Abstract
The current findings emphasize interpreting wireline logs to assess the hydrocarbon prospect of the Lower Cretaceous Yageliemu Formation in the Yakela (YKL) gas condensate field, Tarim Basin, China. The present study consists of wireline logs of four drilled wells (S4, YK13, YK21, and YK32) and numerous reservoir zones have been comprehended. According to the petrophysical evaluation, the gas-bearing zone has high resistivity values, good porosity (Φeff) and permeability (K), low water content (Sw), and less shale content (Vsh) indicating clean sand. The petrophysical parameters of the interest zones were closely studied which are classed as good-quality sand layers with ranging effective porosities from 4.5 to 10%, permeability ranging from 0.5 to 18 mD, water saturation concentrations ranging from 55 to 59%, and the average value gas is 41–50%. The Archie equation was accurately tested to estimate water saturation in the reservoirs, revealing that in each well, Sw is less than 60%; therefore, the efficiency of the gas-bearing sand is of good quality. Lithofacies, horizontal and vertical variations of reservoir parameters, are evaluated through building self-organizing maps, isoparametric maps of the petrophysical parameters, and litho-saturation cross-plots, respectively. Isoparametric maps assist in visualizing the spatial distribution of the reservoir configuration. It is suggested that more wells be drilled in the southwestern and northwestern parts of the current research area. Due to the high water concentration and shale volume, the northeastern and southeastern portions of the understudied area must be overlooked.
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Abbreviations
- a:
-
Tortuosity factors
- AC:
-
Acoustic log (μsec/ft)
- ANN:
-
Artificial neural network
- Bulkvw:
-
Bulk volume of water
- BS:
-
Bit size (inch)
- CALI:
-
Caliper log (inch)
- Den:
-
Density log (gm/cm3)
- GR:
-
Gamma ray log (API)
- GRmin:
-
Minimum gamma ray log response (clean sandstone)
- GRmax:
-
Maximum gamma ray log response (100% shale)
- IGR:
-
Gamma ray index
- K:
-
Permeability
- m:
-
Cementation exponent
- n:
-
Saturation exponent
- NPHI:
-
Neutron porosity log (p.u)
- RILD:
-
Deep resistivity (ohm)
- RILM:
-
Medium resistivity (ohm)
- RFOC:
-
Shallow resistivity (ohm)
- Rw :
-
Water resistivity (ohm)
- Rt:
-
True formation resistivity (ohm)
- Sg:
-
Gas saturation (%)
- Sw:
-
Water saturation (%)
- SOFM:
-
Self-organizing feature map
- SP:
-
Spontaneous potential log (mV)
- Sw :
-
Water saturation (%)
- ∅T:
-
Total porosity
- ∅eff:
-
Effective porosity
- Vsh:
-
Shale volume
- S04:
-
S04 (well name)
- YKL:
-
Yakela (gas field name)
- YK13:
-
Yakela13 (well name)
- YK21:
-
Yakela21 (well name)
- YK32:
-
Yakela32 (well name)
References
Abd El-Gawad EA (2007) The use of well logs to determine the reservoir characteristics of Miocene rocks at the Bahar Northeast field, Gulf of Suez, Egypt. J Pet Geol 30(2):175–188. https://doi.org/10.1111/j.1747-5457.2007.00175.x
Abdel-Fattah MI (2014) Petrophysical characteristics of the Messinian Abu Madi formation in the baltim east and north fields, offshore Nile delta, Egypt. J Pet Geol 37(2):183–195. https://doi.org/10.1111/jpg.12577
Abdel-Fattah MI, Slatt RM (2013) Sequence stratigraphic controls on reservoir characterization and architecture: case study of the Messinian Abu Madi incised-valley fill, Egypt. Cent Eur J Geosci 5(4):497–507. https://doi.org/10.2478/s13533-012-0144-5
Abdideh M, Ameri A (2019) Cluster analysis of petrophysical and geological parameters for separating the electrofacies of a gas carbonate reservoir sequence Nat Resour Res 1–14https://doi.org/10.1007/s11053-019-09533-1
Ajisafe YC, Ako BD (2013) 3-D seismic attributes for reservoir characterization of “Y” field Niger Delta, Nigeria. IOSR J Appl Geol Geophys 1(2):23–31. https://doi.org/10.9790/0990-0122331
Al Homadhi ES, Hamada GM (2003) Determination of petrophysical and mechanical properties interrelationship for simulated sands. Eng J Univ Qatar 16:1–10. https://hdl.handle.net/10576/7879
Alabi OO, Sedara SO (2016) Evaluation and accurate estimation from petrophysical parameters of a reservoir. Am J Environ Eng Sci 3(2):68–74
Ali M, Ma H, Pan H, Ashraf U, Jiang R (2020) Building a rock physics model for the formation evaluation of the Lower Goru sand reservoir of the Southern Indus Basin in Pakistan. J Petrol Sci Eng 194:107461. https://doi.org/10.1016/j.petrol.2020.107461
Ali M, Jiang R, Ma H, Pan H, Abbas K, Ashraf U, Ullah J (2021) Machine learning-a novel approach of well logs similarity based on synchronization measures to predict shear sonic logs. J Petrol Sci Eng 203:108602. https://doi.org/10.1016/j.petrol.2021.108602
Ali N, Jamil S, Zaheer M, Hussain W, Hussain H, Muhammad Iqbal S, Ullah H (2022) Exploration and development of Shale gas in China: a review. Iran J Earth Sci 14(2):87–103. https://doi.org/10.30495/ijes.2022.1940263.1652
Ali N, Chen J, Fu X, Hussain W, Ali M, Hussain M, Anees A, Rashid M, Thanh HV (2022a) Prediction of Cretaceous reservoir zone through petrophysical modeling: insights from Kadanwari gas field, Middle Indus Basin GeosystGeoenviron 100058https://doi.org/10.1016/j.geogeo.2022.100058
Ali N, Chen J, Fu X, Hussain W, Ali M, Iqbal SM, Anees A, Hussain M, Rashid M, Thanh HV (2022b) Classification of reservoir quality using unsupervised machine learning and cluster analysis: example from Kadanwari gas field, SE Pakistan GeosystGeoenviron 100123https://doi.org/10.1016/j.geogeo.2022.100123
Al-Jawad SN, Saleh AH (2020) Flow units and rock type for reservoir characterization in carbonate reservoir: case study, south of Iraq. J Pet Explor Prod Technol 10(1):1–20. https://doi.org/10.1007/s13202-019-0736-4
Amanipoor H (2013) Providing a subsurface reservoir quality maps in oil fields by geostatistical methods. Geod Cartogr 39(4):145–148. https://doi.org/10.3846/20296991.2013.859779
Anyiam OA, Andrew PJ, Okwara IC (2017) Assessment of the heterogeneity and petrophysical evaluation of reservoirs in the “Akbar Field”, Niger Delta, Nigeria. J Pet Explor Prod Technol 7(4):1035–1050. https://doi.org/10.1007/s13202-017-0361-z
Asquith GB (1990) Log evaluation of shaly sandstone reservoirs: a practical guide. Am Assoc Pet Geol. https://doi.org/10.1306/CE31507
Asquith GB, Krygowski D, Gibson CR (2004) Basic well log analysis, vol 16. The American Association of Petroleum Geologists, Tulsa, Oklahoma Publishers
Azeem T, Chun WY, Khalid P, Qing LX, Ehsan MI, Munawar MJ, Wei X (2017) An integrated petrophysical and rock physics analysis to improve reservoir characterization of Cretaceous sand intervals in Middle Indus Basin, Pakistan. J Geophys Eng 14(2):212–225. https://doi.org/10.1088/1742-2140/14/2/212
Bou-Hamdan KF, Abbas AH (2021) Utilizing ultrasonic waves in the investigation of contact stresses, areas, and embedment of spheres in manufactured materials replicating proppants and brittle rocks Arab J Sci Eng 1–16https://doi.org/10.1007/s13369-021-06409-6
Bou-Hamdan KF (2022) Applications of nanomaterials in the oil and gas industry. In Handbook of Research on Green Synthesis and Applications of Nanomaterials. IGI Global, pp. 173–198 https://doi.org/10.4018/978-1-7998-8936-6.ch008
Chongwain GM, Osinowo OO, Ntamak-Nida MJ, Nkoa EN (2017) Seismic attribute analysis for reservoir description and characterization of M-field, Douala Sub-Basin, Cameroon. Adv Petrol Explor Dev 15(1):1–10. https://doi.org/10.3968/10220
Clavier C, Hoyle W, Meunier D (1971) Quantitative interpretation of thermal neutron decay time logs: part I. Fundamentals and techniques. J Pet Technol 23(06):743–755
Cornish R (2007) Statistics: cluster analysis. Mathematics Learning Support Centre, Loughborough University 1–5
Divya D, Gopinath LR, Christy PM (2015) A review on current aspects and diverse prospects for enhancing biogas production in sustainable means. Renew Sustain Energy Rev 42:690–699. https://doi.org/10.1016/j.rser.2014.10.055
Donaldson EC, Tiab D (2004) Petrophysics: theory and practice of measuring reservoir rock and fluid transport properties, 4th edn. Elsevier Publisher. https://www.elsevier.com/books/petrophysics/tiab/978-0-12-803188-9
El-Din ES, Mesbah MA, Kassab MA, Mohamed IF, Cheadle BA, Teama MA (2013) Assessment of petrophysical parameters of clastics using well logs: the Upper Miocene in El-Wastani gas field, onshore Nile Delta, Egypt. Pet Explor Dev 40(4):488–494. https://doi.org/10.1016/S1876-3804(13)60062-2
El-Khadragy AA, Shazly TF, Ramadan M, El-Sawy MZ (2017) Petrophysical investigations to both Rudeis and Kareem formations, Ras Ghara oil field, Gulf of Suez, Egypt. Egypt J Pet 26(2):269–277. https://doi.org/10.1016/j.ejpe.2016.04.005
Ellis DV, Singer JM (2007) Well logging for earth scientists, vol 692. Springer Publisher. https://link.springer.com/book/10.1007/978-1-4020-4602-5
Elsheikh A, Setto I, Abdelhady AA (2021) Reservoir characterization and 3D modeling of the Aptian Alamein Formation in North Razzak area (North Western Desert, Egypt). J Afr Earth Sci 173:104039. https://doi.org/10.1016/j.jafrearsci.2020.104039
Eshimokhai S, Akhirevbulu OE (2012) Reservoir characterization using seismic and well logs data (a case study of Niger Delta). Ethiop J Environ Stud Manag 5(4):597–603. https://doi.org/10.4314/ejesm.v5i4.S20
Gibson CR (1982) Basic well log analysis for geologists. American Association of Petroleum Geologists Publisher
Gogoi T, Chatterjee R (2019) Estimation of petrophysical parameters using seismic inversion and neural network modeling in Upper Assam basin, India. Geosci Front 10(3):1113–1124. https://doi.org/10.1016/j.gsf.2018.07.002
Gunter GW, Finneran JM, Hartmann DJ, Miller JD (1997) Early determination of reservoir flow units using an integrated petrophysical method. SPE Annu Tech Conf Exhibition. https://doi.org/10.2118/38679-MS
Hakimi MH, Al Qadasi BA, Al Sharrabi Y, Al Sorore OT, Al Samet NG (2017) Petrophysical properties of Cretaceous clastic rocks (Qishn Formation) in the Sharyoof oilfield, onshore Masila Basin, Yemen. Egypt J Pet 26(2):439–455. https://doi.org/10.1016/j.ejpe.2016.06.004
Hong-bo LI, Meijun WTLI (2013) Tracing study on oil-gas filling pathways of Yakela gas condensate field in Tabei uplift. Acta Petrolei Sinica 34(2):219–224. https://doi.org/10.7623/syxb201302002
Hossain S, Junayed TR, Haque AKM (2022) Rock physics diagnostics and modelling of the Mangahewa Formation of the Maui B gas field, Taranaki Basin, offshore New Zealand. Arab J Geosci 15(13):1–21. https://doi.org/10.1007/s12517-022-10436-4
Huang C, Yang B, Zhao X-S (2010) Log interpretation of reservoir parameters and reservoir evaluation for Yageliemuzu Formation in Yakela Gasfield. Xinjiang oil & gas, 4
Hussain M, Liu S, Ashraf U, Ali M, Hussain W, Ali N, Anees A (2022a) Application of machine learning for lithofacies prediction and cluster analysis approach to identify rock type. Energies 15(12):4501. https://doi.org/10.3390/en15124501
Hussain W, Ali N, Sadaf R, Hu C, Nykilla EE, Ullah A, Iqbal SM, Hussain A, Hussain S (2022b) Petrophysical analysis and hydrocarbon potential of the Lower Cretaceous Yageliemu Formation in Yakela gas condensate field, Tarim Basin, China Geosyst Geoenviron 100106https://doi.org/10.1016/j.geogeo.2022.100106
Iqbal SM, Hussain A, Ali N, Hussain W, Hussain H, Hussain S, Shah SYA, Nyakilla EE (2022) Experimental evaluation of different influencing parameters on cutting transport performance (CTP) in deviated wells GeosystGeoenviron 100110https://doi.org/10.1016/j.geogeo.2022.100110
Islam A, Habib MA, Islam MT, Mita MR (2013) Interpretation of wireline log data for reservoir characterization of the Rashidpur Gas Field, Bengal Basin, Bangladesh. IOSR J Appl Geol Geophys 1(4):47–54. https://doi.org/10.9790/0990-0144754
Jumaah HA (2021) Modified Archie’s parameters for estimating water saturation for carbonate reservoir in north of Iraq J Pet Explor Prod Technol 1–9https://doi.org/10.1088/1742-2140/aa805c
Kamel MH, Mabrouk WM (2003) Estimation of shale volume using a combination of the three porosity logs. J Petrol Sci Eng 40(3–4):145–157. https://doi.org/10.1016/S0920-4105(03)00120-7
Krygowski DA, Cluff RM (2015) Pattern recognition in a digital age: a gameboard approach to determining petrophysical parameters. In: SPWLA 56th annual logging symposium. OnePetro
Kumar R, Das B, Chatterjee R, Sain K (2016) A methodology of porosity estimation from inversion of post-stack seismic data. J Nat Gas Sci Eng 28:356–364. https://doi.org/10.1016/j.jngse.2015.12.028
Kurniawan F (2005) Shaly sand interpretation using CEC-dependent petrophysical parameters. https://doi.org/10.31390/gradschool_dissertations.2384
Li H, Wang Z, Xu F, Jin K, Wangning (2019) Characteristics of shale gas reservoir in Micangshan Uplift, Northern Margin of Sichuan Basin Unconv Oil Gas 6https://doi.org/10.1260/0144-5987.31.2.187
Li M, Wang T-G, Li H, Fang R, Yang L, Shi S, Kuang J (2016) Occurrence and geochemical significance of phenylnaphthalenes and terphenyls in oils and condensates from the Yakela Faulted Uplift, Tarim Basin, Northwest China. Energy Fuel 30:4457–4466. https://doi.org/10.1021/acs.energyfuels.5b02697
Mbaga DE, Mwendenusu G (2019) Effect of shale volume on the porosity of clastic reservoirs. Case-study from Mkuki-1 Reservoir, Offshore Tanzania. Fifth Int Conf Fault Top Seals 2019(1):1–5. https://doi.org/10.3997/2214-4609.201902303
Ming C, Yongfu L, Yunhong L, Qi S, Siyu Z, Jun J (2021) Provenance analysis of Cretaceous Yageliemu Formation in the Yangta 11 well block, Tarim Basin# br. China Pet Explor 26(2):77. https://doi.org/10.1080/08120099.2019.1661285
Mjili AS, Mulibo GD (2018) Petrophysical analysis of reservoirs rocks at Mchungwa well in Block 7 offshore, Tanzania: geological implication on the reservoir quality. Open J Geol 8(8):764–780. https://doi.org/10.4236/ojg.2018.88045
Naeem M, Jafri MK, Moustafa SSR, AL-Arifi NS, Asim S, Khan F, Ahmed N (2016) Seismic and well log driven structural and petrophysical analysis of the Lower Goru Formation in the Lower Indus Basin, Pakistan. Geosci J 20(1):57–75. https://doi.org/10.1007/s12303-015-0028-z
Orji CS, Uko ED, Tamunobereton-ari I (2019) Permeability-porosity trends in CAWC reservoir sands in the Niger Delta Nigeria, using well-log data. Malaysian J Geosci (MJG) 3(2):33–42. https://doi.org/10.26480/mjg.02.2019.33.42
Paul WJ (2012) Petrophysics. Dept. of Geology and Petroleum Geology, University of Aberdeen
Pigott JD, Williams MT, Abdel-Fattah M, Pigott KL (2014) The Messinian Mediterranean crisis: a model for the Permian Delaware Basin? AAPG International Conference and Exhibition, Istanbul, Turkey
Qadri SMT, Islam MA, Shalaby MR (2019) Application of well log analysis to estimate the petrophysical parameters and evaluate the reservoir quality of the Lower Goru Formation, Lower Indus Basin, Pakistan. Geomech Geophys Geo-Energy Geo-Resour 5(3):271–288. https://doi.org/10.1007/s40948-019-00112-5
Qiang Y (2012) Reservoir comprehensive classification and evaluation research of Yageliemu formation in YK gas reservoir. Pet Geol Eng 2
Qiao Y, An H (2007) Study of petrophysical parameter sensitivity from well log data. Appl Geophys 4(4):282–287. https://doi.org/10.1007/s11770-007-0038-3
Saadu YK, Nwankwo CN (2018) Petrophysical evaluation and volumetric estimation within Central swamp depobelt, Niger Delta, using 3-D seismic and well logs. Egypt J Pet 27(4):531–539. https://doi.org/10.1016/j.ejpe.2017.08.004
Saboorian-Jooybari H (2017) A structured mobility-based methodology for quantification of net-pay cutoff in petroleum reservoirs. SPE Reservoir Eval Eng 20(02):317–333. https://doi.org/10.2118/183643-PA
Salman SM, Bellah S (2009) Rock typing: An integrated reservoir characterization tool to construct a robust geological model in Abu Dhabi carbonate oil field. SPE/EAGE Reservoir Characterization & Simulation Conference, cp-170. https://doi.org/10.2118/125498-MS
Shah MS, Khan MHR, Rahman A, Islam MR, Ahmed SI, Molla MI, Butt S (2021) Petrophysical evaluation of well log data for reservoir characterization in Titas gas field, Bangladesh: a case study J Nat Gas SciEng 104129https://doi.org/10.1016/j.jngse.2021.104129
Stundner M, Oberwinkler C (2004) Self-organizing maps for lithofacies identification and permeability prediction. SPE Annu Tech Conf Exhibition
Timur A (1968) An investigation of permeability, porosity, and residual water saturation relationships. In: SPWLA 9th annual logging symposium. OnePetro
Xu K, Tian J, Yang H, Zhang H, Ju W, Liu X, Wang Z, Fang L (2022) Effects and practical applications of present-day in-situ stress on reservoir quality in ultra-deep layers of Kuqa Depression, Tarim Basin, China. J Nat Gas Geosc. https://doi.org/10.1016/j.jnggs.2022.04.002
Yu X, Ma YZ, Psaila D, La Pointe P, Gomez E, Li S (2011) Reservoir characterization and modeling: a look back to see the way forwardhttps://doi.org/10.1306/13301421M963458
Zhong H, He Y, Yang E, Bi Y, Yang T (2022) Modeling of microflow during viscoelastic polymer flooding in heterogenous reservoirs of Daqing Oilfield. J Petrol Sci Eng 210:110091. https://doi.org/10.1016/j.petrol.2021.110091
Zinszner B, Pellerin F-M (2007) A geoscientist’s guide to petrophysics. Editions Technip
Acknowledgements
I am thankful to Dr. Izhar Sadiq (Ocean College, Zhejiang University, People’s Republic of China) for reading and commenting on the manuscript, which helped improve the article.
Funding
The authors wish to thank the fluid flow lab of Faculty Earth Resources and School Oil and the Gas Engineering Department, China University of Geosciences, Wuhan, for the financial support that made this work possible.
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Highlights
• Well-log data are used to characterize the Lower Cretaceous Yageliemu Formation.
• The range of effective porosity has been calculated as 4.5–10%.
• Permeability is 0.5–18 mD, recognizing the well-sorted nature of sand.
• Hydrocarbon saturation in the respective zones is 41 to 50%.
• The Yageliemu Formation reservoir can produce a considerable amount of hydrocarbon.
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Hussain, W., Pan, L., Wang, X. et al. Evaluation of unconventional hydrocarbon reserves using petrophysical analysis to characterize the Yageliemu Formation in the Yakela gas condensate field, Tarim Basin, China. Arab J Geosci 15, 1635 (2022). https://doi.org/10.1007/s12517-022-10902-z
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DOI: https://doi.org/10.1007/s12517-022-10902-z