Facies modeling of synchronous successions - A case study from the mid-cretaceous of NW Zagros, Iran

Journal Pre-proof Facies modeling of synchronous successions - a case study from the midCretaceous of NW Zagros, Iran

Jaber Shoghi, H. Bahramizadeh-Sajjadi, A. Nickandish, M. Abbasi PII:

S1464-343X(19)30351-6

DOI:

https://doi.org/10.1016/j.jafrearsci.2019.103696

Reference:

AES 103696

To appear in:

Journal of African Earth Sciences

Received Date:

07 April 2019

Accepted Date:

31 October 2019

Please cite this article as: Jaber Shoghi, H. Bahramizadeh-Sajjadi, A. Nickandish, M. Abbasi, Facies modeling of synchronous successions - a case study from the mid-Cretaceous of NW Zagros, Iran, Journal of African Earth Sciences (2019), https://doi.org/10.1016/j.jafrearsci. 2019.103696

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Facies modeling of synchronous successions - a case study from the mid-Cretaceous of NW Zagros, Iran Jaber Shoghi1 a, H. Bahramizadeh-Sajjadi b, A. Nickandishb and M. Abbasia, a

Geology Department, Magma Energy Co., Tehran, Iran

b

Geology Department, Iranian National Oil Co., Tehran, Iran

Abstract Facies modeling of Albian-Turonian successions at Tang-e-Bijar gas field in the Lurestan Province, NW of the Zagros region, Iran is the main objective of this study. The sedimentary environment and biozones of the Sarvak and Garau formations (Albian-Turonian time) are different in Lurestan Province when compared with the south Zagros and the Persian Gulf ranges. Synchronous successions of the formations with different lithofacies and laterally changing of biofacies are always controversial. The primary objectives of this paper is to determine the concurrency of the Sarvak and Garau successions using the correlation of foraminifera biozones and subsequent modeling of simultaneous lithofacies via employing the Truncated Gaussian Simulation with a trend (TGSim) algorithm. In this regard, the Tang-e-Bijar and nearby field data such as core data and petrophysical logs, paleontological and stratigraphy studies were taken into consideration. The stratigraphic ranges of the two formations were determined as Albian-Turonian age. Based on these biostratigraphic data, the tongue of the Garau Formation was clarified. The sequence stratigraphy zonation has been used for the entire Tang-e-Bijar field wells, based on

1

Corresponding author. Department of Geology in the Magma Energy Group, Sepehr Street, Shahrak-e-Gharb,

Tehran, Iran. Tel:+982188080824 Email Address: [email protected]

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Integrated Prediction Error Filter Analysis (INPEFA) logs and core data. In order to capture the heterogeneity of deep sea lithofacies, MRGC clustering method with supervising lithofacies was implemented in this study and five electrofacies were generated and coded from 1 to 5. They correspond to Rudist-Oncoids, packstone to grainstone (RO), Orbitolinid peloid packstone (OP), Fine Orbitolinid wackestone to packstone (FO), Bioturbated echinoderm mudstone to wackestone (BM), and Oligosteginid Mudstone (OM) lithofacies, respectively. The facies modeling in the reservoir such as Tang-e-Bijar where synchronous successions and laterally transient heterogeneous has occurred has always been challenging. To address this challenge, a new workflow has been implemented in this paper. Keywords: Facies modeling, Cretaceous successions, Sarvak and Garau formations age, Tang-e-Bijar, Lurestan Province, NW Zagros (Iran)

1. Introduction Facies modeling is a very important and challenging task in any reservoir modeling process (Odezulu et al. 2014; Sisinni et al. 2016; Tomassetti et al. 2018). Most of the challenges stem from complex geological settings and a poor understanding of the region (Sisinni et al. 2016). Capturing of facies heterogeneities in a reservoir and their propagation extensively depends on the availability of reliable data such as detailed sedimentary studies, core studies covering all the intervals, and 3D seismic data. Most of the geologists have the idea that facies are representatives of geological units (Serra and Abbott 1982; Embry and Johannessen 1993; Odezulu et al. 2014; Sisinni et al. 2016; Tomassetti et al. 2018). These geological units are known to record many aspects of their individual 2

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depositional environment and reservoir behavior (Davis et al. 1993; Odezulu et al. 2014). Experience has proven that by the appropriate ordering of lithofacies., it would be easier to correlate the vertical distribution of geological events such as sedimentary sequences, diagenesis (Serra and Abbott 1982), and even reservoir properties distribution. The present study deals with facies distribution and modeling in the Tang-e-Bijar field, which is located in Lurestan Province, Zagros thrust-fold of Iran (Fig. 1A and B). The Sarvak and Garau formation are the main gas reservoir unit in the field (Fig. 2). These lithostratigraphic units have markedly diachronic boundaries. The Sarvak Formation is underlain by the Garau Formation and overlain by the Surgah Formation in the type section (James and Wynd 1965; Motiei 1995; Bahramizadeh-Sajjadi 2012) (Fig. 2). This unit appears in the Lurestan Province with two major neritic and pelagic facies. The neritic carbonate facies consists of thick bedded, rudist-and other bivalves-bearing intervals (Razin et al. 2010; Ezampanah et al. 2013; Omidvar et al. 2014). Pelagic facies are composed of thin bedded, fine-grained, clayey limestone with pelagic fossils (Oligosteginids and planktonic foraminifers) representing basinal environments (BahramizadehSajjadi 2012). There is a biozonal change toward the deepest areas of the basin (NNW of Tang-eBijar) where the Garau Formation was deposited with the same age (nearby field. See Fig. 6), but its biofacies and lithofacies are different comparing with the Sarvak Formation (James and Wynd 1965; Motiei 1995; Bahramizadeh-Sajjadi 2012). Determination of stratigraphic ages of the Sarvak and Garau formations is thus necessary for facies modeling. Relative ages of these formations were determined based on core and cutting micropaleontological and biozones studies. Common electrical logs such as Corrected Gamma Ray (CGR), sonic, neutron and density logs were employed for those areas with lacking geological information. Due to the long span in the ages of the Garau Formation (Neocomian-Turonian) in Lurestan's tectonic-sedimentary basin, especially

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in its type section like Kabir-Kuh (James and Wynd 1965; Motiei 1995; Bahramizadeh-Sajjadi 2012), the naming and initiation of the Garau successions interdigitated within the Sarvak Formation is always complex. Therefore, it is attempted to define the proper extension and ages of the two formations by studying their biozones, as a way to identify the extension of the Garau successions within the Sarvak Formation and their lateral changes. In order to construct a reliable facies model with available data such as well logs, few cores data, thin sections studies from core and cutting, and seismic 2D data, all the information including conceptual models, regional geology, palaeogeography of the Garau Formation, and previous stratigraphic studies needed to be taken into consideration. Introduction of a method for facies modeling by using a conceptual model could prove to be useful as it leads to more correlation between preliminary and final geological facies model. The main objective of this study is to use biozones, electrofacies, and lithofacies information together, as a way to construct facies model adapted to a deep carbonate environment, and to select a practical algorithm in transition environment to propagating lithofacies. The facies model was constructed in lateral and vertical directions by the TGSim approach via Petrel software, which has been suggested for modeling of facies with depositional trends (Tomassetti et al. 2018). This method has been proved practical in our study area where a natural transition through a sequence of facies occurs. The importance of 3D facing modeling is more recognized when the field development is prioritized. Incorporation of the new method for distribution of facies in the model along with avoiding randomly propagation is believed to reduce the uncertainties and drilling risks, as well as a cause to new strategies to be taken in the field development.

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2. Geological setting The Tang-e-Bijar field is located in the Lurestan Province, NW of the Zagros Fold and Thrust Belt in Iran (Takin 1972; Motiei 1995; Sherkati and Letouzey 2004; Alavi 2007; Farzipour‐Saein et al. 2008) (Fig. 1 A, B and C). During the Neocomian–Turonian time, due to the spreading of the NeoTethys Ocean (Ricou et al. 1977; Takin 1972; Murris 1980; Berberian and King 1981), deposition of calcareous oozes with planktonic foraminifera, nannofossils, radiolarians, and carbonate platforms became widespread in NE of Arabian plate ( Hallam 1963; Takin 1972; Berberian and King 1981; Bordenave and Hegre 2010; Bahramizadeh-Sajjadi 2012). These thick and extent successions formed major petroleum systems in many regions. Examples for these carbonate systems in the Zagros Basin and Arabian Plate are the Garau, Sarvak, and Ilam formations in Iran (Aqrawi et al. 2010; Emami et al. 2010; Hajikazemi et al. 2010; Razin et al. 2010; Sharp et al. 2010; Hollis 2011; Vergés et al. 2011 Hajikazemi et al. 2012; Rahimpour-Bonab et al. 2012; Rahimpour‐Bonab et al. 2013), the Mauddud and Mishrif formations in the UAE, and the Natih Formation in Oman (Alsharhan and Nairn 1986; Alsharan et al. 1998). The Tang-e-Bijar field’s reservoir intervals are mostly composed of carbonates and muddy carbonates. Therefore, the study of foraminifera assemblages in order to determine the relative ages of both formations is vital to show concurrency between them, through interdigitations and lateral changes of facies. The Sarvak and Garau formations include the most significant hydrocarbon source rocks and reservoir in the Lurestan Province. They are composed of more than 1,000 m of limestone, shaly (argillaceous) limestone, glauconitic limestone and bedded cherts with high organic matter and dark grey limestone contents, based on surface sections (Ezampanah et al. 2013; Navidtalab et al. 2014) and wells data. Due to the absence of index palynomorphs and shallow-marine fauna, the

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depositional environment of the Garau Formation is interpreted to be deposited in a deep basinal setting with about 1,000 m deep in some areas of the Lurestan Province (Navidtalab et al. 2014).

3. Materials and methods This study is based on core and cutting data, from which 80 thin sections were papered and studied in the challenging zones, together with data from previous unpublished studies, and petrophysical evaluation. The methodology used in this work made up field data collection and 3D modeling of lithofacies via Petrel E&P software 2016.

3.1. Field description The first drilling attempt was unsuccessful in March of 1965, thereby the field was discovered in June of 1965 with a second well which successfully reached to the reservoir of the Sarvak Formation. Twelve wells have been drilled in the Tang-e-Bijar field so far; among them the studied data were available for only nine of them. As shown in Fig. 1 C these wells have been denoted as W-01 to W-09 from SE to NW, respectively. The main reservoir is the Sarvak Formation, while the traces of hydrocarbon also can be found in the Garau successions. However, the Garau’s hydrocarbon in place is not comparable with that of Sarvak reservoir. The Sarvak Formation in the study area records a different environment than that of its type locality in the Dezful Embayment (James and Wynd 1965; Motiei 1995). It is mainly composed of pelagic limestone with thin interbedded interval of neritic facies. Toward deeper basinal parts (N and NW of Tang-e-Bijar) a remarkable change in facies features are observed, with interdigitations and tongues of the Garau Formation. This fact is corroborated by field data as well as the paleogeography map of the area provided by Bordenave and Hegre (2010) (see Fig. 3. and Fig. 6). 6

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3.2. Determination of stratigraphic ages 3.2.1. Garau Formation The type section of the Garau Formation is located in the south of the Lurestan Province (Kabir Kuh) (Fig. 2 andFig. 3), where it reaches a thickness of approximately 814 m (James and Wynd 1965). The lithostratigraphic equivalent of this unit is also known as Balambo Formation in Iraq (van Bellen et al. 1959). It is overlain by the Sarvak Formation in its type section. However, it transitionally grades to the Sarvak Formation in the Lurestan Province (James and Wynd 1965; Bahramizadeh-Sajjadi 2012). Generally, the age of the lower part of the Garau Formation is Neocomian, which known as the Radiolaria Flood Zone (RFZ) see Fig. 2. But that of the upper part is very variable, ranging from the Berriasian to the Cenomanian (James and Wynd 1965). Although, in a study made by Bahramizadeh-Sajjadi (2012) in the Lurestan Province, the age of the Garau Formation is eventually reported until the late Cenomanian. Almost no forms of benthic foraminifera have been seen in the Garau Formation, and most of the planktonic forams are related to the deep environment, which is mostly composed by fine grained facies and contains shales and marls with disseminated pyrite, representing a low energy and deep basin without free oxygen in the substrates (Navidtalab et al. 2014). According to evidence from the lower part of this unit, it can be admitted that the deep deposits of the Garau Formation overlain on the evaporated sediments of the Gutnia formation of Late Jurassic age (James and Wynd 1965) (Fig. 2). The upper part of the Garau Formation has very different facies arrangement, as an example, at the type section, through an inconsistency below the Bangestan Group (Sarvak, Surgah and Ilam formations) (James and Wynd 1965).

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3.2.2. Sarvak Formation This formation is mostly consisting of limestone and argillaceous limestone successions (James & Wynd, 1965). In the type section (Bangestan Mountain), the thickness of this unit is about 835 m and consists of fine greyish limestone with nodular and dark grey thin layers of marls. Carbonates of the Sarvak Formation (Albian to Turonian) form a major reservoir unit (James & Wynd, 1965) even though permeability varies significantly due to variations in depositional facies and diagenesis. The depositional environments of the Sarvak Formation and its equivalent in the Zagros Basin range from shallow open marine, restricted shelf, reef, slope, open marine and basinal (Alsharhan and Nairn 1986; Aqrawi et al. 2010; Razin et al. 2010; Hajikazemi et al. 2012; Rahimpour‐Bonab et al. 2013; Navidtalab et al. 2014; Omidvar et al. 2014). Pure carbonate lithofacies, a thick interbedded layer with rudist and microfaunas such as Orbitolina sp related to the neritic environment, and fine-grained clays and clayey limestones containing concentrations of Oligosteginids and planktonic forams related to the pelagic environments are typical of the Saravk Formation in the study area (Fig. 2). The biozones recognized for the Sarvak Formation and the Garau’s tongue successions interbedded within the Sarvak Formation are described from the wells with paleontological data, in the following. 3.2.3. Determination assemblage interval zones in the wells 3.2.3.1. Oligosteginid and Conical Orbitolina assemblage interval zones in Well-01 Age: late Albian-Turonian This well was drilled in April of 2000 on the SE of the field and no indication of the Garau Formation was reported. Most fossils belong to the Sarvak Formation (from 1,038 to 1,884 SubSea True Vertical Depth (SSTVD)). The top of the Sarvak Formation was recognized by 8

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Oligostegins facies, which can be correlated with biofacies-26 of James and Wynd (1965). The Conical Orbitolina assemblage bio-zone of James & Wynd, (1965) has also appeared. All the drilled interval belongs to the Sarvak Formation with late Albian-Turonian age. Owing to the fact that the thin sections of this well were not available, the data were extracted from paleologs, which studied by Bahramizadeh-Sajjadi, in an unpublished study of 2009. Investigating the overall results, the presence of thin doubtful intervals related to the Garau’s tongue were justified with electrical and nearby wells (Fig. 7 andFig. 9).

3.2.3.2. Oligosteginid and Rotalipora sp. Assemblage interval zones in Well-02 Age: Cenomanian -Turonian Considering the Paleolog of W-02 in the field, which was investigated by Rahaghi, 1976 in an unpublished research, the palaeontology study was carried out based on cutting thin sections. These data revealed that the Sarvak Formation age is considered to range between the Cenomanian and Turonian stage (From 1,501 to 814 m SSTVD). No index-fossils related to the Garau Formation have been reported; However, probable intervals of the Garau’s tongue were not fully studied. Index fossils of the lower part of the Sarvak Formation from 1,540 to 1,440 m SSTVD depth include Luftusia sp, Orbitoides madia, O. orientalis, Neumannites granulata. Oligosteginids, all of which related to a Cenomanian age, are just the same as biozone-20 of James and Wynd (1965) (Fig. 4 C and D). The upper part of the Sarvak Formation from 942 to 842 m SSTVD depth has a Turonian age, based on the occurrence of the foraminifera Pithonella ovalis, Calcispherula innominata, Hedbergella aff, Pitonella ovalis, Rotalipora aff. are corresponding to biozone-27 of James and Wynd (1965), (Fig. 4 A and B ).

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3.2.3.3. Oligosteginids and Clavihedbergella simplex assemblage interval zones in Well-05 Age: early Cenomanian-Turonian This well was drilled into the Sarvak Formation in April of 1969 without penetrating the Garau’ tongue. The top of this unit contains some dark-brown argillaceous limestone and shaley intervals. The amount of shale within the Sarvak Formation is here much higher than in the other wells. The micropalaeontological studies were conducted by Hamrang in an unpublished study in 1969, from the depth of 1,321 to 1,837 m SSTVD. An early Cenomanian age has been determined by index fossils such as Rotalipora appenninca, oligostegina sp. Pithonella ovalis, Gavelinella baltica, and Schackoina cenomana. The presence of Turonian was also revealed by index fossils such as: Clavihedbergella simplex, Gavelinella baltica and Rotalipora cushmani. 3.2.3.4. Globigerinelloides Algeriana assemblage interval zones Age: Albian In addition to the previous studies as mention above, we prepared and studied 80 thin sections of the two wells (W-02 and W-03). These wells penetrated within the Garau and Sarvak successions, and the Garau’s tongue doubtful intervals are recognizable in electrical logs. It should be noted that in W-03, the Garau intervals were identified, and below these intervals, the Sarvak Formation fossils were again revealed. The Garau index fossil Globigerinelloides algeriana was detected at a depth of 1,517 m SSTVD biozone-13 of James & Wynd, (1965) (Fig. 5A). These intervals are composed of highly argillaceous (shaly and marly bedded) limestone. Below them, the Sarvak Formation is expanded. The Biglobigerinella barri with Rotalipora sp. biozones have been recognized at depth of 1,548 m SSTVD in well-03 with Albian age related to the Sarvak Formation (Fig. 5 B and C). In the well-02 Rotalipora sp. with Albian age and Hetrohelix sp. occur in 10

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lithofacies of the Sarvak Formation, indicating the Albian Cenomanian intervals at the depths of 1,293 and 1,134 m SSTVD, respectively (Fig. 5D). This data indicates that the lower and the upper time-unit boundaries of the Sarvak Formation in the study area can be expanded from Albian to Turonian ages. Therefore, below this time-unit boundary, there are successions related to the Garau Formation, but no wells have penetrated this unit so far. The biozone of Rotaliapora-Radiolaria, biozone-20, and Oligostigina-Radiolaria have been related to the lower part of Sarvak which contains pelagic foraminifera. Another important approach of this study is that it has revealed a Garau succession’ tongue within the Sarvak Formation along with detection of the age of these units. In order to the correlation of the Sarvak Formation and Garau succession tuning the boundary of the zones, nearby field data and log data were employed to consider the Sarvak and the Garau intervals (Fig. 6). 3.3. Sequence-Based Reservoir Zonation The analytical tool - spectral trend attribute analysis and its application along with the interpretation of Gamma Ray (GR) wireline log data were employed for interpreting the geological zonation from sequence stratigraphy point of view, through supervision of several cores and cutting lithofacies. For the sea-level fluctuations recorded in sedimentary pattern strata, the GR attribute can be used as a proxy for indicating the effects of sea-level changing (Fischer 1986; Vail 1991; Nio et al. 2005). A Negative Integrated Prediction Error Filter Analysis (INPEFA) trend results from a cumulatively negative set of prediction error values in Gamma Ray log (see Fig. 7). These tend indicted that Gamma Ray values are less, so coarsing upward than predicted. In very general terms, a negative INPEFA trend can be interpreted the record of a sea-level fall with progradation of a sedimentary system associated to a High-stand System Tract (HST), which is 11

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obviously observed in sediment context. The progradation trend could, for example, imply a fall in the sea-level or a supply of coarse sediment, shallowing-upward, or a decreasing distance from the shoreline (Nio et al. 2005). Conversely, an overall positive trend in the INPEFA represents a sequence of data through which the actual values of the log are higher than those predicted as a retrogradation trend. The INPEFA trend indicates that the actual values are more shaley than predicted, implying a transgressive and deepening trend. This might represent a decrease sediment supply, increase in water depth or accommodation space, or increasing distance from the shoreline, depending on sedimentary context usually associated to a Transgressive System Tract (TST) in particular intervals. At the turning point, an overall negative trend gives way to an overall positive (fining-upward) trend. Definitely, a significant change has affected the depositional system (Nio et al. 2005). The stratigraphic subdivisions are based on the INPEFA, conventional petrophysical logs, paleologs, and lithofacies (Fig. 7). As a result, two main geological and reservoir zones have been distinguished in the Sarvak and Sarvak-Garau (S&G) successions zones. Therefore, sequence boundary (SB) and maximum flood surface (MFS) were indicated by the record of intraclast packstone to grainstone and mudstone facies, respectively. The electrical logs such as density, neutron, and resistive logs have been used for tuning the system tracts boundaries. Experience has proven that using this method provides a good match with the sedimentary process and the reservoir’s attributes when cores did not cover the reservoir zones entirely. Considering the T-R sequence stratigraphy (Embry and Johannessen 1993) to define depositional sequences of the Sarvak and Garau successions. the four wells were found to excellently accord with each other. Among these wells, the W-01 indicated a good correlation with the Sarvak Formation despite the different trends observed for the S&G lithofacies for the same well (Fig. 7).

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Observed system tracts in W-01 indicated that based on 3rd-order depositional sequence a HST has taken place in the entire S&G zones. As described earlier, contents of biozones in the intervals of W-01 show benthic forams and shallow water facies (slope to margin setting lithofacies ) see Fig. 8 andFig. 9. The existence of benthic forams and limestone and less clay content lithofacies in W01 implied that this area was in a relatively elevated palaeogeographic location during the deposition of these sequences. Farzipour‐Saein et al. (2008), Hallam (1963) and Haq (2014) indicated that the paleohighs related to inherited faults systems (tectonic sea-level fluctuation and/or eurybatic shifts). This event has been noted in facies and sequences of the W-01 (Fig. 7 and Fig. 9).

The depositional sequences I and II correspond to the Sarvak and Garau successions with Albian to late Albian age. These sequences (~300 m in thickness) are composed of two SB and two MFS. The third-order sequences such as Sequence I and Sequence II are developed in response to the latest Albian transgression (Haq et al. 1987) and are mostly consist of argillaceous limestone and shaly. These intervals correspond to the MFSs K 100 and 110 of Sharland et al. (2001). The Sarvak depositional sequences were bounded at the top and bottom by SB and MFS, which contain three sequences (Sequence III, Sequence IV and Sequence V). The sequence III resembles that of Early Cenomanian age (K120), it is also characterized by the formation of basin to slope relief during transgression system tract (Haq et al. 1987; Razin et al. 2010; Sharp et al. 2010). The sequence IV corresponds to middle Cenomanian age (K130), it is also characterized by the formation of intrashelf to Shelf basin relief during transgression system tract (Haq et al. 1987). The Turonian sequence (V) is preserved in the field’s wells and only 50 m of this sequence remained. These intervals correspond to the MFS140 of Sharland et al. (2001).

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The Sarvak reservoir units represent a series of regressive and transgressive periods, which are marked by oilgostegina sp. features and Orbitolina-Oncoid facies. This sequence reaches ~350 m thickness. Reservoir quality in HST is better than TST, due to the low clay content of lithofacies which indicted a high energy environment setting. 4. Construction of a conceptual model The emergence of the Garau tongue in the wells indicates that the deep water facies of the Garau sea had retrograded upon on the shelf carbonate platform facies of the Sarvak Formation. The evidence for this sedimentary episode is the emergence of limestone lithofacies with biostratigraphic indicators of the neritic biozones in the lower part of the S&G-3 and 4 zones at the W-02, W-03 and W-04. Based on these results, it can be seen that the Garau succession was interbedded within the Sarvak Formation structurally forming an interfingered architecture (Fig. 6 andFig. 7). As a result, by determining the intervals of the Globigerinelloides Algeriana index fossil and correlating them with the nearby wells, where lithofacies of the Garau Formation appeared, the S&G zones including S&G-1, S&G-2 & S&G-3 and even the upper S&G-4 can be considered as a part of the Garau successions. It could be deduced that sedimentary successions of the two formations were deposited at the same time in this field, and following the transgression of Garau sea in the course of basin deepening due to a global mean sea-level rising or to the tectonic regime, the tongue of the shale and marl lithofacies were deposited on the Sarvak Formation. Therefore, the reappearance of the Sarvak biozones beneath the Garau’ intervals are justifiable. The Garau succession’s tongue becomes thinner towards W-01, and only the S&G-1 zone indicates a good correlation with other wells, as revealed via INPEFA attribute log (Fig. 7). The probability

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of propagation of the Garau intervals based on Sedimentary Conceptual Model (SCM) in the field is shown in Fig. 8 A and B. Besides this, cores macroscopic and microscopic petrographic analysis, have led to the identification of seven microfacies types, which were grouped into five main microfacies. Depositional environments of these facies range from the basin to margin setting. However, most of the recognized lithofacies belong to the basin environments except for the W01 which suggests slope and margin microfacies. As the SCM shows, none of the wells have penetrated the main Garau Formation in this field, and the W-02 and W-03 are the only wells penetrated into the tongue of the Garau successions. According to SCM, the biofacies changed toward deep basin followed by an increase in clay content which could probably be an indication of facies modification from Sarvak to Garau Formation toward the NW (Fig. 9 andFig. 10). The seven determined microfacies types have been listed below: F1) Rudist and Echinoderm, packstone to grainstone: rudist debris constitutes the main components of this facies, and other less significant bioclasts are echinoderms, bivalves, bryozoans, and benthic foraminifera (Nummofalothia). Based on its stratigraphic position, the succession with this lithofacies is assigned to the upper Cenomanian. These rudist-bearing cored intervals show well visible porosity and low clay content (low CGR log values) (Fig. 9).

F2) Oncoid packstone to grainstone: The lagoonal to open marine indicators such as oncoid, bryozoan, and echinoderm debris are prominent components in this facies. Interparticle and intraparticle pores are the main pore types. Often, early marine cementation occluded the pore spaces. Dolomitization had no important effect on the reservoir properties of this facies. This facies also categorized in good reservoir rocks and also same as microfacies one shows little clay. The facies F1 and F2 having been integrated for facies modeling; these two facies have good reservoir quality and less clay content (Fig. 9). 15

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F3) Orbitolinid-peloid packstone: These facies is composed of intraclasts with various grain sizes (sand- to pebble-grade) and shapes, which comprises medium-grained peloid, Orbitolinid skeletal packstone can be introduced as the main type of carbonate facies. It should be added that the main source of fine grain peloidal debris is related to destruction of micritized foraminifers and other micritized skeletal debris. There are some assemblages of distinct benthic foraminifers such as those of family Orbitolinidae (Orbitolina sp. and Dictyoconus sp.), which are accompanied with some fragments of micritized echinoderm and bivalve debris (Fig. 9). F4) Orbitolinid peloid, skeletal wackestone/packstone: This facies is marked by a mixture of shallow (such as Orbitolinid, Ostracod and foraminifera) and open marine biota such as echinoderms and brachiopods, together with scored or erosional surfaces, storm deposits and hummocky cross stratification. Due to the mud-dominated nature, this facies has less reservoir quality than F1 and F2 microfacies. The microfacies F3 and F4 have been mixed for modeling. Because of these lithofacies have equal reservoir quality and based on CGR log clay content has increased in the matrix. Which effect cause to reservoir quality be decreased while comparing with other microfacies (Fig. 9). F5) Fine skeletal wackestone to packstone: This core interval is essentially dominated by limy grain-supported facies, which can be assigned to a part of limy Sarvak and Garau successions. This core interval was started with bioturbated fine skeletal wackestone to packstone (as the main facies) and then followed by a significant stack of fine grain skeletal packstone with a notable amount of glauconitic debris. The reservoir quality of this lithofacies is less than aforementioned once (Fig. 10). F6) Fossiliferous bioturbated wackestone-mudstone: this facies is composed of fine bioclasts including brachiopods, sponge spicules, echinoderms and bryozoans in which bioturbation is

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present in the form of burrow fills. It is interpreted to have deposited in the basin depositional setting. This facies has poor reservoir properties (Fig. 10). F7) Pelagic mudstone: this facies is characterized by shale and marl lithology with pelagic fossils such as Calcisphaerula innominata and Hedbergella sp. In terms of sedimentary environment, this facies was deposited in the pelagic deep marine setting, which can be coincided with the outershelf carbonate platform, and mostly composed of mudstone. From reservoir point of view, the quality of these successions is poor (Fig. 10). The five lithofacies have been categorized for facies modeling based on reservoir point of view. Due to sparse core data the MRGC method has been implemented for extracting of electrofacies and supervised by core facies in the Sarvak and Garau successions this lithofacies are nominated: rudist-oncoids, packstone to grainstone (RO), orbitolinid peloid packstone (OP), fine orbitolinid wackestone to packstone (FO), echinoderm bioturbated mudstone (BM), oligosteginid mudstone (OM). 5. Facies Modeling 5.1. Facies generating Among the drilled wells, nine had electrical log data which were implemented to generate electrofacies. The main important logs include Gamma Ray, Sonic, density, and neutron along with a more precise Corrected Gamma Ray log which was used for clay content estimation (especially practical in deep marine facies). The MRGC method was employed in generating electrofacies using supervised data. The reasons for using this method refer to reservoir high heterogeneity of the rock fabric and vertically rhythmic changing of lithofacies in the wells. In order to identify reservoir facies, there was a need to understand how depositional setting of lithofacies and those clay content effected on reservoir 17

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behavior. Hence, this method could enhance the generating of the electrofacies so that reservoir quality straightforward related to clay content of lithofacies and also pore throat distribution. As mention earlier, due to the basin to margin environments of deposited lithofacies, amount of clay plays important role in porosity distribution, so capturing lithofacies and distinguished them by clay content via electrical logs especially along with Corrected Gamma Ray (CGR) with supervised cores data are advantages of this approach. Therefore, the MRGC method enables the underlying structure of the data is analyzed and natural data groups are formed that may have very different densities, sizes, shapes and relative separations (Ye and Rabiller 2000). One of the most important steps for generating the electrofacies are a selection of a reference data set. In this study, petrophysical logs including CGR, Sonic, Neutron and Density were used and selected as input data for generating the MRGC clustering. Histogram and cross plot of petrophysical logs are shown in Table 1 and Fig. 11, respectively. According to geological and reservoir information such as core description, zonation and lithology features, five clusters and facies were considered, which supervised with sedimentary facies. Taking into accounts the changes in lithological and petrophysical characteristics, the optimum model of five clusters were obtained after running the MRGC method with selecting 3 and 6 electrofacies as the minimum and maximum limits. The lithofacies characterized in these wells are RO, OP, FO, BM and OM and have been coded as 1, 2, 3, 4 and 5, respectively. Therefore, from reservoir quality point of view, the RO and OP represent more reservoir quality compared (most of them are located in HSTs sequences unit) to FO, BM and OM. Fig. 12 shows cross plots of petrophysical data opposite each other according to the electrofacies obtained from the MRGC model. 5.2. Preparing of model

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Prior to building the facies model, a structural model was constructed using thrust faults, horizons, and zones based on 2D seismic structural interpretation, it is worth mentioning that the thrust faults caused to compartment the reservoir, these faults active during and post-collision (the Miocene Time) of the Zagros orogeny in region (Alavi 2007; Murris 1980; Ricou et al. 1977). The layering of the model was defined along with good quality control to avoid distorted cells as well as to ascertain the development of the static model which can further be used in dynamic simulations. In the next step, lithofacies data were up-scaled, and data was imported into the 3D model using the available methods. Checking all the wells, it is obviously visible that W-01 has a lower clay content compared to other wells, and there is a trend showing a clay content increase from the southeast (Margin environment) to the northwest (Basin environment) (see Fig. 13 and Fig. 14). Regarding the depositional setting of lithofacies, it can be seen that the amount of clay content increased in W-05, and in some cases, mudstone lithofacies term were used in the description of cutting thin sections. Therefore, recognition of clay increase in lithofacies can be useful to determine the depositional environment belts. To incorporate the trend in facies based on petrophysical data, the volume of shale in the wells 01, 03, 04 and 05 (from SE to NW) were evaluated based on CGR log (Table 2). Specific trends can be incorporated based on the changes of facies in the sedimentary successions from the southeast toward the northwest of the field. The horizontal axis of this trend has been tuned according to the distances of each well with the reference well (W-01) having the lowest clay content. The vertical axis shows clay volumetric percentages of that was evaluated in the Sarvak and S&G intervals. According to this diagram, it is predictable that the clay content has been increased in the two formations toward the northwest. Therefore, clay content in the Sarvak Formation in the field changes significantly from the W-05 to the west and converts to deep basin lithofacies with high clay content. However, the facies

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changes in the S&G intervals more closely to the W-01. It is while some S&G intervals such as S&G-1, S&G-2 and S&G-3 show more lateral facies changes. This transition of lithofacies from southeast to northwest can be defined as carbonate belts in the marine basin. 5.3. Model procedure The Truncated Gaussian Simulation with trend (TGSim) algorithm was implemented to distribute facies parameters via Petrel E&P software (Fig. 15). This method is a stochastic approach which is used to distribute facies in environments where the transgression or retrograding of the sea has occurred. The advantages of this method include using the wells data by the statistical method and its distribution in the model and determining the trend in the area where the lithofacies belts are observed. Ordering of facies dictated that which facies will be modeled adjacent to one another. Therefore, employing this method could prevent distribution of lithofacies entire model as randomly (i.e. generate only via a Gaussian seed), assigning of lithofacies belts and determining of clay trend toward the NW portion of field (toward basin), consequences of distribution of properly facies in the field, other properties Such as Porosity, water saturation and permeability values are placed in right lithofacies. 3D Facies model was constructed for each zone based on statistical and a variogram analysis for all facies in each zones (Fig. 15A and B). Unlike TGSim, The Sequential Indicator Simulation (SISim) method was implemented for zones without clear trends observed. In this study, five main lithofacies belts were recognized in the Sarvak Formation including the Rudist-Oncoids, packstone to grainstone (RO), Orbitolinid Peloid packstone, fine Orbitolinid wackestone to packstone (FO), Bioturbated echinoderm mudstone/wackestone (BM), Oligosteginid mudstone/wackestone (OM). The methodology used in this study for facies modeling accords excellently with wells data; however, for some zones, (S&G-1, S&G-3, S&G-4, S&G-5 and S&G-7) the SISim algorithm was 20

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used. According to the direction of sea propagation from the northwest and the Sarvak and Garau formation depocenter the azimuth of retrogradation of sea-level was selected as 328º. This is accorded with palaeogeography map of Bordenave and Hegre, (2010) (see Fig. 3), and sequence stratigraphy which shows thickening of the Garau successions is toward N-NW of the study area. Selection of each facies belt boundary is based on clay trend graph represented in Fig. 13,Fig. 14 and Table 2, where significant changes occur in clay percent values, for more pictures related to facies model refer to (Fig. 16 andFig. 17 (A-D)). Finally, the lithofacies model was constructed using paleontological and stratigraphical studies, zonation based on INPEFA gamma ray log, petrophysical logs, conceptual model, MRGC clustering and TGSim algorithm. 6. Discussion This paper is focused on providing a practical workflow for accurate distribution of lithofacies and capturing reservoir heterogeneity via TGSim algorithm in the entire reservoir (field dimension is about10*37km) as shown in Fig. 18. The facies modeling which has been constructed based on sequence stratigraphy framework in simultaneous successions requires two main input parameters: Indication of biofacies ages, and zonation based on variation of sequences in the Sarvak Formation with the Garau’s successions tongue (Albian-Turonian). Detection of the ages in these units has been performed based on foraminifera microfossils considering the studies carried out by James and Wynd (1965) and later revised by BahramizadehSajjadi (2012) in the Lurestan Basin. Our study revealed that the Sarvak Formation has different attributes and lithofacies contents compared with the Persian Gulf, the deep marine facies is a characteristic of this unit in the study area.

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Reservoir zonation has been conducted based on INPEFA log, which is an attribute of Gamma log. Nio et al. (2005) proposed an analytical algorithm using GR log which can generate an attribute log. This log can be employed as a proxy for sediment texture and process in case sparse core and thin section data are available. The method provides accurate results since an approximate thickness of 750 m from the Saravk and Garau successions can be taken into consideration, whereas only a few intervals have been cored. Therefore, based on INPEFA log, paleontological, and sedimentary studies, new zonation has been provided in sequence stratigraphy framework. Five sequences were deposited during Albian-Turonian time (113Ma-89Ma) including the I and II sequences in the S&G and sequences of III, IV and V in Sarvak successions. But the W-01 shows only one sequence in S&G successions which as aforementioned, could be attributed to paleohigh setting arising from tectonic activity during deposition of S&G unit in the SE portion of the field. Selecting a proper facies model algorithm is of paramount importance enabling us to model complex lithofacies in any reservoir (Amour et al. 2012) see Fig. 18. The TGSim algorithm has been selected for the Sarvak and Garau successions, where interfingering and simultaneous facies were deposited. The reasons for selecting this method originate from reservoir scale depositional geometry and ordering the facies trend transitions. The advantage of the TGSim algorithm over to SISim are reproducing the depositional geometries and trending of lithofacies which provides robust facies model in accordance with geological concepts. 7. Conclusions The methodology has been used in this paper is based on full field studies, enabling geologists to generate a reliable 3D facies model by using Petrel software. The facies model was constructed using the TGSim in simultaneous facies reservoirs. The most unique and important feature of this approach is that it produces a realistic geomodel via avoiding the random distribution of reservoir

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property. In this study, the available data for building the facies model include well log data, thin sections, and cores from some intervals of the reservoir. Through the implementation of the TGSim, we were able to take into account well data, trends, distributions of lateral and vertical changes, and tongues of two lithofacies with the same ages. The final facies model indicates a good correlation with the conceptual model. This suggests that the properties have been properly distributed in the reservoir. Clustering method based on MRGC was employed to generate electrofacies and their assignment to lithofacies as a means of representing reservoir heterogeneity. A clay trend was observed toward the northwest, which was also corroborated by the wells from this field and the adjacent one. As a result, reservoir quality and field recovery diminish in this direction. The outcomes of this study introduced a new strategy for the development of the field toward the northwest and prepared a plan for increasing the number of production wells between the W-01 and W-02.

ACKNOWLEDGEMENTS The National Iranian oil company supported this work. The authors would like to especially thank the Iranian Central Oil Fields Company (ICOFC) for their permission to publish this paper, particularly Mr. Behbahani, the ICOFC head of reservoir engineering. We also highly appreciate the CEO of Magma Energy company Mr. Azad for his kind supports during the preparation of this study. Special thanks to Dr B. Esrafili-Dizaji who greatly improved and clarified the earlier version of the manuscript.

References

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Murris RJ (1980) Middle East: Stratigraphic Evolution and Oil Habitat 64:597-618 doi:10.1306/2F918A8B-16CE-11D7-8645000102C1865D Navidtalab A, Rahimpour-Bonab H, Nazari-Badii A, Sarfi M (2014) Challenges in deep basin sequence stratigraphy: a case study from the Early–Middle Cretaceous of SW Zagros Springer 60:195-215 doi:10.1007/s10347-013-0377-x Nio SD, Brouwer J, Smith D, de Jong M, Böhm A (2005) Spectral trend attribute analysis: applications in the stratigraphic analysis of wireline logs first break 23 Odezulu CI, Olawole S, Saikia K, Mento D (2014) Effect of Sequence Stratigraphy-based Facies Modeling for Better Reservoir Characterization: A Case Study from Powder River Basin. Paper presented at the Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, UAE, 2014/11/10/ Omidvar M, Mehrabi H, Sajjadi F, Bahramizadeh-Sajjadi H, Rahimpour-Bonab H, Ashrafzadeh A (2014) Revision of the foraminiferal biozonation scheme in Upper Cretaceous carbonates of the Dezful Embayment, Zagros, Iran: integrated palaeontological, sedimentological and geochemical investigation Revue de micropaléontologie 57:97-116 Rahimpour-Bonab H, Mehrabi H, Enayati-Bidgoli A, Omidvar M (2012) Coupled imprints of tropical climate and recurring emergence on reservoir evolution of a mid Cretaceous carbonate ramp, Zagros Basin, southwest Iran Cretaceous Research 37:15-34 Rahimpour‐Bonab H et al. (2013) Palaeo‐exposure surfaces in Cenomanian–santonian carbonate reservoirs in the Dezful embayment, SW Iran Journal of Petroleum Geology 36:335-362 Razin P, Taati F, Van Buchem F (2010) Sequence stratigraphy of Cenomanian–Turonian carbonate platform margins (Sarvak Formation) in the High Zagros, SW Iran: an outcrop reference model for the Arabian Plate Geological Society, London, Special Publications 329:187-218 Ricou L, Braud J, Brunn J (1977) Le Zagros Livre à la mémoire de AF de Lapparent (1905–1975) Mémoire hors Série de la Société Géologique de France 8:33-52 Serra Ot, Abbott H (1982) The contribution of logging data to sedimentology and stratigraphy Society of Petroleum Engineers Journal 22:117-131 Sharland P et al. (2001) Sequence stratigraphy of the Arabian Plate GeoArabia 2:371 Sharp I et al. (2010) Stratigraphic architecture and fracture-controlled dolomitization of the Cretaceous Khami and Bangestan groups: an outcrop case study, Zagros Mountains, Iran Geological Society, London, Special Publications 329:343-396 Sherkati S, Letouzey J (2004) Variation of structural style and basin evolution in the central Zagros (Izeh zone and Dezful Embayment), Iran Marine and petroleum geology 21:535-554 Sisinni V, McDougall N, Guarnido M, Vallez Y, Estaba V (2016) Facies modeling described by probabilistic patterns using Multi-point statistics an application to the k-field, Libya American Association of Petroleum Geologists 229-229 doi:10.1190/ice2016-6320106.1 Takin M (1972) Iranian geology and continental drift in the Middle East Nature 235:147 Tomassetti L, Petracchini L, Brandano M, Trippetta F, Tomassi A (2018) Modeling lateral facies heterogeneity of an upper Oligocene carbonate ramp (Salento, southern Italy) Marine and Petroleum Geology 96:254-270 doi:https://doi.org/10.1016/j.marpetgeo.2018.06.004 Vail Pea (1991) The stratigraphic signatures of tectonics, eustasy and sedimentology an overview. In: Cycles and events in stratigraphy, Einsele Springer Verlag van Bellen RC, Dunnington H, Wetzel R, Morton D (1959) Lexique Stratigraphique International: Asie. Iraq. Tertiary. Mesozoic and Palaeozoic. Centre National de la Recherche Scientifique, Vergés J, Goodarzi M, Emami H, Karpuz R, Efstathiou J, Gillespie P (2011) Multiple detachment folding in Pusht-e Kuh arc, Zagros: Role of mechanical stratigraphy Ye S-J, Rabiller P A new tool for electrofacies analysis: multi-resolution graph-based clustering. In: SPWLA 41st annual logging symposium, 2000. Society of Petrophysicists and Well-Log Analysts,

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Figs.

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Fig. 1. (1A) Location map of the Zagros fold-thrust belt in Iran. (1B) The figure shows the main sub-divisions of the Zagros Fold-thrust Belt such as the Lurestan, Izeh, Dezful embayment, Abadan plain, Fars and Bandar-e-Abbas hinterland areas (Takin 1972; Motiei 1995; Sherkati and Letouzey 2004; Alavi 2007; Farzipour‐Saein et al. 2008). The study area of the Tang-e-Bijar field is shown inside a rectangle in the south Lurestan area. (1C) It shows the underground contour map (UGC) of the Sarvak Formation (countor map is adjusted with meter, based on sub-sea true vertical depth (SSTVD) and location of the studied wells; cross section on the map correlates the wells (W-01, W-02, W-03, W-04 and W-05) biozones which are depicted in Fig. 7.

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Fig. 2. Cretaceous biofacies and their stratigraphic position chart in the Lurestan Province (I represents the beginning of section from Emam Hasan (EH) well and II is located in the Mal-eKuh (MK) well; see Fig. 3 surface location map). The chart shows laterally and vertically changing of the Sarvak and Garau formations. The classification of each formations is based on James and Wynd (1965) biofacies studies in the Zagros region revised by Bahramizadeh-Sajjadi (2012). The study area is shown in a rectangle.

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Fig. 3. Isopach map of the distribution of the Garau Formation in the Zagros region (Bordenave and Hegre 2010). The solid line shows the location of biofacies and stratigraphic section which is depicted in Fig. 2. (EH: Emam Hassan, MK: Male-Kuh, TG: Tang-e-Bijar, Hn: Hulayilan, Sk: Sarkan).

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500µm

500µm

500µm

500µm

Fig. 4. (A-D). Microscopic photos of thin sections from well-02 showing Cenomanian carbonate microfacies. (A) Argillaceous limestone with indetermined Oligosteginid, Pithonella ovalis and Calcisphaerula innominata at depth 1,062 SSTVD (1,620 MD). (B) Gray marly limestone with Pithonella oxalis, Calcisphaerula innominata and Stomiosphaera sphaerica at depth 1,070 SSTVD (1,628 MD). (C) Glauconitic gray limestone with planktonic foraminifera at depth 1,350 SSTVD (1,909 MD). (D) Gray limestone with Orbitolina at depth 1,526 SSTVD (2,086 MD) (Rahaghi 1976 unpublished study). (Blue arrows show the indicated microfossils)

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500µm

500µ m

500µm

500µm

Fig. 5. (A-D). Revisited microscopic thin sections from W-02 and W-03 (A) Globigerinelloides

algeriana in W-03 index fossils of the Garau Formation at depth 1,517 SSTVD (2,364 MD) with Albian age. (B) Biglobigerinella barri with Rotalipora sp. Related to the Sarvak Formation at depth 1,549 SSTVD (2,399 MD) in W-03 with Albian age. (C) Rotalipora appenninica. Related to the Sarvak Formation at depth 1,293 SSTVD (1,851 MD) in W-02 with Albian age. (D) Heterohelix sp. related to the Sarvak Formation at 1,134 SSTVD (1,692 MD) in W-02 with Cenomanian-Albian age. The black arrows indicate the location of the mentioned fossils.

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Fig. 6. The sequence-based correlation zones of the W-01, W-02 and W-03 wells of Tang-e-Bijar

field with the nearby field based on biozones, lithofacies changes and log data (first track shows the CGR and GR logs and second track shows the Sonic log (DT). The correlation flattens on the S&G_01. The Garau’s successions tongue is shown with brown color, the Sarvak Formation intervals beneath the Garau’s tongue proved by biozones contents and shown with blue color. The W-01 only shows correlation with other wells in the S&G_1. The other zones show the Sarvak’s biozones. The W-02 and W-03 the Garau succession were deposited in S&G_1 to S&G_4 which is revealed by Globigerinelloides algeriana assemblage zone and that can be correlated with the Garau unit in the nearby field. The zonation of the Sarvak-Garau intervals (S&G zones) naming and starting are the correlation.

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Fig. 7. Chronostratigraphic, biozonation and sequence stratigraphic subdivisions of the Sarvak

Formation and S&G successions in the study area. The foraminifera biozones are based on James and Wynd (1965) biofacies studies in the Zagros region. Biofacies of W-01, W-02 and W03 were studied by Bahramizadeh-Sajjadi (2009), Rahaghi, (1976) and Hamrang, (1969) as unpublished works, respectively. The sequence stratigraphy correlation is compared to Sharland et al. (2001) system tracts and shows acceptable matching. however, in the faulted successions due to local sea level fluctuation, this match is not remarkable.

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Fig. 8. (A) Conceptual model of sedimentary environments of the Sarvak and Garau successions

with laterally interfingering of the Garau’s tongue (not in scale). (B) Schematic section of the rimmed shelf carbonate platform recorded by the Sarvak and Garau successions. (FWWB: fairweather wave base, SWB: storm wave base, ML: Marl, Lst: limestone, Arg Lst: argillaceous limestone and Sh: shale) .

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Fig. 9. Core lithofacies, depositional environment and sequence stratigraphy of W-01 (see the

location of the core interval in Fig. 7).

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Fig. 10. Core lithofacies, depositional environment and sequence stratigraphy of W-04 (see the

location of core interval in Fig. 7). 36

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Fig. 11. Assortment, histograms and distribution curves of the five lithofacies in the MRGC

model (the code numbers and name of lithofacies are shown in the figure. The pure limestone with blue (cyan) to mudstone (slate grey) facies have been selected to indicating clay increases according to lithofacies. Weight represents, numbers of each lithofacies in the Tang-e-Bijar wells’s column, CGR: Corrected Gamma Ray, NPHI: log of Neutron, RHOB: log of density and DT: represents of sonic log.

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Fig. 12. Cross plots of the variety of petrophysical logs according to the five supervised

electrofacies in the MRGC model.

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Fig. 13. Trends of clay content in the the Sarvak and S&G successions from the SE to NW wells

(the reference point on X axis has been selected from the W-01); the trend lines are based on the CGR log and shale volume. The lithofacies belts boundaries are separated due to shale volume content.

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Fig. 14. (A-C) Correlation of modeled electrofacies in the Sarvak and Garau successions in the

field’s wells. (A) Correlation through the wells (W-09, W-08, W-05, W-04, W-07) in the framework of the sequence zonation; (B) Location of correlation line on the Sarvak map; (C) Contenued correlation through the wells (W-06, W-03, W-02 and W-01); first track includes SGR and CGR logs, the second track represents of modeled lithofacies and the third track is the 40

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evaluated the volume of limestone and shale in the wells column. (The blank area has not been evaluated, due to lack of data).

B

Fig. 15. (A) Example of statistical analysis which was used for the facies modeling; (B) Example

of TGSim workflow which applied in facies modeling.

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W-07 W-05

W-04

RO OP

W-06 W-03

W-09 W-08

FO BM OM

W-02

W-01

Fig. 17

Fig. 16. 3D view of facies distributed in the entire reservoir (vertical scale =1). (rudist-oncoids,

packstone to grainstone (RO), orbitolinid peloid packstone (OP), fine orbitolinid wackestone to packstone (FO), bioturbated echinoderm mudstone to wackestone (BM), Oligosteginid mudstone (OM) litho-facies. A vertical section from W-01 to W-05 is depicted in Fig. 17.

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Fig. 17. (A-D) Vertical sections of the lithofacies model through the wells, showing depositional

setting and lithofacies from the SE to NW of the field (vertical scale =1). (A) Vertical section through W-01 toward the west of W-05, facies model showing increasing of clay content toward the northwest of field (indicates marginal toward basinal environments), clay volume log tie to the wells; (B) Close up vertical section from east of W-02 toward the NW of W-05 the CGR log tie to the wells indicates those shale and limestone intervals. (C) Close up view of a portion of lithofacies in location of W-01, showing the less clay content intervals in the well column; the CGR log was tied to the well; (D) Close up view of the lithofacies of the W-04 along with system tracts. 43

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Fig. 18. Workflow of the building of the facies model in simultaneous successions.

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Tables Table 1 Average petrophysical parameters logs as input data in MRGC workflow. Lithofacies are selected as associated data. (Weight indicate numbers of each lithofacies in the Tang-eBijar wells’s column, CGR: Corrected Gamma Ray, NPHI: Neutron-Porosity log, RHOB: log of density and DT: represents of the sonic log). Facies Weight CGR NPHI RHOB

DT

RO

5611

6.27

0.01

2.71

53.32

OP

12871

10.66

0.04

2.67

57.85

FO

6640

16.13

0.06

2.68

69.87

BM

6511

31.85

0.09

2.68

64.05

OM

4064

27.97

0.26

2.57

88.93

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Table 2 Average weight of clay contents in categorized zones from the SE to NW field’s wells. The distance calculated from the W-01 as reference well, average clay volume has been calculated in entire the Sarvak and S&G successions. Clay Volume (%) Zones

SE

NW W-01

W-02

W-03

W-04

W-05

SV-1

3.7

4.2

5.8

-*

7.76

SV-2

12.13

10.77

8.1

-

15.7

SV-3-1

10.26

8.74

7.62

9.17

10.21

SV-3-2

13.1

11.45

9.63

14.17

13.03

SV-4-1

5.6

5.35

3.97

6.16

6.56

SV-4-2

6.7

6.13

3.63

4.74

-

S&G-1

28.49

24.18

22.44

24.71

-

S&G-2

1.8

10.36

8.71

10.86

-

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Clay Volume (%) Zones

SE

NW W-01

W-02

W-03

W-04

W-05

S&G-3

0.08

25.31

26.19

29.47

-

S&G-4

0.4

3.09

1.66

3.63

-

S&G-5

1.8

5.15

5.59

9.29

-

S&G-6

2.4

3.62

10.86

-

-

S&G-7

14.3

16.52

-

-

-

From W-01

0

10887

13000

14904

17383

Aveg. Sarvak

8.69

7.91

6.62

8.2

12.08

Aveg. S&G

5.73

10.61

11.73

14.49

-

Distance (m)

*

without data

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Highlights:  Facies Modeling of Albian-Turonian successions in Lurestan province at the northwest of the Zagros fold-thrust belt, Iran is the main objective of this study.  Sedimentary environment and biozones of the Sarvak and Garau formations in the study area are different, while compare with the Dezful Embayment.  For constructing facies model, available data such as well logs, cores descriptions, thin sections study, and imprecise seismic data, all information including conceptual models, regional geology, paleogeography, and stratigraphy studies have been taken into consideration.  Multi Resolution Graph Based Clustering (MRGC) techniques have been used for identifying electrofacies in reservoirs. This method can be used for generating of electrofacies from CGR, GR, DT, NPHI and RHOB logs with supervised core lithofacies data.  Determination of stratigraphic ages of the Sarvak and Garau formations have been performed based on Cretaceous foraminifera using the thin sections of the wells (Core and Cutting samples) as well as previous paleologs studies.  Sequence stratigraphy zonation and determination of the Sarvak and Garau successions age are vital for lithofacies modeling. These tasks have been conducted using Integrated Prediction Error Filter Analysis (INPEFA) log and biozone of the James and Wynd (1965).  The Truncated Gaussian with Trend method has been used to distribute facies parameters.