Or, NAM, Sept 2018.
Review and update of Study and Data Acquisition Plan Induced Seismicity in Groningen, Assessment
timing: January 2019, NAM, Jan van Elk and Dirk Doornhof, January 2019 (under review).
Development of v2 partial collapse fragility and consequence functions for the Groningen field, Helen
Crowley, Rui Pinho, Barbara Polidoro and Peter Stafford, November 2015
Report on the v5 Fragility and Consequence Models for the Groningen Gas Field, Helen Crowley and Rui
Pinho, November 2017
Report on soil-structure interaction (SSI) impedance functions for SDOF systems, Mosayk, 20 th October
2015.
Risk Assessment of Falling Hazards in Earthquakes in the Groningen region, Tony Taig and Florence Pickup
(TTAC Ltd.), March 2016.
Risk Assessment of Falling Hazards in Earthquakes in the Groningen region (Appendices), Tony Taig and
Florence Pickup (TTAC Ltd.), March 2016.
Production Optimisation 2018, Per Valvatne, Leendert Geurtsen, Assaf Mar-Or, Gosia Kaleta, Jan Limbeck
and Gerard Joosten, NAM, October 2018.
Letter to Ministry of Economic Affairs: NAM Productie Optimalisatie Studie: Beoordeling en advies,
T.F.Kockelkoren, SodM, 16 October 2018.
Letter to the Ministry of Econimic Affaits and Climate Policy: Beoordeling toepasbaarheid resultaten
rapport "Optimisation of the Production Distribution over the Groningen field to reduce Seismicity",
T.F.Kockelkoren, SodM, 20 februari 2018.
Bouwstenen voor Operationele Strategie Groningenveld 2018/2019, NAM, 15/6/2018.
Groningen Dynamic Model Update 2017 – V5, Quint de Zeeuw and Leendert Geurtsen, EP201806200206,
June 2018.
V5 Ground-Motion Model (GMM) for the Groningen Field, Julian J Bommer, Benjamin Edwards, Pauline P
Kruiver, Adrian Rodriguez-Marek, Peter J Stafford, Bernard Dost, Michail Ntinalexis, Elmer Ruigrok and
Jesper Spetzler, Independent Consultant, Delares, KNMI, Oct 2017.
V4 Ground-motion Model (GMM) for Response Spectral Accelerations, Peak Ground Velocity and
Significant Duration in the Groningen field, Julian Bommer, Bernard Dost, Benjamin Edwards, Pauline P
Kruiver, Pier Meijers, Michail Ntinalexis, Adrian Rodriguez-Marek, Elmer Ruigrok, Jesper Spetzler and
Peter Stafford, Independent Consultants, Deltares and KNMI, June 2017
SBR, Trillingsrichtlijn deel A – Schade aan Gebouwen, Stichting Bouw Research, Rotterdam, 52 pp., 2017.
Eerste advies panel van hoogleraren over risicobeleid en veiligheidsmaatregelen geïnduceerd
aardbevingsrisico, panel van hoogleraren, bestaande uit prof. dr. Eric Cator (Applied stochastics, Radboud
Universiteit Nijmegen), prof. dr. Ira Helsloot (Besturen van veiligheid, Radboud Universiteit Nijmegen) en
prof. dr. ir. Jan Rots (Structural mechanics, Technische Universiteit Delft), 27-6-2018.
Eerste deel van aanvullend advies over veiligheidsrisico’s van infrastructuur en cumulatie-effecten van
geïnduceerde aardbevingen, panel van hoogleraren, bestaande uit prof. dr. Eric Cator (Applied
stochastics, Radboud Universiteit Nijmegen), prof. dr. Ira Helsloot (Besturen van veiligheid, Radboud
Universiteit Nijmegen) en prof. dr. ir. Jan Rots (Structural mechanics, Technische Universiteit Delft), 16
oktober 2018

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42

43
44
45
46

47
48
49

Addendum op advies panel van hoogleraren over risicobeleid en veiligheidsmaatregelen geïnduceerd
aardbevingsrisico panel van hoogleraren, bestaande uit prof. dr. Eric Cator (Applied stochastics, Radboud
Universiteit Nijmegen), prof. dr. Ira Helsloot (Besturen van veiligheid, Radboud Universiteit Nijmegen) en
prof. dr. ir. Jan Rots (Structural mechanics, Technische Universiteit Delft)8 november 2018
Met het oog op de tijd - Een blik op de tijdsbesteding van Nederlanders, Sociaal en Cultureel Plan
Bureau, Mariëlle Cloïn (red.), November 2013,
https://www.scp.nl/Publicaties/Alle_publicaties/Publicaties_2013/Met_het_oog_op_de_tijd
European Seismological Commission (G. Grü nthal), European Macroseismic Scale 1998, EMS-98, 1998
Methodology Prognosis of Building Damage and Study and Data Acquisition Plan for Building Damage,
Nederlandse Aardolie Maatschappij BV (Jan van Elk, Jeroen Uilenreef & Dirk Doornhof), 30 January 2017
Instemmingsbesluit Groningen gasveld 2018-2019, Minister of Economic Affairs and Climate Policy,
14/11/2018.
Briefadvies panel van hoogleraren over de berekening van de gemiddelde verblijfsduur in verschillende
type bouwwerken, Panel van Hoogleraren (Prof. dr Eric Cator, prof. dr. Ira Helsloot en prof. dr. Jan Rots),
2nd February 2019.
Beoordeling advies “berekening gemiddelde verblijfsduur” van het panel van hoogleraren, SodM, 11 th
February 2019.
Kamerbrief “Advies hooglerarenpanel over berekening aardbevingsrisico”, Ministerie van Economische
Zaken en Klimaat, 7th maart 2019.
Crowley H., Pinho R. & Cavalieri F. (2019) “Report on the v6 Fragility and Consequence Models for the
Groningen Field.

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Appendix A – Correspondence
Verwachtingenbrief (Expectation Letter)

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Letter Advies hooglerarenpanel over berekening aardbevingsrisico (7-3-2019)

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