Corso di Dottorato Regionale in Scienze della Terra
PhD Course in Earth Sciences
XXX Ciclo – 30
thCycle
2014 – 2017
Daniele Maestrelli
“Structural setting and deformation rates along the external margin
of the Northern Apennines, with implications for the deep fluids
migration”.
Tutore - Supervisor: Prof. Federico Sani
Co-tutore(i) - Co-Supervisor(s): Dr. Marco Bonini
Dr. David Iacopini
Coordinatore del Corso di Dottorato
Prof. Carlo Baroni
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Abstract………...…...p. 5
Riassunto……….………...p. 7
1. Introduction an aims of the thesis..………...p. 9
2. Methodology………....p. 12
2.1. Fieldwork and structural analysis………..………....p. 12
2.1.1. Field mapping and revision……….….p. 12
2.1.2. Mesoscopic structural analysis………....p. 12
2.2. Interpretation of seismic reflection profiles………...p. 15
2.2.1. 2D and 3D seismic interpretation.………...p. 16
2.2.2. Image post-processing and attribute analysis………...p. 16
2.2.2.1. Seismic attributes………p. 17
2.2.2.2. Colour blend………p. 19
2.2.3. Geobody interpretation……….p. 20
2.3. Trishear modelling………...……….p. 21
2.4. Aerial photos and satellite images interpretation……….p. 22
2.5. Static and Dynamic stress calculation………p. 24
2.5.1. Dynamic stress changes………...………….p. 25
2.5.2. Static stress changes………..p. 26
3. The Emilia-Romagna Apennine margin: structures, recent tectonic
activity and deformation rates...p. 31
3.1. Introduction and aims of the study………..p. 31
3.2. Geological framework……….….p. 33
3.3. Field and seismic evidence of Pede Apennine Thrust-related
deformation……….p. 36
3.3.1. Geological, structural and seismic data………...……..p. 37
3.3.1.1. Savignano sul Panaro and Castelvetro………...p. 37
3.3.1.2. Sassuolo (Secchia River)-Scandiano……...…………...p. 40
3.3.1.3. Quattro Castella………...…..p. 41
3.3.2. Stratigraphic and sedimentological data………...………p. 44
3.3.2.1. The Enza and Panaro sections………...………..p. 44
3.3.2.2. The Secchia sections………...………...p. 45
3.3.2.3. Synthesis of the observation on the AEI syntems……...p. 47
3.3.3. Pedological analysis:a further indication of recent activity…..p. 49
3.4. Numerical modelling of PAT-related structures……….……….p. 53
3.4.1. Analysis of deformation rates………...….p. 57
3.5. Discussion and final consideration……….p. 60
4. Fluid migration along the Emilia-Ramagna Pede-Apennine margin:
relationship between tectonics and mud volcanoes………p. 64
4.1. Introduction to mud volcanism and to the mud volcanoes of the
Emila-Romagna Pede-Apennine margin………...p. 64
4.1.1. Mud volcanism: a brief introduction……….p. 64
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4.1.1.2. Insights into Italian mud volcano geochemistry…………p. 67
4.1.2. Mud volcanoes of the Emilia-Romagna Pede-Apennine
margin………...………...p. 69
4.2. Seismic interpretation of Pede-Apennine margin: structures and
mud volcanoes………....…p. 71
4.3. The “Dragone di Sassuno” case study………...p. 73
4.3.1. Field data……….p. 74
4.3.2. Insights from aerial photos interpretation………...…p. 78
4.3.3. PAT-related seismicity and induced mud volcano eruptions:
investigating Static and Dynamic stress changes………..p. 84
4.4. Mud volcanism and active structures: discussion and conclusions
on the Emilia-Romagna Pede-Apennine Margin mud volcanoes……..p. 90
5. Fluid migration along the Marche Pede-Apennine margin………...p. 92
5.1. Introduction and geological framework………...……….p. 92
5.2. Structures and fluid migration: the S.Paolo di Jesi and Maiolati
Spontini case study……….………p. 94
5.3. Structures and fluid migration: the Monteleone di Fermo case
study……….p. 97
5.3.1. Local geological framework……….………p. 99
5.3.2. Geological, structural and seismic data……….……p. 99
5.4. Structure and fluid migration: the Offida case study…………..……...p. 101
5.5. Seismicity influence on fluid migration……….………...p. 109
5.5.1. The Monteleone di Fermo eruptions in response to the 2016
Central Italy seismic sequence………..…….p. 109
5.5.1.1. Summary of the Central Italy seismic sequence
and mud volcano eruptions……….………p. 110
5.5.1.2. Peak ground velocity and dynamic stress changes….p. 114
5.5.1.3. Static stress changes………....p. 115
5.5.1.4. Discussing the role of dynamic and static stress
changes at Monteleone di Fermo………...….p. 118
5.5.2. A further, possible case of seismic triggering for the
Monteleone mud volcanoes………..….p. 122
5.5.3. The Contrada S. Lazzaro (Offida) December 1959 eruption..p. 123
5.5.3.1.
Calculation of Static stress changes………....p. 124
5.5.3.2.
Discussing static and dynamic stress effect…...p. 126
5.5.4. Concluding remarks……….……...p. 126
6. Seismic analogues of fluid-migration pathways and relation with
structures: the case studies of the Loyal Field and Ceará Basin……...p. 128
6.1. Introduction to analogues investigation………..…....p. 128
6.2. The Loyal Field case study……….……p. 129
6.2.1. Fluid migration pathways: features, meaning and
problematic………...…....p. 129
6.2.2. Dataset………...p. 130
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6.2.3. Specific methodology………..…….p. 132
6.2.3.1. Methodology for pipes structural analysis…….…...p. 132
6.2.3.2. Methodology for pipes statistical analysis (two-
Points statistic)………....….p. 133
6.2.4. Geological setting………..……...p. 133
6.2.4.1. Tectonic and structural framework……….…………..p. 133
6.2.4.2. Main stratigraphy……….……...……p. 135
6.2.5. Results………..…………..p. 136
6.2.5.1. Preliminary considerations: insight into the Loyal
Field seismic volume………...p. 136
6.2.5.2. Seismic characterization of fluid escape pipes in the
Loyal Field………...…...p. 138
6.2.5.3. Lateral versus vertical flow migration using partial
stack……….……...p. 145
6.2.5.4. Fault and fracture patterns……….……p. 146
6.2.6. Discussion……….……p. 151
6.2.6.1. Fluid versus solid material intrusion………….……...p. 151
6.2.6.2. Pipes alignment and structural control……….…...…p. 152
6.2.6.3. Evolutionary model……….……...….p. 153
6.2.7. Conclusive remarks………....…….p. 156
6.3. The Ceará Basin case study: evidence for a sedimentary driven
Focused fluid flow……….…...p. 157
6.3.1. Dataset and geological framework……….………...p. 158
6.3.2. Sedimentary architectures and fluid migration pathways….………....p. 159
6.3.3. Discussion: a model for sedimentary focused fluid
migration pathways……….…….….p. 163
6.3.3.1. Sediment architecture and vertical fluid pathways….p. 163
6.3.3.2. Down-slope arrays that nucleated the ‘canyons’…...p. 165
6.3.4. Concluding remarks………...….p. 166
7. Comparing mud volcanoes of the Northern Apennines and their
Seismic analogues: a conceptual model for fluid migration …...p. 167
8. General conclusions and remarks………...p. 173
8.1. The Emilia-Romagna Pede-Apennine Margin and its mud
volcanoes...p. 173
8.2. The Marche Pede-Apennine Margin and its mud volcanoes…....…...p. 174
8.3. Seismic analogues of mud volcanoes………...p. 174
8.4. Final remarks……….……..p. 175
9. References………..……...p. 177
Acknowledgments………..………...p. 206
Appendix
Appendix A to Chapter 3……….….….p. 207
Appendix B to Chapter 5………..…….p. 217
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Abstract
The principal aim of this Ph.D. thesis was the investigation of the structural setting of the external Northern Apennine margin, in the Emilia-Romagna and Marche Region, as well as the analysis of possible relations linking the structure of the margin and the migration of deep fluids. This last phenomenon is responsible for the formation of the so-called mud volcanoes, which are of particular interest for our study and that have been investigated with a multidisciplinary approach. First, I investigated the structural setting of the Emilia-Romagna pede-Apennine margin, including possible relations with the mud volcanoes of the area. The same study approach was used for the Marche foothills, and for their associated mud volcanoes. Furthermore, I studied two 3D seismic dataset from different tectonic contexts, to be used as analogues for investigation of mud volcanoes and -more in general- fluid migration processes. The Emilia Romagna Pede-Apennine Margin has been analysed using a multidisciplinary approach, integrating structural, sedimentological, pedological and seismic data. In addition, I carried, for two target transects crossing the margin (at Quattro Castella and Scandiano localities), cinematic 2D cross section numerical modelling of the main structure, the so-called Pede-Apennine Thrust (PAT). The implemented Trishear deformation mechanism, has shown how the studied sector (between the Enza and Panaro rivers) has been tectonically active in recent times. The PAT is poorly exposed and deforms at least Middle Pleistocene deposits. These semi-consolidated sediments, investigated from a sedimentological point of view, revealed that the PAT and its related structures influenced also the river drainage pattern, forcing paleo-rivers to flow parallel to the margin (which roughly strikes NW-SE), at least in some sectors during the Pleistocene. This trend is also visible in extremely recent deposits, outcropping in the vicinity of the margin at the Ghiardo Plateau, that have been dated using the OSL technique applied to deformed palaeosoils. Dating highlighted an extremely recent tectonic phase (~60-80 kyr). Numerical modelling allowed us to calculate PAT deformation rates. Of particular interest are the slip rates, which reach maximum values up to 0.68-0.79 mm/yr for the last 0.8-1.2 Ma. In the same sector, extended toward the west to also include the Bologna area, I performed an analysis of the relationships between fluid migration and structural framework, which is believed to be directly responsible for the formation of the locally outcropping mud volcanoes. Subsurface structures were mapped using seismic sections, confirming a straightforward correspondence between anticlines and mud volcanoes, being generally located on the anticline surface projection (roughly close to the anticline axis or in the anticline’s forelimb/backlimb). In particular, I investigated the Dragone di Sassuno mud volcano, evidencing this correlation and the link between the upward migrating fluids and the fracture array associated to the associated anticline: fluids exploit systematic fractures to reach the surface. An in depth analysis was carried out to investigate possible relationships linking the seismic activity of the PAT and the mud volcano eruptions. I investigated three seismic events with M > 4 occurred between 1779 and 1780 and I modelled the variation of static stresses associated to these
6 earthquakes, that occurred almost contemporaneously to large eruption of the Dragone di Sassuno mud volcano, as described by the Author Serafino Calindri at the time of eruption. I observed that static stress changes have not been responsible for triggering the mud volcano eruption, being the calculated values negative. Negative values imply that the fractures forming the feeder dyke systems were maintained closed by the stresses, inhibiting the fluid flow. Therefore, I propose a correspondence between the dynamic stresses associated with these earthquakes and the mud volcano eruptions: dynamic stresses, shaking the reservoir, are able to increase overpressures and therefore favour the eruptions. Mud volcanoes have been investigated also along the Marche Apennine foothill, with particular focus on the mud volcano systems located in three key areas: S. Paolo di Jesi, Monteleone di Fermo and Offida. As for the Emilia-Romagna mud volcanoes, I characterized the structural setting of these systems using field and seismic data. Also in these cases, a correspondence between mud volcano and anticline structures has been observed. For the Monteloene di Fermo and Offida mud volcanoes eruptions, I investigated the possibility of seismic triggering. An interesting case study was offered by the activation of the Monteloene di Fermo mud volcanoes coincident with three major earthquakes of the 2016-2017 Central Italy seismic sequence. I verified that the dynamic stress associated with the seismic events and calculated at the mud volcano location was high enough (>4 bar) to be considered the main trigger of mud volcano activation. Normal stress changes were too small (less than 0.1 bar) to have had any influence on the triggering. Summarizing, I verified a “direct” relationship between structures (anticlines) and mud volcanoes, which steers their location, and an “indirect” one, linking the activation of seismic structures (also far from the mud volcanoes location, ~70-80 km) and the mud volcano eruptions. As a final investigation, I used two 3D seismic analogues from the Loyal Filed (Scotland) and from the Caerá Basin (Brazil) as seismic analogues for fluid migration mechanisms. The first dataset, highlighted fundamental similarities between the so called “fluid escape pipes” -here widely distributed- and mud volcanoes. Both are linked to anticline structures, and fluids responsible for their formation exploit systematic fractures to migrate upward. In addition, the fluid responsible for the Loyal Field fluid escape pipes formation, revealed to be composed of a mud-water-hydrocarbons mixture, as in the case of the Italian mud volcanoes. A further analogy is represented by the evolution and activity of these geological objects, alternating periods of large eruptions to periods of quiescence. The second dataset evidenced the presence of a very significant amount of depressions resembling pockmarks at the seabottom, generally indicating the presence of a strong fluid flux. Therefore, it has been analysed in order to obtain further information on a seismic analogue on fluid migration mechanisms and possible relation with structures. Nonetheless, this analogue case study from a different tectonic context highlighted the dependence of these fluid migration pathways on large-scale sediment waves, vertically stacking their permeable trough to form preferential paths for fluid “passive” migration. Therefore, in this case I did not highlight any correspondence between tectonic structures and fluid migration.
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Riassunto
“Assetto strutturale e tassi di deformazione lungo il margine esterno dell’Appennino Settentrionale, con implicazioni per la migrazione di fluidi profondi”
Scopo principale di questa tesi di dottorato è l’analisi dell’assetto strutturale del margine esterno dell’Appennino Settentrionale Emiliano-Romagnolo e Marchigiano, nonché lo studio delle relazioni che intercorrono tra le strutture ivi presenti e la migrazione di fluidi profondi. Tale fenomeno, nell’area di studio comporta la formazione di cosiddetti vulcanelli di fango (mud volcanoes), ben conosciuti ed investigati nel settore Emiliano-Romagnolo, tuttavia meno studiati in quello Marchigiano. Inoltre, tale studio ha visto l’utilizzo di dataset sismici 3D, provenienti da altri contesti tettonici, utili per l’investigazione dettagliata delle strutture, geometrie, meccanismi di messa in posto e processi evolutivi di analoghi dei vulcanelli di fango. Il margine Appenninico Emiliano-Romagnolo è stato investigato con un approccio multidisciplinare, integrando dati strutturali, sedimentologici, pedologici e sismici. In aggiunta, si è proceduto, per due transetti individuati attraverso di esso, ad impostare una modellizzazione numerica -effettuata applicando il metodo deformativo del Trishear- atta a calcolare i tassi di deformazione della principale struttura del margine, il cosiddetto Thrust Pedeappenninico (PAT). L’analisi ha messo in evidenza come il settore studiato (compreso tra le Valli del Fiume Panaro e del Fiume Enza) sia interessato da un’attività tettonica recente. Il PAT infatti, spesso emergente o sub-emergente, deforma depositi Medio Pleistocenici. Tali depositi, investigati da un punto di vista sedimentologico, hanno messo in evidenza come le strutture del margine abbiano condizionato non solo l’evoluzione tettonica del margine stesso, ma anche il reticolo idrografico dei paleo-corsi d’acqua. Si è messo in evidenza infatti come durante il Pleistocene Medio questi fossero orientati parallelamente al margine Appenninico, almeno per alcuni tratti. Tale orientamento si riscontra anche in depositi estremamente recenti, e localizzati a fronte del margine in corrispondenza del Plateau di Ghiardo. Datazioni OSL di suoli ivi deformati hanno permesso di individuare fasi tettoniche relative a circa 60-80 kyr. La modellizzazione numerica ha permesso di calcolare i tassi di deformazione del PAT, ed in particolare gli slip rate, che sono risultati essere compresi nell’ordine di 0,68-0,79 mm/anno per gli ultimi 0,8-1,2 Ma. Nello stesso settore, e in quello immediatamente circostante la città di Bologna, si è dunque provveduto ad investigare le relazioni intercorrenti tra le strutture del margine e i fluidi responsabili della formazione dei mud volcanoes. Sezioni sismiche hanno permesso di mappare le strutture del sottosuolo e constatare la corrispondenza tra anticlinali e vulcanelli. In particolare, uno studio di dettaglio sul vulcanello denominato Dragone di Sassuno, ha messo in evidenza questa dipendenza, nonché l’ulteriore relazione intercorrente tra strutture e fluidi: questi, nella risalita verso la superficie, utilizzano infatti i sistemi di frattura associati all’anticlinale sul quale il vulcanello giace, e che probabilmente svolge in profondità il ruolo di trappola per i fluidi stessi. Come ulteriore approfondimento della tematica, si è provveduto ad indagare possibili correlazioni tra l’accadimento di
8 terremoti storici e l’attivazione di tale vulcanello di fango. È stato possibile modellizzare le variazioni degli stress statici associati a tre eventi sismici di M> 4 occorsi tra il 1779 ed il 1780, in concomitanza di forti eruzioni del vulcanello di Sassuno, descritte dettagliatamente dall’Autore Serafino Calindri al tempo dell’eruzione. In questo caso si è osservato che tale variazione degli stress non può aver avuto un’influenza positiva sulle attivazioni, essendo i valori ottenuti negativi. Tali valori indicano infatti condizioni sfavorevoli all’apertura del complesso di fratture costituenti il feeder dyke system del vulcanello. Si è ipotizzato quindi, data la corrispondenza temporale tra eventi sismici ed attivazione del vulcanello, una possibile dipendenza di tali attivazioni dagli stress dinamici, transitori ed associati al passaggio delle onde sismiche. Vulcanelli di fango sono stati individuati ed investigati anche lungo il Margine Apenninico Marchigiano, con particolare focus su tre aree chiave: S.Paolo di Jesi, Montelone di Fermo e Offida. Anche in questo caso si è provveduto a caratterizzarne l’assetto strutturale con rilievo di campagna ed utilizzo di sezioni sismiche. Come nel caso dei vulcanelli emiliani, si è riscontrata una corrispondenza tra anticlinali -in questo caso sepolte-, strutture ad esse associate e vulcanelli di fango. Per i vulcanelli di Monteleone di Fermo e di Offida, si è provveduto ad indagare la possibilità di attivazione a seguito di triggering sismico. Un caso particolarmente interessante è rappresentato dall’attivazione dei vulcanelli di Monteleone di Fermo a seguito degli eventi sismici dell’Italia Centrale, verificatisi a partire dal 24 Agosto 2016. Si è potuto verificare come i valori degli stress dinamici calcolati in corrispondenza dei vulcanelli attivati siano sufficientemente elevati (>4 bar) da essere considerati la principale causa di attivazione, considerando anche i non sufficienti valori degli stress statici (<0.1 bar). In questo caso, le relazioni intercorrenti tra strutture e migrazione di fluidi è duplice. Una relazione “diretta” tra strutture (anticlinali) e vulcanelli, che ne condiziona il posizionamento, ed una “indiretta” tra attivazione di strutture sismogenetiche distanti dai vulcanelli (>70-80 km) e l’innesco delle eruzioni. Come ultima analisi si è provveduto ad utilizzare due volumi sismici 3D provenienti dal Loyal Field (Scozia) e dal Bacino di Ceará (Brasile). Il primo dataset ha messo in evidenza fondamentali punti di similarità tra l’evoluzione delle cosiddette “fluid escape pipes” e i vulcanelli di fango. Entrambe le tipologie di oggetti geologici sono strettamente dipendenti dall’assetto strutturale delle anticlinali che ne ospitano i reservoir e dalle geometrie dei sistemi di frattura che favoriscono la risalita dei fluidi verso la superficie. In aggiunta, il fluido responsabile della formazione delle fluid escape pipes del Loyal field è risultato essere composto da una mistura contenente fango-acqua-idrocarburi, come nel caso dei vulcanelli di fango italiani. Ulteriore analogia risiede nell’evoluzione dell’attività delle fluid escape pipes e dei vulcanelli, entrambi alternanti periodi di quiescenza a periodi di intensa attività eruttiva. Nel caso del Bacino di Ceará, la presenza sul fondale marino di oggetti assimilabili a pockmarks, ovvero zone depresse indicanti l’emissione di fluidi, è risultata essere uno stimolo per l’analisi del dataset, nell’ottica di un’ulteriore analisi dei processi che guidano la migrazione dei fluidi stessi. Lo studio ha però messo in evidenza come queste depressioni siano in realtà associate a forme di fondo (sediment waves), impilate in maniera tale da formare condotti di migrazione preferenziale, tuttavia passiva, per i fluidi intrappolati nel sottostante reservoir, in maniera indipendente da strutture tettoniche.
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1. Introduction and aims of the thesis
This introduction furnishes an overview of the thesis, by describing the aims and the approaches used during our work. The main aim of this study was the investigation of the structural setting of the northern Apennine margin, and its role in controlling the migration of deep fluids. A series of peculiar case studies has allowed us to explore the relationships between the structures of the margin and fluid migration therein, with particular focus on mud volcanism, a process involving the migration of a mud-water-hydrocarbon mixture from a deep subsurface up to the surface. Mud volcanism is in fact widely distributed all along the northern Apennine foothills (Emilia-Romagna and Marche regions), and is genetically and spatially associated with the structures of the margin. The link between fluid migration and structures can be double. Besides a “direct” link, represented by the structural controls on fluid migration, which is geometrically and genetically dependent on the fluid reservoir and the fluid migration pathways (e.g. a mud volcano system emplaced along a structure acting as fluid trap and influencing the upward migration of fluids), an “indirect” link can be defined. This indirect dependence is represented by the influence of seismogenic structures (also located far away from the mud volcano area) upon the activation of mud volcanoes (i.e. seismic triggering due to stress variations associated with seismic events). Mud volcanoes of particular interest are located along the Emilia-Romagna Pede-Apennine Margin, and have been thoroughly studied (e.g. Capozzi and Picotti, 2002, 2010 Bonini, 2008, 2012, 2013), while less documented are the mud volcanoes in the Marche Apennine foothills.
After the description of the adopted methodology (Chapter 2), a starting point for our work is the investigation of the Pede-Apennine Margin in the Emilia-Romagna region (Chapter 3), in a sector between the Enza River to the west and the Panaro River to the east. In this sector, I have performed the analyses of the Apennine Thrust Front (PTF; e.g. Boccaletti et al., 1985), known also as Pede-Apennine Thrust (PAT). I aimed to build up a structural framework, in which structural data, together with sedimentological, pedological, and seismic data could contribute to highlight the role of the PAT in the shaping of the margin, up to recent times. Furthermore, in order to quantitatively describe this influence, I have carried out a numerical analysis of deformation rates (i.e. slip rate, propagation rate etc.) of the PAT, using the trishear forward modelling. In this and adjoining areas, several mud volcanoes are present and appear to have a direct relation with the structural setting of the margin (e.g. they are located at the top of anticlines occurring along the margin itself). The definition of the possible structural controls on mud volcanoes is a further aim of this thesis. In Chapter 4, several seismic lines were used to investigate the subsurface in correspondence of mud volcano systems along the PAT, and fieldwork data have been collected to complete this analysis. In some favourable cases, aerial photographs have been used to characterize their recent activity (about last ≈70 years, even if scattered during this time span).This analysis, together with literature data, was useful to characterize historical mud volcanoes
10 eruptions. Particularly, I evaluated the role of dynamic and static stress changes associated to historical and recent seismic events in the possible triggering of eruption of target mud volcanoes, located in the study area. A similar approach was used to investigate the relation between structures and mud volcanoes of the Marche Apennine foothill (Chapter 5) by integrating seismic line interpretation, field (mainly structural) data, together with aerial photos and literature data. These analyses aim at the definition of the broader structural setting of the mud volcanoe system of the Apennine foothills. A further step is the characterization of their activity, investigating as in the case of the Emilia-Romagna area, a potential correlation between seismic events and paroxysmal eruptions of mud volcanoes. This approach is used for historical eruptions, and in particular, for the unique and favourable case study offered by the 2016-2017 central Italy seismic sequence. After the 24th August 2016, a series of moderate
to large earthquakes stroke the Amatrice-Norcia area (Lazio-Umbria regions), and the effect of the seismic events appears to have strongly influenced the activity of some of the mud volcanoes distributed along the Marche Apennine foothills. I investigated these mud volcanoes, located in the Fermo province, near the Monteleone di Fermo village, from a structural point of view in the September 2015. Eleven months later, the same mud volcanoes erupted after the destructive Mw 6.0 24 August 2016 earthquake.
These mud volcano systems promptly responded after the following major seismic events of the sequence, suggesting a strong correlation between seismic events and mud volcano triggering. Structural and seismic data were used to constrain the numerical modelling of the Coulomb (static) stress changes induced by the major seismic events, while seismological data (peak groud velocity, PGV) were used to model the dynamic stress changes. This analysis has provided new insights into the structural setting of mud volcano systems along the Apennine margin and clarified the role of dynamic and static stresses on fluid emissions. Unfortunately, the mentioned analysis characterises the mud volcano systems only at a large scale, as the available seismic reflection data are at too low resolution to image the feeder dyke systems and reservoirs, as well as the small-scale dependence of fluid migration from fracture/faults patterns. The opportunity for a more detailed investigation (Chapter 6) of these peculiar seal bypass system (i.e. a complex of geological features able to drive the upward migration of fluids, bypassing the seal; Carthwright et al., 2007) is offered by the analysis of an “analogue dataset” derived by the re-appraisal of the Loyal Field, an oil and gas productive field located northwest of the Shetland Island, in the North Sea, (Scotland, UK). In detail, the Loyal Field is located on the south-westernmost edge of the Faroe-Shetland trough, a channel derived by the evolution of an abandoned rift into an area of inversion tectonics, during Paleocene-Eocene times. The high-resolution studied dataset images a series of large fluid escape pipes, which show clear indication of an upward migrating hydrocarbon-bearing fluid, with a muddy matrix, that is a fluid physically not too dissimilar from the mud volcanoes fluid. Furthermore, also geometrical evidence supports the idea that these fluid migration pathways have comparable features with mud volcanoes, and are here settled at the top of a buried anticline related to compressional tectonic phases. In addition, the high resolution seismics allows the detailed investigation of the internal architecture of the conduits and their relation with fractures/faults patterns, an analysis
11 that was not possible for the Italian mud volcanoes. Therefore, even if the tectonic environment is not a collisional thrust-and-fold belt, as for the Italian mud volcanoes, inversion tectonics in the Faroe-Shetland Trough is responsible for the development of compressive structures, to which fluid migration is related. All the mentioned features make the Loyal Field dataset a favourable and complementary analogue for the study of mud volcanoes of the Italian Apennines. In addition, I further investigate fluid migration processes using a supplementary dataset from the offshore of the Caeará State, Brazil. This dataset, here named Ceará Basin and released by PGS Company, is interesting in that it shows a series of impressive depressions on the seabottom, similar to fluid pockmarks, thereby indicating the possible presence of fluid migration at the seabed. It is noteworthy that the Cearà Basin is located on the Brazilian passive margin, and therefore it offers the opportunity to investigate such processes in a different tectonic contexts.
Each chapter starts with an introductive part addressing the discussed topic, with specific discussions and conclusions at the end of the chapter. In Chapter 7 I give a comprehensive discussion on the analysed mud volcanoes and their seismic analogues, illustrating a conceptual model for fluid migration. Afterwards, Chapter 8 elaborates comprehensive conclusions, with the aim to reconcile the analyses of fluid migration processes and their relationships with the structures conducted on the Apennine margin, with investigation of fluid migration processes imaged by seismic datasets elsewere (particularly the Loyal Field).
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2. Methodology
In this chapter, I describe in detail the methodology adopted during this PhD work. Due to the multidisciplinary approach of this study, I report in separate sections a general description of every used method. I made large use of field and seismic reflection data with the aim to constrain tectonic structures and to highlight the role of these structures in the migration of fluids (e.g. relations between anticlines and fault patterns and fluid migration pathways). In addition, such an approach was integrated with a variety of further investigations with specific methodology, requiring a detailed explanation.
2.1. Fieldwork and structural analysis
2.1.1. Field mapping and revisionAreas of particular interest along the Pede-Apennine Margin were surveyed in order to potentially revise previous published geological map, and to map new geological features aiming at the investigation of the recent activity of structures and at the definition of the relationships among local geology, structural setting and fluid migration (i.e. mud volcanoes). In particular, a revision of the stratigraphy outcropping along the Emilia Romagna Pede-Apennine Margin was necessary, due to the high number of units (of also different rank) forming the deposit representing the the many published geological maps. Due to the time-transgressive nature of these deposits, due to the asynchronous regression of the sea level from west to east in the Po Plain, and as a consequence of the eastwards progression of the margin uplift (Boccaletti et al., 2004; Gunderson et al., 2014), similar sediments were deposed at different times along the margin. Therefore, these units have been mapped with different names. In order to reconcile this discrepancy I subdivided them on the basis of similar sedimentological features, stratigraphic position and age range (see Section 3.2). Fieldwork information derived from this analysis was used to set the application of the Trishear modelling to the PAT, as explained in Section 3.3.
2.1.2. Mesoscopic Structural analysis
Along the Emilia-Romagna Apennine margin, the structural analysis mainly consisted in the collection of brittle mesoscopic structures used for stress inversion analysis to reconstruct the stress fields acting at the time of the studied deformation. The collected brittle structures belong to three main types: mesoscopic faults with clear kinematic indicators, mesoscopic faults with no visible or unclear kinematic indicators, and joints, that is purely dilatant fractures. Only structures showing a complete kinematic characterization can be used to extrapolate a stress field. This requirement is fulfilled by measuring fault plane parameters, such as dip direction, dip, and pitch of lineations, (the latter suggested by kinematic indicators, e.g. slikenlines with indication of shear sense, produced by striation objects, growth mineral fibres, etc.). Nonetheless, extensional joints, and faults with no evidence of kinematic indicators,
13 (therefore not able to constrain a complete and clear kinematic framework), still represent a valuable dataset to integrate the obtained paleo-stress fields, and were included in our analysis. Along the Emilia-Romagna Pede-Apennine Margin, brittle mesoscopic structures were mainly collected along major river incisions, which dissect the margin and create favourable conditions for good exposures. Outside this favourable natural traverses the Pede-Apennine Margin is strongly vegetated or, where the morphology is smother, quite modified by human activity, a condition not favourable for structural surveying. Furthermore, lithologies outcropping along the Emilia Romagna Pede-Apennine Margin are mainly represented by Plio-Pleistocene marine to transitional deposits composed of mudstones and semi-consolidated sandstones. Pleistocene to Holocene continental deposits are constituted by fluvial conglomerate and sandstone alternated to lacustrine shales. These lithologies, generally are not favourable for kinematic indicators preservation due to low degree of lithification, cementation and, in these cases, low lithstatic charge (being them really young and shallow. Therefore the distribution of structural data in the study area may appear locally concentrated but also quite scarce at places. Regardless, joints and faults were mainly observed in the Pliocene marine mudstones and in the fine-sediment portion of the fluvial Pleistocene Synthems.
In order to determine the paleo-stress tensors and the orientation of the principal stress axes, I applied the right dihedron inversion method to the collected fault populations (Angelier and Mechler, 1977; Caputo and Caputo, 1988). This method implies the individuation of areas in a stereonet, having the maximum probability to contain the maximum or minimum stress axis, respectively. To this graphical method, Caputo and Caputo (1988) have introduced the condition of orthogonality among stress axes, using the Conditioned Least Square Method (CLSM). Thus, the output results consist of the orientation of the three principal axis of the stress ellipsoid. Data have been elaborated using the FAULT software (Caputo and Caputo; 1988).
Mesoscopic faults and joints were studied and measured, where possible, also with the aim to reconstruct the surficial structural setting of mud volcanoes along the Emilia Romagna and Marche Pede-Apennine Margin. Orientations of mesoscopic brittle structures were used to constrain the trend of mud volcanoes feeder dyke systems, which are generally identifiable at the surface as spatially associated iso-oriented mesoscopic extensional joints, and/or mud vents and fluid seeps alignments. Furthermore, mud volcanoes have been suggested to be related to deep anticline structures (Jakubov et al., 1971; Bonini, 2008, 2012; Fig. 2.1a). This is in agreement with the muddy/watery mixture containing hydrocarbons, responsible for reservoir overpressures that drive the fluid mixture to surface. Classically, hydrocarbon reservoirs are associated with anticline structures, acting as fluid traps. Therefore, the link between folds and mud volcanoes has been investigated, and folds were analysed during the fieldwork. In particular, it has been suggested a relation between fold-related joints and mud volcano vents (e.g. Bonini, 2012; Fig. 2.1b). Mud volcanoes may be strongly influenced by the ac and bc distribution: following the Hancock (1985) classification, a, b, and c are three arbitrary and orthogonal Cartesian axes, referring to
14 a given fold. Axis b is always parallel to the fold axis, ab plane is always parallel to stratification and c is always perpendicular to the stratification (Hancock, 1985). Therefore, the ac and bc joints are those respectively orthogonal and parallel to the fold axis plane (Fig. 2.1b). When the presence of mud volcanoes was not related to an outcropping anticline I have investigated the structural pattern using the available seismic reflection lines (see Section 3.2 for description of the approach used in seismic interpretation). Furthermore, I used structural data on mud volcanoes to constrain the calculation of static stress (generated by selected seismic events) at mud volcanoes positions (see Section 3.6 for the methods) and therefore investigate the evolution of mud volcano activity.
Fig. 2.1. (a) 3D cartoon showing the structural relation between ac-bc joint systems in a thrust-related anticline
and the location of mud volcanoes. The latter tend to be located at the top of the anticline (acting as fluid traps and creating overpressured reservoirs) and are often aligned along ac and bc joint systems. Mud volcano eruptions can generate a great fluid discharge, creating a violent overpressure decrease in the most superficial reservoir and resulting in a caldera collapse. Caldera elongation tends to align along “fold axis-parallel” directions, in agreement with the local stress field. PPT: Plicene-Pleistocene claystones; EPL: Epi-Ligurian sequence; LU: Ligurian Units; MA: Marnoso Arenacea formation. Encircled numbers are: (1) bottom of the main fluid conduit or diatreme, and pressurised (2) deep and (3) shallow fluid reservoirs. The asterisk marks the LU and MA contact, which is inferred to be an hydraulic interface at depth (modified from Bonini, 2012). (b) Hancock (1985) classification of fold-related anticline joints (modified from Ramsay & Huber, 1987)
15
2.2. Interpretation of seismic reflection profiles
Fieldwork analysis was integrated by the interpretation of seismic reflection profiles that were used to specifically address the following issues:
Structural setting of target sectors of the Pede-Apennine in the Emilia-Romagna and Marche regions;
Structural constraint on migration of fluid pathways (i.e. mostly mud volcanoes) along the Emilia-Romagna and Marche Apennine foothills;
Study of the fluid migration pathways in seismic analogues from different tectonic contexts, for comparison with mud volcanoes seal bypass systems.
The seismic dataset used for the Apennine area consists of a series of 2D seismic reflection profiles acquired by ENI and AGIP during the last decades and that were kindly provided by ENI S.p.A. for this thesis.
Moreover, the seismics used for the study of fluid migration pathways as analogues for mud volcanoes of the Apennines consist of two different datasets. A first one, the so called “Loyal Field” dataset (Fig. 2.2) has been released by the British Petroleum (BP) and given to Aberdeen University, where the seismic interpretation took place in the SeisLAB facility.
Fig. 2.2. Picture showing target sections of the three-dimensional Loyal Field dataset (inline, crossline, time-slice).
16 The second dataset, from the “Ceará Basin” was released to Aberdeen University by PGS Company. Both datasets consist of high-resolution 3D seismic data. In the following sections, I describe the methodology adopted for their elaboration and interpretation.
2.2.1. 2D and 3D seismic interpretation
To interpret the 2D ENI-Agip seismic lines, and the 3D Loyal Field and Ceará datasets I had to apply a different approach. This discrepancy does not derive from the two- and three-dimensional characteristics of the different datasets, but is due instead to the different file format. Both the Loyal Field and Ceará seismic volume were available in a Segway format, and were therefore analysed using specific seismic interpretation softwares, while 2D seismic lines of the Apennine foothills were available only as raster images, and therefore they were interpreted with a classic line-drawing approach. Where available, deep wells were used to correlate seismic data to stratigraphy, and image postprocessing was applied to the datasets to enhance the interpretation.
I mapped target horizons both for 2D and 3D seismic data (manually in the case of the 2D raster images, or interactively in the case of the three dimensional Segway datasets). The 2D seismic interpretation focused on the manual piking of target reflectors, and reflector truncations, to highlight structural features (faults/fractures, and folds) or areas of fluid leaking. In the case of 2D sections, due to their scale, the interpretation yielded large-scale information, not allowing the small-scale analysis of reflectors or areas of seismic disruption that might be observed, for example, in the vicinity of mud volcano systems. On the contrary, a more detailed analysis was possible for the 3D datasets, for which the seismic resolution was high enough to image these kinds of features. The 3D seismic datasets were mapped using Petrel® (Schlumberger, 2016 and previous version) and Geoteric® (ffA). The major reflectors were mapped. Interpretation was carried out by manually picking seismic reflections on a line-by-line basis with a grid increment spacing of 2x2 (representing a separation of 25m x 25m for both Loyal Field and Ceará datasets) on inlines, crosslines and using arbitrary lines when required. Particularly, the faults mapping largely proceeded on time-slice as well, to better follow the 3D layout of their planes.
2.2.2. Image post-processing and attribute analysis
In order to enhance the seismic imaging and interpretation, a series of tools were used on our dataset to extract “seismic attributes” (Fig. 2.3). Seismic attributes are algorithms that manipulate the seismic data and return outputs able to highlight features of interest, as, for example faults and fractures, or to enhance the imaging quality of the dataset itself. In our work, I made extensive use of these tools, and introduce here below the main used attributes. A further visualization and analysis method, only applied to the 3D Loyal Field dataset, makes use of “colour blend”, an algorithm able to merge seismic attributes, and to visualize them at the same time, enhancing imaging quality and interpretation processes.
17 Fig. 2.3. Examples of seismic attributes used for the analysis of our seismic datasets, here showing the same cross-section depicting the faults pattern. (a) Cosine of phase attribute; (b) Variance attribute; (c) Trace Automatic Gain Control (AGC) attribute; (d) Instantaneous phase attribute. Seismic courtesy of BP.
2.2.2.1. Seismic attributes
Cosine of phase
The calculation of the Cosine of phase (Fig. 2.3a) of the seismic dataset allows the identification of zones of structural discontinuities, enhancing the visualization of fault and fracture zones in areas of poor seismic signal. Particularly, it was used, in addition to Variance attribute, to map the fault patterns in our datasets (both 2D and 3D).
Variance
The Variance volume attribute (Fig. 2.3b) has been used with the aim to better visualize the 3D fault pattern observed in the dataset. The Variance (the opposite of coherency) is calculated in three dimensions across a volume dataset and represents trace-to-trace variability over a particular sample interval producing interpretable lateral changes in acoustic impedance (see Chopra and Marfurt, 2007). Similar traces produce low variance coefficients, while discontinuities have high coefficients. Because faults may cause discontinuities between neighbouring lithologies and, as a result in the trace-to-trace variability visualisation of the variance, it helps fault detection in 3D seismic volumes (Koson et al., 2014). Variance can thus be seen as the lateral counterpart of amplitude analysis as the latter indicates vertical variations.
18 Envelope
Envelope attribute displays “bright” events (or better acustically strong events), for both negative and positive amplitudes. The envelope represents the instantaneous energy of the signal and is proportional in its magnitude to the reflection coefficient. The envelope is generally used to highlight discontinuities (e.g. fractures and faults) changes in lithology, and other features. Furthermore, bright spots highlighted by this attribute algorithm are able to indicate the presence of gas (Koson et al., 2014).
Root Mean Square (RMS)
The RMS attribute represents a post-stack attribute that computes the square root of the sum of squared amplitudes divided by the number of samples within the specified window used (Koson et al., 2014). The subsequent RMS values are assigned a colour, on a scale bar, and visualised. With the root mean square amplitude, a qualitative estimation of the reflectivity can be obtained in order to map areas where the amplitude shows a fast change within the zone of interest. A positive anomaly in the RMS value could be correlated, among other things, with the presence of fluids. However, RMS is sensitive to noise as it squares every value within the window; as a consequence, the final colour expression is only partly related to the relative post stack amplitude value.
Automatic Gain Control (AGC)
AGC attribute (Fig. 2.3c and 2.4b) is able to rescale amplitude values with the normalized RMS amplitude over a specified mobile window. This attribute was fundamental in our interpretation process due to its ability to boost poor seismic reflection and proportionally augment their visibility. Besides, it has the problem to boost the seismic noise as well, and must be used carefully. Applied to the Loyal Field dataset, it was fundamental for the visualization and interpretation of the deep portion of the seismic volume that was affected by poor quality (Fig. 2.4).
Fig. 2.4. Picture showing the enhancing effect of the Trace AGC seismic attribute. (a) A sampled inline cross
section imaged with the normal seismic, with no seismic attribute applied. (b) The same inline cross section shown in (a) after the application of the Trace AGC attribute. Amplitude are rescaled in a proportional way to highlight areas were the seismic signal is poor. This attribute applied to the Loyal Field dataset is particularly efficient on the imaging of the deep portion of the seismic volume. Seismic courtesy of BP.
19 Diapir
The Diapir algorithm (specifically run in Geoteric®) is able to highlight low amplitude areas in the seimic
dataset and therefore it is especially useful to detect salt diapirs and gas chimneys. It is calculated dividing the “Chaos” attribute by the Root mean Square of the Envelope attribute. Chaos attribute is in fact able to detect and display chaotic textures of the seismic data, marking reflector disruptions. Zones of maximum chaoticness indicate discontinuity zones (e.g., fault and fracture zones, angular unconformities; Koson et al., 2014).
2.2.2.2. Colour blend
A further and efficient tool used for seismic imaging and interpretation is the colour blend algorithm. As briefly explained above, this tool is able to merge and visualize at the same time up to three previously generated seismic attributes (Fig. 2.5).
Fig. 2.5. A post-processed example using a colour blend for the Loyal Field dataset, obtained in Geoteric®. Three
different seismic attributes were merged together (and assigned different colours in the RGB scale) to form a new seismic cube. In this case, red colours, corresponding to the Diapir attribute, perfectly highlight the position of fluid escape pipes. (a) Time slice, and (b) inline cross section.
20 This method allows comparison between different geological features highlighted by different seismic attributes. I used this approach the compare the geospatial distribution of fluid escape pipes and fault fractures in the Loyal Field dataset. I merged in a colour blend, Diapir, Semblance and Dip and Azimuth. The algorithm assigns to each attribute a colour in the RGB scale. As example, in Figure 2.5 the red colours corresponds to the Diapir attribute (useful to visualize fluid escape pipes) while, green and blue colours correspond to Semblance and Dip and Azimuth attributes respectively. The two latter attributes, in a way similar to Variance, are good to highlight faults and fractures discontinuities.
2.2.3. Geobody interpretation
A three-dimensional seismic dataset allow the interpreter “to play” with geological objects in an “all-around” way: the possibility to scroll seismic lines and to navigate throughout the seismic volume permits the investigation of seismic features, depicting in our case fluid migration pathways, in an intriguing way. Since I are interested in the evaluation of the fluid migration pathway geometry, the three dimensionality of our datasets was of great importance. Seismic interpretation software such as Petrel® and Geoteric® used in this thesis, gives the possibility to navigate the seismic volume along the
three main directions (inline, crossline and time-slices) or to generate target intersection lines randomly oriented (arbitrary lines). In addition, these two softwares have the further ability to isolate a selected seismic object and generate a 3D interactive rendering of it. This process is called “geobody extraction” and allowed as to map, isolate and reconstruct the three dimensional shape of target fluid migration pathways, in both the Loyal Field and Ceará Basin datasets (Fig. 2.6).
The Geobody extraction requires the isolation of the volume where the geological object of interest is located, by “cropping” the original seismic volume. Once a smaller dataset is obtained, an “opacity” calibration is necessary. The interpreter can filter-out from the cropped volume all the amplitude frequencies that are not of interest. As example, in the case of a gas chimney, the interpreter may want to preserve “neutral” (i.e. close to zero values) amplitudes that are generally associated with the disruption effect of gas passage through the stratigraphic sequence. The software allows the interpreter to assign opacity (0-100%) to each amplitude frequency. In the prospected example, assigning 0% opacity to low and high seismic amplitudes, and 100% opacity amplitude values close to zero, would lead in a transparent rendering of the background, highlighting the gas chimney conduit. A further step is the “voxel extraction” from the cropped ad filtered volume containing the geological object. This procedure allows the quantization of the target objects, by assigning voxels (3D cells with a defined dimension) to the filtered amplitudes and generating the geobody (Fig. 2.6). If the original seismic volume is time-to-depth converted, this procedure allows assigning defined volumes to voxels, and therefore the entire volume of the geobody can be calculated.
21
Fig. 2.6. Example of a fluid migration pathway goebody. (a) A fluid migration pathway from the “Ceará Basin”
was selected for extraction of the 3D geobody, depicting the fluid conduit. In this picture, the 3D geobody is superposed onto a single seismic section, to evidence the conduit shape, while in (b) the geobody is extracted and isolated. To generate this particular geobody, high values (positive and negative) frequencies were isolated from the background, in agreement with the idea that “brights” are associated with the presence of fluids. In this, case, stacked “brights” materialize the fluid migration pathway. Seismic courtesy of BP.
2.3. Trishear modelling
One of the aim of this thesis was to evaluate the potential for slip of the structure of the Pede-Apennine Margin. As explained in Pargraph 3.1, I collected structural data along the Emilia-Romagna Pede-Apennine Margin; the Marche Pede-Apennine margin was surveyed as well, but the structural fieldwork was here difficult due to the low number of outcrops. In fact, the broad and gentle Pede-Apennine foothills, intensively farmed, do not represent a favourable condition for outcrop preservation and, therefore, this area was investigated by using different methods (e.g. seismic interpretation). The methodology that is presented here below was thus applied only to the Emilia-Romagna sector, where field data were available as an input for the Trishear modelling.
In particular, I performed numerical modelling to estimate the rates of deformation related to the Pede-Apennine Thrust (PAT), which marks the boundary between the Pede-Apennine foothills and the Po Plain. Obtaining these rates is of primary importance, considering the historical seismicity of the area and its
22 potential hazard. This approach was already successfully applied along other sectors of this margin (Picotti and Pazzaglia, 2008; Wilson et al., 2009, Gunderson et al., 2013), as well as in other geological contexts (e.g. Bump, 2003; Gold et al., 2006; Jara et al., 2009; Cardozo and Brandenburg, 2014). To reach this goal I used the Trishear fault-propagation folding mechanism (hereinafter referred to as Trishear, developed by Erslev, 1991; see also Suppe and Medwedeff, 1990; Erselv, 1991; Suppe et al., 1992; Hardy and Ford, 1997). Trishear was applied to our case study by means of the free FaultFold software (ver. 4.5.4) available at http://www.geo.cornell.edu/geology/faculty/RWA/programs/), which uses the algorithms described by Allmendinger (1998) and Zehnder and Allmendinger (2000), applying a forward modelling approach.
Deformation along the Emilia-Romagna Pede-Apennine Margin adapts well to the Fault propagation folding mechanism (Suppe and Medwedeff, 1990), which is considered, together with the Fault-bend folding mechanism of Suppe (1983), responsible for the formation of similar fault-related folds. Opposite to the Fault-bend folding mechanism, in the Fault-propagation folding the propagation of the fault generates a fault-related fold that accommodates deformations at the fault tip. This deformation mechanism generates folds that are comparable to folds observed along the Pede-Apennine Margin, where the Pede Apennine Thrust, during its upward propagation, generates anticline folds constituting the margin itself. Syntectonic sedimentation, observed along the margin as growth strata developed on top of hanging wall units, can be successfully applied to a specific case of the Fault-propagation folding, defined by Erslev (1991) and named Trishear fault-propagation folding. This specific mechanism refers to the presence of a triangular deformation zone at the fault tip. Using an analytical approach, the Erslev (1991) demonstrates that this particular mechanism is in reality a specific case of Simple Shear deformation, in which the area of deformation (the so called Trishear area) departs from the fault tip with an angle (Trishear angle) larger than zero.
Due to the prospected similarity between the natural case (PAT-related deformation observed along the Emilia-Romagna Apennine Margin) and the analogue cases numerically modelled by this mechanism (Picotti and Pazzaglia, 2008; Wilson et al., 2009, Gunderson et al., 2013), I applied the Trishear mechanism to two transects of the Emilia-Romagna Apennine Margin, following the procedure described in Section 3.4.
2.4. Aerial photos and satellite images interpretation
Mud volcanoes are widespread along the Northern Apennine foothills and have a long documentation history. For example, in 91 B.C. the Roman writer Plinius in his Naturalis Historia, described the eruption -nowadays associated with a local large earthquake (Guidoboni, 1989) of a mud volcano, which has been identified with the Salse di Montegibbio and/or the Salse di Nirano, which are both located not
23 far from Modena, on the Emilia-Romagna Pede-Apennine Margin (e.g., Bonini, 2009). Nonetheless, documentation like this important written chronicle is scattered in time, and thus it is generally difficult to compare the historical dataset with the geological record. In order to characterize the evolution and activity of mud volcanoes, in relation to the structures of the Pede-Apennine Margin and to fluid migration, an effort to overtake the difficulty of historical data recruitment can be attempted by using satellite images (for very recent times) and aerial photos (for the several tens of years). This kind of data, although scattered in time, can help in recognizing mud volcano features that are not anymore visible in the field, due for example to the anthropic influence on the landscape. I used satellite images available on the web (i.e. Google Earth images) and aerial photos acquired during last 70-80 years by the IGM (Fig. 2.7), the Istituto Geografico Militare of Italy, to evaluate the past setting of target mud volcanoes. This operation was particularly useful to identify ancient mud volcanoes flows, emission points and their alignments.
Fig. 2.7. (a) Selected frame from the 1956 IGM flight, covering the Monterenzio (Bologna, Emilia Romagna) and
adjoining areas. (b) Close-up of the target area in (a) showing the “Dragone di Sassuno” mud volcano, as it appeared in 1956. At that time, two emission points were identifiable, while nowadays (c) only a single vent is visible in the field. The photo was taken on 22nd June 2016.
Aerial photos were also useful to locate literature structural data associated with mud volcanoes. For example, Damiani (1964) carried on a structural survey of the Offida mud volcano (Marche region) after a large eruption that took place in 1959. Several edifices appearing in his detailed topographic maps, together with the structural survey, are not present in the field nowadays. The used satellite images cover a time span of 13 years (2003-2016) while available aerial photos acquired by the IGM cover a time span -yet discontinuous- of 55 years (1945-2000). The classic aerial photo interpretation generally
24 requires an ortho-photo rectification process. In our case, due to our small-scale investigation (Fig. 2.7), only the restricted portion of interest of each photo (i.e. including the mud volcano features) has been geo-referenced to a base image (generally represented by a new satellite image). This has been done using ArcGIS® software.
2.5. Static and Dynamic stress calculation
In order to investigate the relation between the tectonic structures of the Emilia-Romagna and Marche Pede-Apennine Margin and fluid migration – in addition to the structural survey and to the seismic interpretation- I quantitatively analysed the mud volcanoes systems distributed along the Apennine foothills. Mud volcanoes are considered seal-bypass systems (e.g. Cartwright et al., 2007) due to their ability to focus the fluid flow from deep and superficial reservoir and crosscut the stratigraphic sequence up to the surface. The fluids of mud volcanos are typically composed of a water and mud mixture, with a certain component of hydrocarbons (e.g. Minissale et al., 2000; Capozzi and Picotti, 2010; Martinelli et al., 2012; Tassi et al., 2012). The gaseous fraction can trigger the upraising of the fluid-mud mix, due to the ability to exolve from the watery/muddy mixture and to enhance the overpressure, in a way similar to the well-known magmatic processes. Because fluid reservoirs often concentrate at the core of anticlines (e.g. Bonini, 2012) -due to the ability of these structures to act as structural traps- mud volcanoes are frequently located at the top of them or in their vicinity, and are strictly related to their associated brittle structures, such as fault and fracture systems. Mud volcano systems evolve alternating cyclical periods of quiescence to periods of strong paroxysmal activity, a cyclic nature that can depend on various causes (e.g., rainfall variation, anthropic influence, cyclical variations of the discharge amount of hydrocarbons from the reservoir etc.; e.g., Kopf, 2002). Nonetheless, it can happen that a mud volcano system, close to its eruption threshold, might be triggered by the increased overpressure in the reservoir due to the occurrence of a seismic event. Such earthquakes can modify the local stress field (the so-called permanent static stress changes) or can shake the reservoir causing the exolution of gas from the fluid. The latter behaviour is associated with the transient passage of seismic waves and their stress perturbation (dynamic stress changes). I therefore aim to investigate the possible relations between seismic events that occurred along the Pede-Apennine Margin, or that were associated with more distant structures, but that were large enough to influence the mud volcanoes of the margin (e.g., the 2009 L’Aquila earthquake, and the 2016-2017 central Italy seismic sequence). In the following two sections, I explain the rationale of the dynamic stress and static stress changes, which have been applied to the eruptions experienced by the mud volcanoes of the Emilia-Romagna and Marche Pede-Apennine Margin.
25 2.5.1. Dynamic stress changes
The passage of seismic waves generated by large earthquakes induces transient changes in stress at remote distances that can trigger local seismicity (Hill, 2008), and also enhance activity at volcanic systems (Manga et al., 2009, 2012; Delle Donne et al., 2010; Avouris et al., 2017) by perturbing the dynamic equilibrium of crustal fluids (Hill, 2008).
To estimate the dynamic stress generated by the passing seismic waves, I use peak ground velocity (PGV) field from the Amatrice, Norcia, and Montereale-Capitignano-Campotosto earthquakes, since peak ground velocity scales with the peak dynamic stress. Earthquake peak ground velocities can be converted to stress using the following equation (Gomberg and Davis, 1996; Hill et al., 1993; Van Der Elst and Brodsky, 2010; Hong et al., 2016):
𝜎𝑟= 𝜇 𝑃𝐺𝑉
𝛽 (1)
where r is the radial peak dynamic stress, PGV is the peak ground velocities, is the shear wave
velocity, and is the shear modulus. The shear modulus can be derived from: 𝜇 = 𝜌𝛽2 (2)
where is the rock density. PGV for the Amatrice and Norcia seismic events are available in the ANSS Comprehensive Earthquake Online Catalog (USGS, available on the web at https://earthquake.usgs.gov/earthquakes/search/; Fig 2.8), which includes worldwide earthquake source parameters and other related products such as peak ground accelerations and velocities measured by contributing local seismic networks. PGVs at the mud volcano sites have been then obtained by interpolating peak velocity measured by all seismic stations located within an area of ~36 x 103 km2.
PGV at the Earth surface is assumed to be comparable to the PGV experienced by the mud-fluid reservoir. The elastic parameters needed for calculating the peak dynamic stress are assumed to be in the range of the typical rock velocities (e.g. Bourbié et al., 1987), considering a host rock for the fluid-mud reservoir made of porous and saturated sandstones, such as those of the Laga Fm. in the study area (see Section 5.3). I then used the following parameters to calculate the minimum and maximum bounds of peak dynamic stress:
rock density () ranging from 2100 and 2400 kgm-3 shear wave velocities ()ranging from 800 to 1800 m/s
I used MATLAB® to generate PGV and Dynamic stress peak distribution maps for each selected
earthquake, in order to evaluate the possible dependence of accelerations and dynamic stress values on mud volcanos position, in the effort to establish possible seismic triggering relations. For each seismic event, the PGV and the minimum and maximum dynamic stress peak distribution were plotted.
26
Fig. 2.8. Peak Ground Velocity distribution map, form the USGS earthquake catalogue (available at
https://earthquake.usgs.gov/earthquakes/search/) for the 30th October 2016 Norcia seismic event, Central Italy.
Numerical data used by USGS to realize this map were obtained from the catalogue and (applying a refinement filtering out seismic station showing acquisition problems) were used to create accurate PGV maps and to extrapolate dynamic stress maps.
2.5.2. Static stress changes
Static stresses changes are permanent variations in the local stress field produced by slip on a fault (source fault, SF). Stress changes decay with the epicentral distance (R) as 1/R3 and therefore become
negligible just a few fault lengths from the epicenter. Stress changes induced by an earthquake on a receiver fault or fracture are given by the Coulomb Failure Function (CCF) (e.g. Stein et al., 1992; King et al., 1994; Stein, 1999; King and Devés, 2015):
27 Where is the shear stress change on the receiver fault (direction of fault slip considered as positive),
n is the normal stress change (positive if the fault is unclamped), is the friction coefficient, and ΔP
is the fault pore pressure change. Equation 3 is often simplified as: ∆𝐶𝐹𝐹 = ∆𝜏 + 𝜇′∆𝜎𝑛 (4)
where ’ is the apparent coefficient of friction, which includes the effect of material properties and fluid pressure changes. In case of mud volcanoes, static stress changes (i.e., normal stress changes and volumetric changes) are thought to influence mud volcano activity when large enough and favourably oriented with respect to the mud volcano feeder dykes (Bonini et al., 2016). The normal stress change component (n) was calculated in order to evaluate whether the stress variations act to close (clamp)
or open (unclamp) the subsurface receiver feeder dyke system beneath the mud volcanoes, in this latter case, facilitating the emission of fluid from the subsurface.
Calculation of static stresses requires input parameters that in our case are represented by the surface and subsurface geological data. These constraints are the structural data in the form of fluid emission fracture orientations and mud volcano alignments and elongations (as explained in Section 3.1.2). These data have been used as a proxy for the geometry of the subsurface feeder dyke system for the mud volcanoes, which is essential for calculating static stress changes (e.g., Bonini et al., 2016) (Fig 2.9). Furthermore, we collected information from local inhabitants about the historical activity of mud volcanoes, their location, as well as past and no-longer visible features. Information about the subsurface geology have been obtained from literature data and from the interpretation of seismic reflection profiles provided by ENI S.p.A. Well data available from the VIDEPI project were used to correlate the seismic data to stratigraphy. The feeder dyke system is modelled as a vertical fracture representing an array of planar structures exploited by the ascending mud-fluid mixture. Normal stress changes have been calculated in a homogeneous half-space (Okada, 1992) using the Coulomb software, version 3.3 (free download at https://earthquake.usgs.gov/research/software/coulomb/) (Toda et al., 2005, 2011). Elastic moduli and apparent friction coefficient are assumed to be homogeneous. I have used the following standard and average values that have been widely used for static stress calculation (e.g., King et al., 1994, Lin and Stein, 2004; Toda et al., 2005, 2011; Bonali et al., 2013; Bonini et al., 2016):
Poisson’s Ration ()=0.25
Young’s modulus (E)=8x10 5 bar Shear modulus (G)=3.2x105 bar
