Effects of tectonic fracture on reservoir quality of Asmari formation in one of south-west Iranian oilfields using formation micro imager image logs

Abstract

In fractured carbonate rocks, reservoir quality is controlled by the fracture properties. Fracture system characteristics in naturally fractured carbonate reservoirs are vitally important to any development plan. This paper analyzes the effect of effective structures on reservoir quality of the Asmari Formation located in one of the Iranian oilfields in NW of the Persian Gulf. These were accomplished using analysis and interpretation of FMI borehole image logs (full bore formation micro imager). The studied field is a NE-SW trending anticline; Asmari Formation contains three parts (upper and lower Asmari) and the Ghar Sandstone section between them. The image log of the studied well has been processed and corrected using Geolog software. Then the different types of natural structures have been recognized and interpreted, and their attitudes were measured as well. The orientation data of the structures have been analyzed by drawing statistical graphs and also from a structural point of view. The results indicated that bedding is almost horizontal in this well. Moreover, different types of fractures and stylolites could be structurally related to folding. The main observed structures could be categorized as longitudinal and transversal open fractures, longitudinal filled fractures, and parallel and normal bedding stylolites. A comparison of the frequency distribution of various structures with porosity logs (i. e., neutron, density, and sonic logs) shows that the open fractures cause an increase in porosity. However, in some part of the well the filled fractures and stylolites strongly decreased the porosity. Therefore, according to structural impacts on Asmari reservoir quality, it is suggested that any future drillings in the reservoir can be planned concerning the density and orientation of the structures (incredibly open fractures).

Keywords

formation micro imager log / Asmari formation / structural features / reservoir quality

References

[1] SaidiA MReservoir engineering of fractured reservoirs (fundamental and practical aspects) [M], 1987, Paris, Total Edition Press

[2] GongJ, RossenW R. Modeling flow in naturally fractured reservoirs: Effect of fracture aperture distribution on dominant sub-network for flow [J]. Petroleum Science, 2017, 14(1): 138-154

[3] NelsonR AGeologic analysis of naturally fractured reservoirs [M], 2001, Houston, Texas, Gulf Professional Publishing

[4] AmeenM S, HailwoodE A. A new technology for the characterization of microfractured reservoirs (test case: Unayzah reservoir, Wudayhi field, Saudi Arabia) [J]. AAPG Bulletin, 2008, 92(1): 31-52

[5] LaiJ, WangG-w, FanZ-y, et al. . Fracture detection in oil-based drilling mud using a combination of borehole image and sonic logs [J]. Marine and Petroleum Geology, 2017, 84: 195-214

[6] van Golf-RachtT DFundamentals of fractured reservoir engineering [M], 1982, Amsterdam, Elsevier Scientic Pub. Co.

[7] GILMAN J R, WANG H, FADAEI S, et al. A new classification plot for naturally fractured reservoirs [C]//Canadian Unconventional Resources Conference. Calgary, Alberta, Canada, 2011: 146580. DOI: https://doi.org/10.2118/146580-MS.

[8] SOTO B R, MARTIN C, P_EREZ O, et al. A new reservoir classification based on pore types improves characterization [C]//International Conference and Exhibition. Barcelona, Spain, 2012: 152872.

[9] EbrahimiN, JamshidiS, GholinezhadS. Estimation of naturally fractured oil reservoir properties using the material balance method [J]. Scientia Iranica, 2014, 21: 781-791

[10] PrioulR, DonaldA, KoepsellR, et al. . Forward modeling of fracture-induced sonic anisotropy using a combination of borehole image and sonic logs [J]. Geophysics, 2007, 72(4): E135-E147

[11] KhoshbakhtF, MemarianH, MohammadniaM. Comparison of asmari, pabdeh and gurpi formation’s fractures, derived from image log [J]. Journal of Petroleum Science and Engineering, 2009, 67: 65-74

[12] PrioulR, JockerJ. Fracture characterization at multiple scales using borehole images, sonic logs, and walkaround vertical seismic profile [J]. AAPG Bulletin, 2009, 93: 1503-1516

[13] TokhmchiB, MemarianH, RezaeeM R. Estimation of the fracture density in fractured zones using petrophysical logs [J]. Journal of Petroleum Science and Engineering, 2010, 72(1–2): 206-213

[14] AmeenM, MacphersonK, AlmarhoonM, et al. . Diverse fracture properties and their impact on performance in conventional and tight-gas reservoirs, Saudi Arabia: The Unayzah, South Haradh case study [J]. AAPG Bulletin, 2012, 96: 459-492

[15] KhoshbakhtF, AzizzadehM, MemarianH, et al. . Comparison of electrical image log with core in a fractured carbonate reservoir [J]. Journal of Petroleum Science and Engineering, 2012, 86: 289-296

[16] LyuW-y, ZengL-b, LiuZ-q, et al. . Fracture responses of conventional logs in tight-oil sandstones: A case study of the Upper Triassic Yanchang Formation in southwest Ordos Basin, China [J]. AAPG Bulletin, 2016, 100: 1399-1417

[17] RezaieA H, Nogole-SadatM A. Fracture modeling in asmari reservoir of rage sefid oil-field by using multi well image log (FMS/FMI) [J]. Iranian Int J Sci, 2004, 5(1): 107-121

[18] EhrenbergS N, NadeauP H, AqrawiA A M. A comparison of Khuff and Arab reservoir potential throughout the middle east [J]. AAPG Bulletin, 2007, 91(3): 275-286

[19] AQRAWI AA, WENNBERG OP. The control of fracturing and dolomitisation on 3D reservoir property distribution of the asmari formation (oligocene-lower miocene) [C]//International Petroleum Technology Conference, Dubai, UAE 2007: IPTC-11191-MS. DOI: https://doi.org/10.2523/IPTC-11191-MS.

[20] JamesG, WyndJ G. Stratigraphic nomenclature of Iranian oil consortium agreement area [J]. AAPG Bulletin, 1965, 49: 2182-2245

[21] van BuchemF S P, GerdesK D, EstebanM. Mesozoic and Cenozoic Carbonate Systems of the Mediterranean and the Middle East: Stratigraphic and Diagenetic Reference Models. Geological Society of London, Special Publications, 2010, 329: 219-263 van BUCHEM F S P, ALLAN T L, LAURSEN G V, et al. Regional stratigraphic architecture and reservoir types of the oligo-miocene deposits in the dezful embayment (Asmari and Pabdeh Formations) SW Iran. [M]

[22] Esrafili-DizajiB, Rahimpour-BonabH. Carbonate reservoir rocks at giant oil and gas fields in sw Iran and the adjacent offshore: A review of stratigraphic occurrence and poro-perm characteristics [J]. Journal of Petroleum Geology, 2019, 42(4): 343-370

[23] AdamsC G, BourgeoisE. Asmari biostratigraphy: Iranian oil operation companies [J]. Geological and Exploration Division, 1967, 1074: 1-74

[24] SeyrafianA. Microfacies and depositional environments of the asmari formation, at dehdez area (a correlation across central Zagros Basin) [J]. Carbonates and Evaporites, 2000, 15(2): 121-129

[25] SeyrafianA, MojikhalifehA. Biostratigraphy of the late paleogene-early neogene succession, north-central border of Persian Gulf, Iran [J]. Carbonates and Evaporites, 2005, 20(1): 91-97

[26] Vaziri-MoghaddamH, KimiagariM, TaheriA. Depositional environment and sequence stratigraphy of the Oligo-Miocene Asmari Formation in SW Iran [J]. Facies, 2006, 52(1): 41-51

[27] AmirshahkaramiM, Vaziri-MoghaddamH, TaheriA. Sedimentary facies and sequence stratigraphy of the asmari formation at chaman-bolbol, Zagros Basin, Iran [J]. Journal of Asian Earth Sciences, 2007, 29(5–6): 947-959

[28] EhrenbergS N, PickardN A H, LaursenG V, et al. . Strontium isotope stratigraphy of the Asmari Formation (oligocene-lower miocene), SW Iran [J]. Journal of Petroleum Geology, 2007, 30(2): 107-128

[29] MossadeghZ K, HaigD, AllanT, et al. . Salinity changes during late oligocene to early Miocene Asmari formation deposition, Zagros mountains, Iran [J]. Palaeogeography, Palaeoclimatology, Palaeoecology, 2009, 272: 17-36

[30] DillM A, SeyrafianA, Vaziri-MoghaddamH. The Asmari Formation, North of the Gachsaran (dill anticline), Southwest Iran: Facies analysis, depositional environments and sequence stratigraphy [J]. Carbonates and Evaporites, 2010, 25: 145-160

[31] SadeghiR, Vaziri-MoghaddamH, TaheriA. Microfacies and sedimentary environment of the Oligocene sequence (Asmari Formation) in Fars sub-basin, Zagros Mountains, southwest Iran [J]. Facies, 2011, 57(3): 431-446

[32] HosseiniE, NeshatG J, HabibniaB. Characterization of fractures of asmari formation by using image logs, case study: Marun oilfield [J]. American Journal of Oil and Chemical Technologies, 2015, 4(3): 269-276

[33] FaragS M, MasC, MaizeretP D, et al. . An integrated workflow for granitic basement reservoir evaluation [J]. SPE Reservoir Evaluation, 2010, 13(6): 893-905

[34] AbdelR. Prediction of naturally fractured reservoir performance using novel integrated workflow [J]. International Journal of Advanced Computer Science and Applications, 2017, 8(4): 31473429

[35] GhazbanFPetroleum geology of the persian gulf [M], 2010, Iran, Tehran University

[36] KonyuhovA, MalekiB. The persian gulf basin: Geological history, sedimentary formations, and petroleum potential [J]. Lithology and Mineral Resources, 2006, 41: 344-361

[37] AQRAWI A A M, WENNBERG O P. The control of fracturing and dolomitisation on 3D reservoir property distribution of the Asmari Formation (oligocene-lower miocene) [C]//International Petroleum Technology Conference. Dubai, UAE. International Petroleum Technology Conference, 2007. DOI: https://doi.org/10.2523/11191-ms.

[38] MCQUILLAN H. Fracture-controlled production from the oligo-miocene Asmari Formation in Gachsaran and Bibi Hakimeh Fields, Southwest Iran carbonate petroleum reservoirs, Iran [M]//ROEHL P, CHOQUETTE P. Carbonate Petroleum Reservoirs. Casebooks in Earth Sciences. New York: Springer, 1985: 511–523. DOI: https://doi.org/10.1007/978-1-4612-5040-1_33.

[39] MOTIEI H. Petroleum geology of Zagros [R]. Iran Geological Survey of Iran, 1996.

[40] AmeenM S, BuhidmaI M, RahimZ. The function of fractures and in situ stresses in the Khuff reservoir performance, onshore fields, Saudi Arabia [J]. AAPG Bulletin, 2010, 94(1): 27-60

[41] WilsonM E J, LewisD, YogiO, et al. . Development of a Papua New Guinean onshore carbonate reservoir: A comparative borehole image (FMI) and petrographic evaluation [J]. Marine and Petroleum Geology, 2013, 44164-195

[42] KeetonG I, PranterM J, ColeR D, et al. . Stratigraphic architecture of fluvial deposits from borehole images, spectral-gamma-ray response, and outcrop analogs, Piceance Basin, Colorado [J]. AAPG Bulletin, 2015, 99(10): 1929-1956

[43] BrekkeH, MaceachernJ A, RoenitzT, et al. . The use of microresistivity image logs for facies interpretations: An example in point-bar deposits of the McMurray Formation, Alberta, Canada [J]. AAPG Bulletin, 2017, 101(5): 655-682

[44] LaiJ, WangG-w, WangS, et al. . A review on the applications of image logs in structural analysis and sedimentary characterization [J]. Marine and Petroleum Geology, 2018, 95: 139-166

[45] BrownJ, DavisB, GawankarK, et al. . Imaging: Getting the picture downhole [J]. Oilfields Review, 2015, 27(2): 4-210

[46] RiderHThe geological interpretation of well logs [M], 2002, Sutherland, Scotland, Rider-French Consulting

[47] NieX, ZouC-c, PanL, et al. . Fracture analysis and determination of in situ stress direction from resistivity and acoustic image logs and core data in the Wenchuan Earthquake Fault Scientific Drilling Borehole-2 (50–1370 m) [J]. Tectonophysics, 2013, 593: 161-171

[48] LaiJ, WangG-w, FanZ-y, et al. . Sedimentary characterization of a braided delta using well logs: The Upper Triassic Xujiahe Formation in Central Sichuan Basin, China [J]. Journal of Petroleum Science and Engineering, 2017, 154: 172-193

[49] PrioulR, DonaldA, KoepsellR, et al. . Forward modeling of fracture-induced sonic anisotropy using a combination of borehole image and sonic logs [J]. Geophysics, 2007, 72(4): E135-E147

[50] KosariE, Ghareh-ChelooS, Kadkhodaie-IlkhchiA, et al. . Fracture characterization by fusion of geophysical and geomechanical data: A case study from the Asmari Reservoir, the Central Zagros fold-thrust belt [J]. Journal of Geophysics and Engineering, 2015, 12(1): 130-143

[51] FolkestadA, VeselovskyZ, RobertsP. Utilising borehole image logs to interpret delta to estuarine system: A case study of the subsurface Lower Jurassic Cook Formation in the Norwegian northern North Sea [J]. Marine and Petroleum Geology, 2012, 29(1): 255-275

[52] Ja’FariA, Kadkhodaie-IlkhchiA, SharghiY, et al. . Fracture density estimation from petrophysical log data using the adaptive neuro-fuzzy inference system [J]. Journal of Geophysics and Engineering, 2012, 9(1): 105-114

[53] MalivaR G, ClaytonE A, MissimerT M. Application of advanced borehole geophysical logging to managed aquifer recharge investigations [J]. Hydrogeology Journal, 2009, 17(6): 1547-1556

[54] SerraOFormation micro scanner image interpretation [M], 1989, Houston, Texas, Schlumberger Education Services

[55] TaiebiF, AkbarizadehG, FarshidiEDetection of reservoir fractures in imaging logs using directional filtering [C], 2017, Qazvin, Iran, IEEE: 150154

[56] ZahmatkeshI, AghliG, MohammadianR. Systematic fractures analysis using image logs and complementary methods in the Marun oilfield, SW Iran [J]. Geopersia, 2015, 5(2): 139-150