Tectonic and Structural Framework of the Zagros Fold-Thrust Belt

By Elsevier Science

The latest volume in the Developments in Structural Geology and Tectonics series from Elsevier, Tectonic and Structural Framework of the Zagros Fold–Thrust Belt is a collection of the most up-to date research and developments in the unique tectonic and structural geology of the Zagros. The Zagros fold–thrust belt is famous among geologists and is one of the most-studied terrains in the world. Because of its unique structures, the Zagros orogeny is challenging for many researchers and experts; this book is the essential reference that collates the newest data and fully explores that aspect. In addition, because the Zagros range is a potential source for hydrocarbons, it is of interest to petroleum geologists and exploration companies worldwide. This book is an essential, cutting-edge reference for oil companies, structural geologists, and students at both the undergraduate and postgraduate levels.

• Includes valuable new data about one of the most famous collisional mountain ranges in the world, the Zagros fold–thrust belts, as a guide for other collisional ranges such as the Himalaya, the Alps, and the Andes, as they share common fundamental deformation mechanisms
• Provides research from geologists across the world, with the goal of understanding the unique dynamics and kinematics of the Zagros range

• Language: English
• Publisher: Elsevier Science
• Release date: Dec 7, 2018
• ISBN: 9780128150498

Book preview

Tectonic and Structural Framework of the Zagros Fold-Thrust Belt

Developments in Structural Geology and Tectonics

Editor

Ali Farzipour Saein

University of Isfahan, Isfahan

Table of Contents

Cover image

Title page

About the Series

Copyright

Dedication

Contributors

Preface

Acknowledgments

Chapter 1. Fracture Analysis of Hydrocarbon Reservoirs by Static and Dynamic Well Data, Case Study: The Aghajari Oil Field (the Zagros Fold-Thrust Belt)

Introduction

Geologic Framework

Methodology

Results and Discussion

Conclusions

Chapter 2. Tectono-Sedimentary Evolution of the Iranian Zagros in a Global Context and Its Impact on Petroleum Habitats

Introduction

Evolution of the Iranian Zagros

Conclusions

Chapter 3. Zagros Foreland Fold Belt Timing Across Lurestan to Constrain Arabia–Iran Collision

Introduction

Structure and Stratigraphy of the Lurestan Province: Foreland Successions

Afrineh and Chaman Goli Growth Synclines

Magnetostratigraphy

Correlation of Local Magnetic Polarity Stratigraphy With Global Polarity Time Scales

Discussion

Conclusions

Chapter 4. Structural Geology and Neotectonics of Iraq, Northwest Zagros

Introduction

Shalair Terrane

Outer Arabian Platform

Mosul Fault

Inner Arabian Platform

Conclusion

Chapter 5. High-Pressure/Low-Temperature Blueschists in the Zagros Mountains

Introduction

Hajiabad Blueschists

Neo-Tethyian Ophiolites

Inclusions in Diapirs of Hormoz Salt

Chapter 6. Structural Evolution of the Northeast–Southwest Trending Tectonic Lineament and a Model for Graben Formation in the Denizli Region of Western Anatolian (West of the Zagros Fold-and-Thrust Belt)

Introduction

Stratigraphic Features of Denizli Region

Tectonic Framework of the Region

Northeast–Southwest Trending Fractures

Babadağ–Honaz Faults and Their Formation Phases

Discussion and Conclusions

Chapter 7. Right-Lateral Strike-Slip Faulting and Related Basin Formations in the Turkish–Iranian Plateau

Introduction

Tectonic Setting and Seismicity

Method

Right-Lateral Faults in the Turkish–Iranian Plateau

Strike-Slip Basins Related to Right-Lateral Faulting

Discussion and Conclusions

Appendix

Chapter 8. Tectonic Geomorphology of the Zagros Orogen

Introduction

Geologic and Geographic Settings

Methods

Results

Discussion

Conclusions

Chapter 9. Structural Style in the Fars Geological Province: Interaction of Diapirism and Multidetachment Folding

Introduction

Detachment Units

Discussions

Conclusions

Chapter 10. Internal Deformation of Turkish–Iranian Plateau in the Hinterland of Bitlis–Zagros Suture Zone

Introduction

The Rhomboidal Cell Model

Methodology

Ahar Rhomboidal Cell

Urmiye Rhomboidal Cell

Nahçivan Rhomboidal Cell

Van Rhomboidal Cell

Memişhan Rhomboidal Cell

Tendürek Rhomboidal Cell

Ağrı Rhomboidal Cell

Erivan Rhomboidal Cell

Kars Rhomboidal Cell

Horasan Rhomboidal Cell

Hınıs Rhomboidal Cell

Muş Rhomboidal Cell

Karlıova Rhomboidal Cell

Kiğı Rhomboidal Cell

Beşgöze Rhomboidal Cell

Düzyurt Rhomboidal Cell

Çayırlı Rhomboidal Cell

Global Positioning Satellite Studies

Discussions

Conclusions

Supplementary Data

Chapter 11. De-risking Plays in the Highly Folded Zone Foreland Basin of the Zagros Fold–Thrust Belt, Kurdistan Region, Iraq

Introduction

Regional Structural Patterns

Prospective Nature of Thrust Belts

Prospective Nature of High Fold–Thrust Zone

Thrust Imbricate Models

Conclusions

Author Index

Subject Index

About the Series

Developments in Structural Geology and Tectonics is an Elsevier book series where potential authors are welcome to contact the Series Editor: Soumyajit Mukherjee ([e-mail], [e-mail]) with new book proposals either as authors or editors. All theoretical, practical, regional and interdisciplinary topics of structural geology and tectonics are welcome as potential book proposals.

Copyright

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Notices

Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary.

Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility.

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ISBN: 978-0-12-815048-1

ISSN: 2542-9000

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Dedication

To my kind father, FARHANG, who is fighting against Alzheimer.

Contributors

I. AbdollahieFard     National Iranian Oil Company, Exploration Directorate, Tehran, Iran

W. Abdulnaby     Department of Geology, College of Science, University of Basrah, Basrah, Iraq

B. Aktuğ     Ankara University, Department of Geophysical Eng., Ankara, Turkey

E. Beamud     Laboratori de Paleomagnetisme CCiTUB-CSIC, Institute of Earth Sciences Jaume Almera, CSIC, Solé i Sabarís s/n, Barcelona, Spain

H. Emami     Equinor ASA, Fornebu, Norway

K. Esat     Ankara University, Department of Geol. Eng., Tectonics Research Group, Ankara, Turkey

A. Farzipour Saein     Department of Geology, University of Isfahan, Isfahan, Iran

M. Garcés     Group of Geodynamics and Basin Analysis, University of Barcelona, Facultat de Geologia, Campus de Pedralbes, Barcelona, Spain

GH. Gharabeigli     National Iranian Oil Company, Exploration Directorate, Tehran, Iran

A. Gürbüz     Niğde Ömer Halisdemir Üniversitesi, Mühendislik Fakültesi, Jeoloji Mühendisliği Bölümü, Niğde, Turkey

M. Hançer     Pamukkale University, Geological Engineering Department, Kinikli–Denizli, Turkey

B.U. Haq     Sorbonne, Pierre and Marie Curie University, Paris, France

F. Kiani Harchegani     Dipartimento di Fisica e Scienze della Terra, Universita` di Ferrara, Ferrara, Italy

S. Homke     Equinor ASA, Fornebu, Norway

B. Kaypak     Ankara University, Department of Geophysical Eng., Ankara, Turkey

K. Kolo     Department of Petroleum Geosciences, Faculty of Science, Soran University, The Kurdistan Region of Iraq

H. Koyi     Hans Ramberg Tectonic Laboratory, Department of Earth Sciences, Uppsala University, Villavä, Sweden

H. Mansurbeg

Department of Petroleum Geosciences, Faculty of Science, Soran University, The Kurdistan Region of Iraq

Department of Earth and Environmental Sciences, University of Windsor, Windsor, ON, Canada

K. McClay     Fault Dynamics Research Group, Department of Earth Sciences, Royal Holloway University of London, United Kingdom

H. Motamedi     National Iranian Oil Company, Exploration Directorate, Tehran, Iran

R. Othman     Department of Petroleum Geosciences, Faculty of Science, Soran University, The Kurdistan Region of Iraq

F. Şaroğlu     Jeolojik Mirası Koruma Derneği (JEMİRKO), Ankara, Turkey

G. Seyitoğlu     Ankara University, Department of Geol. Eng., Tectonics Research Group, Ankara, Turkey

SH. Sherkati     National Iranian Oil Company, Exploration Directorate, Tehran, Iran

P. Skott     Equinor ASA, Fornebu, Norway

P. Spirov     Faculty of Petroleum and Mining Engineering, VŠB–Technical University of Ostrava, Erbil Campus, Kurdistan Region of Iraq, Iraq

C.J. Talbot     Hans Ramberg Tectonic Laboratory, Department of Earth Sciences, Uppsala University, Uppsala, Sweden

M. Toori     Arazi, 4th Section, Zanjan, Iran

M. Vatandoust     Department of Geology, University of Isfahan, Isfahan, Iran

J. Vergés     Group of Dynamics of the Lithosphere (GDL), Institute of Earth Sciences Jaume Almera, ICTJA-CSIC, Solé i Sabarís s/n, Barcelona, Spain

Preface

This edited book on the tectonics of the Zagros mountain range, edited by Prof. A. Farzipour Saein, contains 11 key chapters authored and coauthored by experts from 10 countries. Tectonics and structural geology have been developing in terms of several specialized branches. Notwithstanding, fold and thrust belts such as the Zagros Orogen continue to receive attention from academic and industrial geoscientists worldwide. Thematic volumes on this subject have been available from time to time (e.g., Leturmy and Robin, 2010; Lacombe et al., 2011) and such efforts to compile developments on the subject need to continue. This book fits this purpose. A similar effort is also noticeable for other orogens such as the Himalaya (e.g., Mukherjee et al., 2013, 2015; Sharma et al., 2018; Trealoar and Searle, 2018). I congratulate the editor, Prof. A. Farzipour Saein, the authors, and the reviewers for their dedicated efforts to bring out this significant volume.

Soumyajit Mukherjee

Series Editor

References

Lacombe O, Grasemann B, Simpson G. Introduction: geodynamic evolution of the Zagros. Geological Magazine. 2011;148:689–691.

Leturmy P, Robin C. Tectonic and Stratigraphic Evolution of Zagros and Makran during the Mesozoic – Cenozoic: Introduction. vol. 330. Geological Society, London, Special Publications; 2010:1–4 Tectonic and Stratigraphic Evolution of Zagros and Makran during the Mesozoic–Cenozoic.

Mukherjee S, Mukherjee B, Thiede R. Geosciences of the Himalaya-Karakoram-Tibet orogen. International Journal of Earth Sciences. 2013;102:1757–1758.

Mukherjee S, Carosi R, van der Beek P.A, Mukherjee B.K, Robinson D.M. In: Mukherjee S, Carosi R, van der Beek P, Mukherjee B.K, Robinson D, eds. Tectonics of the Himalaya: An Introduction. vol. 412. Geological Society, London, Special Publications; 2015:1–3 ISBN:978-1-86239-703-3.

Sharma, Villa I.M, Kumar S. Crustal Architecture and Evolution of the Himalaya-karakoram-tibet Orogen. Geological Society of London Special Publications; 2018 (Ongoing).

Trealoar P.J, Searle M. Himalayan Tectonics: A Modern Synthesis. Geological Society of London Special Publications; 2018 (Ongoing).

Acknowledgments

Praise be to god. First, I would like to thank the contributors to this volume for entrusting me with their manuscripts and for their generally timely responses to my requests. I would like to express my appreciation to Series Editor (Soumyajit Mukherjee) and anonymous reviewers, T. Frank (Senior Editorial Project Manager) and M. Rajendran (Senior Project Manager) for their support and assistance in various stages of this book editing. My wife and son (Shahrzad and Mohamad Abbbas) are thanked for their patience and encouragement and also I do not forget my mother's prayers. University of Isfahan is thanked for giving me opportunity to develop my academic career. Finally, the following colleagues served as efficient reviewers of chapters.

S. Mukherjee

M. Hançer

M. Tadayon

G. Seytoughlou

K. Esat

J. Verges

A. Gurbuz

SH. Sherkati

T. Ostaomer

GH. Torabi Four anonymous reviewers

Ali Farzipour Saein

The Editor

Chapter 1

Fracture Analysis of Hydrocarbon Reservoirs by Static and Dynamic Well Data, Case Study

The Aghajari Oil Field (the Zagros Fold-Thrust Belt)

Masumeh Vatandoust and Ali Farzipour Saeina     Department of Geology, University of Isfahan, Isfahan, Iran

a Corresponding author: [e-mail], [e-mail]

Abstract

According to several decades of hydrocarbon production history along the Zagros Fold–Thrust Belt, the Late Oligocene–Early Miocene Asmari Formation (a fractured reservoir) is the main reservoir rock (carbonate rocks) in southwest Iran. In fractured reservoirs, available data directly related to fractures are scattered and mostly one-dimensional (e.g., core and image log data). Other types of data are more widespread (e.g., production dynamic data) and in general are indirectly related to the fracture distribution pattern. In such reservoirs, it is crucial to model the fracture network on a field scale by integrating all available static and dynamic data.

In this study using static and dynamic data, a discrete fracture network model, which reflects various statistical properties of fractures, has been constructed for the Asmari reservoir in the Aghajari oil field. According to the resulting fracture density and permeability maps of the Aghajari Anticline, the northwest and southeast parts of the southwest limb and the central part of the northeast limb have more fracture density and permeability.

Keywords

Aghajari oil field; Asmari formation; Dynamic well data; Fracture analysis; Static well data

Introduction

The Zagros fold–thrust belt (ZFTB) extends ∼1800  km along the Iraq and Iran border (Joudaki et al., 2016) (Fig. 1.1). It contains more than half of the world's hydrocarbon reserves (Sepehr and Cosgrove, 2005). Continent–continent collision between the African–Arabian plate and Iranian block formed this belt (Takin, 1972; Koyi, 1988; Stöcklin, 1974; Berberian and King, 1981) and significant crustal shortening. The shortening rate across the Zagros is estimated to be 13  mm/yr since the onset of collision (Pirouz et al., 2017) in the ZFTB, caused by sedimentary cover and basement folding and faulting (Alavi, 2007; McQuarrie, 2004; Mouthereau et al., 2007; Nilforoushan et al., 2003; Sepehr and Cosgrove, 2005).

The Asmari Formation is an Oligocene–Early Miocene carbonate platform that is the most prolific oil reservoir in Iran; commonly, it is regarded as a classic fractured carbonate reservoir with production properties that strongly depend on the existence of fracture networks (Stephenson et al., 2007).

Although it is possible to investigate the fracture distribution from outcrops, there are several difficulties in detecting fracture density in subsurface reservoir rocks. The importance of the presence of natural fractures has promoted the development of robust fracture network models (Herbert, 1996). Direct observation of detailed three-dimensional (3D) fracture networks deep in the crust is impossible. Field data are usually collected from 1D borehole logging (e.g., image logs with a ∼0.1  m-long investigation or resolution) and 2D outcrop mapping (length scale of investigation of ∼0.1–500  km) (Einstein and Baecher, 1983). Seismological surveys may be able to locate 3D large-scale structures, but current technology can hardly detect widely spreading medium-sizes and small fractures owing to the resolution limit. A description of natural fracture geometries (Mukherjee, In press) therefore relies on data extrapolations from 1D/2D to 3D and from small samples to the whole study area.

The stochastic discrete fracture network (DFN) method can extrapolate fracture sets from wells and outcrop to areas with no data (Hennings et al., 2000; Anraku et al., 2000). The general stochastic DFN approach assumes fractures to be straight lines (in 2D) or planar discs (in 3D) and treats other geometrical properties as well (e.g., position, frequency, size, orientation, aperture).

Using relevant software, this study presents a discrete fracture model of the Asmari Reservoir of the Aghajari Anticline, one of the main oil fields in ZFTB. To achieve this goal, static (data obtained from drilled cores and image logs) and dynamic data (mud loss [ML], production logging test [PLT], and productivity index [PI]) were integrated.

Figure 1.1  Structural setting of the Dezful Embayment in the Zagros fold-and-thrust belt in southwest Iran. The Aghajari oil field is plotted. BTF , Balarud transfer fault; HTF , Hendijan transfer fault; KTF , Kazerun transfer fault; MFF , mountain front fault; ZFF , Zagros front fault. 

Modified after Verges, J., Emami, H., Homke, S., Garses, M., 2009. Neogene Sequence of folding in the NW zagros fold belt dating non-marine foreland growth strata. In: 1st EAGE International Petroleum Conference and Exhibition, Shiraz, Iran.

Geologic Framework

The Zagros Basin was part of the stable supercontinent of Gondwana in the Paleozoic and a passive margin in Mesozoic, and became a convergent orogeny in the Cenozoic ( Agard et al., 2011; Berberian, 1995; Berberian and King, 1981; McQuarrie and van Hins-bergen 2013; Mouthereau et al., 2012; Stocklin, 1968 ). Northwest (NW)–southeast (SE) trending ZFTB is divided into three subparallel structural and stratigraphic regions. Toward the east (Fig. 1.1) are the foredeep, the Simply Folded Zone, and the Imbricate Zone (Berberian, 1995; Falcon, 1974; Sepehr and Cosgrove, 2004; Stocklin, 1968; Joudaki et al., 2016). In addition to orogen-parallel zonation, based on structural features, the Simply Folded Zone is also divided along strike toward east into the Fars, the Izeh, the Dezful Embayment, and the Lurestan salient (Sepehr and Cosgrove, 2004; Sherkati and Letouzey, 2004).

One of the most important hydrocarbon provinces in the ZFTB is the Dezful Embayment, a structural depression developed in front of the Izeh folded zone. Its subsidence is related to development in the foredeep of ZFTB. In the western part of this zone, the Balarud flexure exists and the north–south trending Kazerun Fault is located in its eastern part (∼90  km) ( Sepehr and Cosgrove, 2005; Abdollahi et al., 2006). The Aghajari oil field (a thrust-related anticline) (see Mukherjee, 2014 for review on such folds) is one of the giant oil-producing hydrocarbon fields located within the Dezful Embayment (Fig. 1.1). The anticline is slightly asymmetric with the NW–SE axis. The southwest flank is usually steeper, dipping up to 70  degrees. On the other hand, the average dip of the northeast flank is ∼30  degrees.

The Asmari Formation is one of the main reservoir rocks in SW Iran and also a typical and prolific fractured reservoir (Nelson, 2001). This formation is divided into five zones. Six subzones exist (from a depth of  ∼  2300 to ∼3000  m) within the Aghajari Field, based on lithological variations, porosity, and water saturation (Vatandoust and Farzipour, 2017) (Fig. 1.2).

The outcome of static modeling of the spatial distribution of fractures at the field scale was used as input for dynamic reservoir modeling, which was the purpose of this study. However, the scarcity of wells in which fracturing data were available made such direct mapping difficult and uncertain.

Figure 1.2  Lithostratigraphic column for the Zagros fold–thrust belt. The Asmari Formation at the Aghajari Anticline can be divided into five zones and six subzones as indicated. 

Modified after AbdollahieFard, I., Braathen, A., Mokhtari M., Alavi, S.A., 2006. Interaction of the Zagros fold thrust belt and the arabian-type, deep-seated folds in the abadan plain and the dezful embayment. SW Iran, Pet. Geosci. 12, 347–362.

Methodology

Characterization

It is necessary to characterize fractures (orientation, fracture density, etc.) to investigate the effects of different parameters on fracture density. In this study, the orientation data of open fractures, including the dip and dip azimuth of fractures, are obtained from core (well A) and image logs (wells B, C, D, E, and F) (Fig. 1.3A and B). Aperture data are obtained from the image log from well F. Because well data are on a small scale and of high accuracy, the parameters used as drivers are on a large scale and of low accuracy. Thus, combining these data can lead to the construction of a suitable model for fracture density distribution. To extrapolate statistics for 3D fracture systems (density distributions) from 1D sampling data, based on stereoanalyses (Warburton, 1980; Berkowitz and Adler, 1998), some parameters (e.g., curvature, porosity, ML, and distance from fault maps) of the Asmari Reservoir were used as drivers. To investigate the effects of different parameters on the fracture density, the weight of each parameter should be calculated. To do so, a statistical method called discriminant analysis was used. In general, if C1 to Cn are the parameters and W1 to Wn are their weights, the values of driver are calculated using discriminant analysis via Eq. (1.1) (Pérez y Pérez, 2014):

(1.1)

Figure 1.3  (A) Electromagnetic interference analysis (conductive fractures, resistive fractures, and layer boundaries), and (B) shear fractures in core from well A, Aghajari field. T stands for top and B for bottom (of the core sample). Red arrows indicate shear sense (shear direction).

To determine how fracture density varies spatially, and to generate a fracture density map, it is necessary to generate a variogram, which is used to predict the locations of the fractures. A simulation of a fracture density map regarding the variograms is the next step in the study. The result of calculations performed at this stage is a fracture density map of different fracture sets. These maps show a lateral distribution of fractures at different points for the area 56  ×  6  km in the reservoir. To determine the structure and distribution of fractures spatially, an experimental variogram of different fracture sets, a variogram calculated from the data, and a variogram model best fitted to the data are calculated. The variogram model is chosen from a set of mathematical functions that describe spatial relationships (Gorsich and Genton, 2000). The appropriate model is chosen by matching the shape of the curve of the experimental variogram to the shape of the curve of the mathematical function. Finally, calculation of the effect of fractures on the permeability model is the most important purpose of geostatistically simulating fracture density.

Modeling and Calibration

In a DFN model, a virtual rock volume is stochastically populated with planar, straight, nonparallel, and discrete objects representing natural fractures. The virtual fractures are assigned properties from statistical distributions defined by subsurface data, field production data within the carbonate Asmari Reservoir with a depth of ∼2300 to ∼3000  m, and mechanical and hydraulic behavior theories. It is necessary to attribute to each fracture set geometric and hydraulic properties such as the length and hydraulic conductivity and to calibrate these parameters using reservoir production data, especially well test data as performed by Singha et al. (2012), respectively. In the case of the hydraulic conductivity of each fracture set, the fracture data (fracture aperture) derived from the Formation MicroImager (FMI) log from well F are used. By using these data and Poiseuille's law, (Eq. 1.2) (Singha et al., 2012), the conductivity of fractures is calculated:

(1.2)

where C  =  conductivity in millidarcy; and a  =  aperture in millimeters.

(Singha et al., 2012) Generally, to calculate a fracture network and permeability (k) accurately and reliably, it is necessary to consider a grid around a well containing its fracture aperture data. To determine the grid size, it is necessary to analyze the permeability values for a grid of different dimensions. The minimal dimension of a grid for which the permeability remains constant is the grid size. The parameters of length and conductivity for different fracture sets should be calibrated with different scenarios with production data using automated production data calibration, which is performed in the related software. For that, for each scenario, the fracture length and conductivity are changed (fracture length of 5–90  m and conductivity of 3–14  millidarcy) until the model permeability correlates with that from production data, ∼13  millidarcy. A comparison of the results of actual and synthetic tests can be used to determine the precision and validation of the model (Singha and Al-Shammeli, 2012).

Upscaling

Upscaling is a process in which calculated properties for a fracture network (initially calculated for the zone of interest, 500  ×  200  m around a well with production data) are distributed in the whole reservoir. In this way, at the end of the upscaling process, fracture permeability is calculated for all grid cells (Tamagawa et al., 2002).

Results and Discussion

Fractures are grouped into three sets with their orientations (set 1: NE–SW; set 2: east–west; and set 3: NW–SE) in this study (Figs. 1.4–1.6). Fracture density logs with the number of fractures per unit length (P10) are computed for wells with fracture data (maximum fracture density: 7  m−¹ for well A, 4  m−¹ for wells B and D, 6.4  m−¹ for well C, 9  m−¹ for well E, and 5 for well F) using the relevant software (Fig. 1.7).

Unfolding of the bedding plane to study fracture set chronology, as was performed earlier by Ahmadhadi et al. (2008), demonstrates that fracture set 1 (striking perpendicular to the bedding strike; with the attitude NE–SW, 62  degrees NW) was not affected by the rotation of the bedding (30  degrees). This could be interpreted thus: Fractures that occurred during any stage of fold growth were named the transverse fracture set (Fig. 1.5). Fracture set 2, after removing the bedding dip, is bed-perpendicular, taken as supporting a prefolding origin (Hancock, 1985). However, bedding perpendicular tensile fractures can develop at the onset of folding (Chu et al., 2013).

Figure 1.4  Stereographic projection, Schmidt net, upper-hemisphere projection diagram, and strike diagram of open fractures. Open fractures of the Asmari Reservoir are grouped in three sets (sets 1–3); mean poles of individual fracture sets are reported on stereogram as dots .

Figure 1.5  Stereographic projection, Schmidt net, and upper-hemisphere projection diagram of open fracture sets in the fold after removing folding.

Figure 1.6  Subsurface contour map of the top-Asmari Formation at the Aghajari field, showing the location of wells with fracture data. Rose diagrams of all fracture sets are represented in different wells. The rose diagrams in the bigger size correspond to higher fracture numbers.

Fracture set 3 is perpendicular to the bedding and parallel to the fold axis and could be interpreted as extensional axial fractures generated in response to the fold outer arc extension (Lacombe et al., 2011). Evidence supporting this fact is the change in the strike of these fractures in well B. In this part of the field, fractures are affected by both the structural curvature and conjugated transverse faults close to well B. Hence, typically, they are fold-related fractures.

To investigate the effects of different parameters on the fracture density and to determine effective drivers, the weight of each parameter is calculated and factors with a higher correlation coefficient (affinity coefficient: curvature, ML, and PI maps) are selected as drivers for generating a fracture density map (Table 1.1). Fractures occur mostly in parts of a fold with high curvature values (Fischer and Wilkerson, 2000) and are also based on a geometrical analysis of the Asmari Reservoir at the NW–SE trending Aghajari field; high-curvature areas are expected to develop open fractures (Vatandoust and Farzipour, 2017).

Figure 1.7  Fracture density logs for wells with fracture data. High fracture density may be seen in zones 1 and 3 of the Asmari Reservoir.

Table 1.1

Loss of drilling fluids occurs when a borehole reaches a fractured reservoir interval. Monitoring fluid loss can be used to identify fractured zones (Dyke et al., 1995; Sanfillippo et al., 1997; Datwani, 2012). Lost circulation occurs when drilling mud flows into natural fractures and caverns; the rate of ML in a tight carbonate may be used to indicate the degree of fracturing. The ML map therefore may indirectly represent the distribution of open fractures in the Asmari Reservoir (Vatandoust and Farzipour, 2017).

Fig. 1.8. shows results of the experimental variogram and the approximated spatial functions. The resulting variograms are used to simulate fracture density (Fig 1.8). The fracture density map for three fracture sets is the result of this stage of the study (Figs. 1.9–1.11). These maps are the result of integrating 1D fracture data with different drivers (curvature, ML, and PI) and extrapolations from small samples to the whole study domain.

Figure 1.8  Experimental variogram ( red dots ) calculated from the data and variogram model fitted to the data ( blue curve ) for all fracture sets (distance, X axis, versus variance, Y axis, diagram).

Figure 1.9  Fracture Iso-density map for fracture set 1 of the Asmari Reservoir in the Aghajari field.

At this stage of the study, to predict hydraulic behavior for the fracture network, geometric and hydraulic properties (length and hydraulic conductivity, respectively) are attributed to each fracture set. The calculated fracture hydraulic conductivity, using fracture aperture, is about 250  millidarcy for fracture set 1, 150  millidarcy for fracture set 2, and 200  millidarcy for fracture set 3.

To calibrate calculated hydraulic conductivity with the production data and permeability estimate, a fracture network is constructed for a small-scale 3D grid, and a zone of interest in well F (the well with a fracture aperture, length and production data [Fig. 1.12]) and permeability are calculated for different lengths and conductivity for grids for well F. To perform an accurate and reliable calculation, it is necessary for the grid to have a minimal dimension.

To determine a minimal grid size, grid dimensions change from 100  ×  100  m to 230  ×  230  m; the effect of this change on fracture permeability are presented as a chart (Fig. 1 13). As may be seen, 175  m is the representative elementary volume for the grid; at this length, permeability calculations are stable and accurate. After this length is reached, parameters of length and conductivity for fractures should be calibrated in different scenarios with production data.

Figure 1.10  Fracture Iso-density map for fracture set 2 of the Asmari Reservoir in the Aghajari field.

For well F, a different scenario involved the length and conductivity of the fractures.

The optimal amount of permeability is about 13  millidarcy according to well test data. Therefore, the square root of the maximum and minimum permeability multiplication obtained from the calculation results should be about 13  millidarcy:

(1.3)

(Fraca user manual, 2005) For a small length, the permeability of the model does not change much even with high variations in the conductivity of the fracture sets. When the length of the fractures is small, there is no connection between fractures; as a result, the conductivity of the fluid will be reduced. For lengths of about 45  m, the permeability is close to 14–15  millidarcy. By plotting the permeability diagram against the length of the fractures (Fig 1. 14), it is observed that after ∼45  m, the permeability value remains almost constant. Therefore, 45  m is the optimum length for the fractures. Therefore, the values of 250  millidarcy for conductivity and 45  m for fracture lengths are considered. A calibrated length and conductivity of fractures are used to calculate the permeability of a fracture network within other parts of the reservoir.

Figure 1.11  Fracture Iso-density map for fracture set 3 of the Asmari Reservoir in the Aghajari field.

According to the fracture density map for different fracture sets and distribution of the strike and dip of fractures, considering the length and conductivity parameters of fractures, the geometric model of the fracture network was constructed and the permeability of all reservoir cells was automatically calculated by the relevant software (Fig. 1.15). Average permeability in X, Y, and Z directions was equal to 165.73, 118.01, and 97.93  millidarcy, respectively. High permeability was observed in zones 1 and 3 of the Asmari Reservoir within the Aghajari field equal to 370  millidarcy (Fig. 1.16).

Figure 1.12  Generated discrete fracture network model of well F. Different fracture sets are represented as different-colored planes: blue plane (set 1), green plane (set 2), and red plane (set 3).

Figure 1.13  Determination of computational grid dimension for well F.

Figure 1.14  Determination of a suitable fracture length for fracture modeling using permeability calibration.

Figure 1.15  Permeability model of the Asmari Reservoir in the Aghajari field. The highest concentration of permeability occurs in the southern and northern parts of the southwest limb of the fold and the central part of the northeast limb.

Figure 1.16  The strike section of the permeability model of the Asmari Reservoir in the Aghajari field. The highest concentration of fracture permeability occurs within zones one and three of the reservoir.

Conclusions

Based on a fracture analysis of the Asmari Reservoir at the NW–SE trending Aghajari Anticline, high–fracture density areas are located in the hinge zone, in the SE and NW parts of the SW limb, and in the central part of the NE limb. According to the fracture density maps, fracture sets 1 and 2 (NE–SW and east–west) are more abundant in the central part of the NE limb and the NW part of the SW limb, and fracture set 3 (NW–SE) has a higher density at the hinge zone owing to the high fold curvature in these areas. The results of fracture network modeling and permeability estimation demonstrated that the highest amounts of permeability occur in the southern and northern parts of the SW limb of the fold and the central part of the NE limb. High permeability is observed in zones and 3 of the Asmari reservoir within the Aghajari field.

The results of this study are in good accordance with the results of work by Vatandoust and Farzipour Saein (2017). They were derived from geometrical methods (inscribed circle and curvature analyses of the fold) to predict the fracture distribution of the Asmari Formation at the Aghajari Anticline. The geometrical analysis demonstrates that regions of high curvature (such as the SE and NW parts of the SW limb of the Aghajari Anticline and the central part of the NE limb) have the greatest potential to develop open fractures. Compared with this work, which presented a DFN fracture model using both static and dynamic data, the work of Vatandoust and Farzipour Saein (2017) presented a predicted method of fracture distribution based on the curvature of anticline.

Acknowledgments

We would like to express our appreciation to the research deputy of the University of Isfahan and the Department of Geology for their support and assistance at various stages of this research. The authors also thank the National Iranian Oil Company for their support. The series editor and reviewers are acknowledged for their constructive comments.

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Chapter 2

Tectono-Sedimentary Evolution of the Iranian Zagros in a Global Context and Its Impact on Petroleum Habitats

Iraj AbdollahieFard¹,a, Shahram Sherkati¹, Ken McClay² and Bilal U. Haq³     ¹National Iranian Oil Company, Exploration Directorate, Tehran, Iran     ²Fault Dynamics Research Group, Department of Earth Sciences, Royal Holloway University of London, United Kingdom     ³Sorbonne, Pierre and Marie Curie University, Paris, France

a Corresponding author 

Abstract

Spatially widespread and extended periods of sedimentation coupled with distinct phases of tectonism resulted in complex stratigraphic relationships on the northeast margin of the Arabian Plate. The Mesozoic and Cenozoic strata were incorporated into the Late Jurassic to present-day tectonic events. This tectono-stratigraphic evolution led to the formation of promising petroleum systems. Most of the explored Zagros areas are structural traps; after more than a century of hydrocarbon exploration, stratigraphic traps have become the focus of exploration. Consolidation of knowledge of regional tectono-stratigraphic evolution of the region is crucial to unlock the remaining potential. The regional architecture of sedimentary basins in central Zagros shows major changes that occurred from the Late Jurassic to the present. Coupled sedimentary and tectonic processes exerted significant controls on the facies and distributions of the strata and associated hydrocarbon systems.

Sedimentary architecture and the timing of structural events on the northeast margin of the Arabian Plate were analyzed in this study using seismic profiles, well data, and gross depositional environmental maps. A tectono-sedimentary evolution of the Zagros shows a correlation with changes in the rates and vectors of displacement for the hosting and surrounding plates. Increases in rates and changes in the displacement vectors of the African and Indian Plates since opening of the Atlantic Ocean produced distinct tectonic events together with reactivation of inherited structures on the northeast margin of the Arabian Plate that induced facies changes and stratal variations. Sedimentary processes controlled the strata architectures, sequences, and facies during tectonically quiescent periods that favored the development of intrashelf basins along the margin.

Keywords

Intrashelf basins; Petroleum habitat; Sea-level changes; Tectonic plate displacements; Tectono-sedimentary evolution; Zagros

Introduction

The Zagros Fold and Thrust Belt is well-known for its substantial hydrocarbon resources and contains at least 49% of the world’s hydrocarbon resources in fold and thrust belts (Cooper, 2007) (Fig. 2.1A and B). After over a century of exploration of the large Zagros anticlines in Iran, stratigraphic traps are the focus of current exploration activity. The Zagros anticlines that have been considered unsuccessful so far (e.g., the first wells were dry in the first half of the 20th century) are now being reassessed as possible facies variations with potential reservoir strata that may form stratigraphic traps. A better understanding of the depositional evolution of the Zagros basins may promote exploration in this mature hydrocarbon province.

The geological