A Comprehensive Review for Integrating Petrophysical Properties, Rock Typing, and Geological Modeling for Enhanced Reservoir Characterization
Main Article Content
Abstract
Reservoir characterization is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling. This comprehensive research paper delves into the complex interplay of rock materials, rock formation techniques, and geological modeling techniques for improving reservoir quality. The research plays an important role dominated by petrophysical factors such as porosity, shale volume, water content, and permeability—as important indicators of reservoir properties, fluid behavior, and hydrocarbon potential. It examines various rock cataloging techniques, focusing on rock aggregation techniques and self-organizing maps (SOMs) to identify specific and anomalous rock faces. Furthermore, the paper explores the adoption of advanced methods, including hydraulic flow units (HFU), providing a fine-grained understanding of reservoir heterogeneity and contributing to the prediction of flow dynamics. The final section includes structural geological models, petrophysical data collected, rock type classification, and spatial data to better represent the reservoir bottom structure. It provides a valuable resource for researchers, geologists, and engineers seeking to characterize reservoirs and make optimal decisions on hydrocarbon exploration and production. It is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling.
Article Details
Section
How to Cite
References
Abdallah, W., Ali, F., Valori, A. and Ma, S., 2023. Extracting continuous profiles of archie parameters from downhole measurements. In: Middle East Oil, Gas and Geosciences Show. OnePetro. https://doi.org/10.2118/213947-MS
Abdul-majeed, Y.N., Ramadhan, A.A. and Mahmood, A.J., 2020. Petrophysical properties and well log interpretations of tertiary reservoir in khabaz oil field/northern iraq. Journal of Engineering, 26(6), pp.18–34. http://doi.org/10.31026/j.eng.2020.06.02.
Abdulkareem, A.N., Hussien, M.Y. and Hasan, H., 2020. Evaluation of petrophysical properties of zubair formation luhais oil field using well logging analysis and archie parameters. Journal of Engineering, 26(3), pp.145–159. http://doi.org/10.31026/j.eng.2020.03.12.
Abed, A.A. and Hamd-Allah, S.M., 2019. Comparative permeability estimation method and identification of rock types using cluster analysis from well logs and core analysis data in tertiary carbonate reservoir-khabaz oil field. Journal of Engineering, 25(12), pp.49–61. http://doi.org/10.31026/j.eng.2019.12.04.
Abudeif, A.M., Attia, M.M. and Radwan, A.E., 2016. Petrophysical and petrographic evaluation of sidri member of belayim formation, badri field, gulf of suez, egypt. Journal of African Earth Sciences, 115, pp.108–120. http://doi.org/10.1016/j.jafrearsci.2015.11.028.
Adeoti, L., Ayolabi, E.A. and James, P.L., 2009. An integrated approach to volume of shale analysis: niger delta example, Orire Field.
Adisoemarta, P.S., Anderson, G.A., Frailey, S.M. and Asquith, G.B., 2001. Saturation exponent n in well log interpretation: another look at the permissible range. In: SPE Permian Basin Oil and Gas Recovery Conference. SPE. p.SPE-70043. http://doi.org/10.2118/70043-MS.
Ahmed, R. and Farman, G.M., 2023a. How to estimate the major petrophysical properties: a review. Iraqi Journal of Oil and Gas Research (IJOGR), 3(1), pp.43–58. http://doi.org/10.55699/ijogr.2023.0301.1037.
Ahmed, R. and Farman, G.M., 2023b. Evaluating petrophysical properties of sa’di reservoir in halfaya oil field. Iraqi Geol. J., pp. 118–126. https://doi.org/10.46717/igj.56.2D.9ms-2023-10-15.
Akbar, M.N., 2019. New approaches of porosity-permeability estimations and quality factor q characterization based on sonic velocity, critical porosity, and rock typing. In: SPE Annual Technical Conference and Exhibition. OnePetro. http://doi.org/10.2118/199777-STU.
Al-Dhafeeri, A.M. and Nasr-El-Din, H.A., 2007. Characteristics of high-permeability zones using core analysis, and production logging data. Journal of Petroleum Science and Engineering, 55(1–2), pp.18–36. http://doi.org/10.1016/j.petrol.2006.04.019.
Al-Hilali, M.M., Zein Al-Abideen, M.J., Adegbola, F., Li, W. and Avedisian, A.M., 2015. A petrophysical technique to estimate archie saturation exponent (n); case studies in carbonate and shaly-sand reservoirs–iraqi oil fields. In: SPE Annual Caspian Technical Conference. SPE. p.SPE-177331. http://doi.org/10.2118/177331-MS.
Al-Mudhafar, W.J., 2018. Multiple–point geostatistical lithofacies simulation of fluvial sand–rich depositional environment: a case study from zubair formation/south rumaila oil field. SPE Reservoir Evaluation & Engineering, 21(01), pp.39–53. http://doi.org/10.2118/187949-PA.
Al-Ofi, S., Ma, S., Kesserwan, H. and Jin, G., 2022. A new approach to estimate archie parameters m and n independently from dielectric measurements. In: SPWLA Annual Logging Symposium. SPWLA. p.D031S004R002. http://doi.org/10.30632/SPWLA-2022-0002.
Alameedy, U., Farman, G.M. and Al-Tamemi, H., 2023. Mineral inversion approach to improve ahdeb oil field’s mineral classification. The Iraqi Geological Journal, pp.102–113. http://doi.org/10.46717/igj.56.2B.8ms-2023-8-17.
Ali, H.Y., Farman, G.M. and Hafiz, M.H., 2021. Study of petrophysical properties of the yamama formation in siba oilfield. Iraqi Geological Journal, 54(2), pp.39–47. http://doi.org/10.46717/IGJ.54.2C.4MS-2021-09-23.
Almazroui, M., Saeed, S., Saeed, F., Islam, M.N. and Ismail, M., 2020. Projections of precipitation and temperature over the south asian countries in cmip6. Earth Systems and Environment, 4, pp.297–320. http://doi.org/10.1007/s41748-020-00157-7.
Alqassab, H. and Vaughan, L., 2012. Impact of facies modeling on reservoir performance forecasting: a comparison between discrete modeling and mixed lithology approaches. In: SPE Kuwait International Petroleum Conference and Exhibition. SPE. p.SPE-163293. http://doi.org/10.2118/163293-MS.
Aquino-López, A., Mousatov, A., Markov, M. and Kazatchenko, E., 2015. Modeling and inversion of elastic wave velocities and electrical conductivity in clastic formations with structural and dispersed shales. Journal of Applied Geophysics, 116, pp.28–42. http://doi.org/10.1016/j.jappgeo.2015.02.013.
Archie, G.E., 1950. Introduction to petrophysics of reservoir rocks, AAPG bulletin,. http://doi.org/10.1306/3D933F62-16B1-11D7-8645000102C1865D.
Bassiouni, Z., 1994. Theory, measurement, and interpretation of well logs. doherty memorial fund of aime, society of petroleum engineers.
Bateman, R.M., 2020. Formation evaluation with pre-digital well logs. Elsevier.
Bhatti, A.A., Ismail, A., Raza, A., Gholami, R., Rezaee, R., Nagarajan, R. and Saffou, E., 2020. Permeability prediction using hydraulic flow units and electrofacies analysis. Energy Geoscience, 1(1–2), pp.81–91. http://doi.org/10.1016/j.engeos.2020.04.003.
Bose, S., Myers, M.T., Chen, P. and Thakur, G., 2019. Application of an integrated petrophysical modeling to improve log based reservoir characterization and oil in-place estimate of a fresh water shaly sand reservoir. In: SPWLA Annual Logging Symposium. SPWLA. p.D053S018R003. http://doi.org/10.30632/T60ALS-2019_DDDDD.
Burke, J.A., Campbell, R.L. and Schmidt, A.W., 1969. The litho-porosity cross plot a method of determining rock characteristics for computation of log data. in SPE Illinois Basin Regional Meeting. http://doi.org/10.2118/2771-MS.
Burke, J.A., Campbell, R.L. and Schmidt, A.W., 1969. The litho-porosity cross plot a method of determining rock characteristics for computation of log data. In: SPE Illinois Basin Regional Meeting. OnePetro. http://doi.org/10.2118/2771-MS.
Burns, A.H.C.R.E.P.S., 2013. Gas shale characterization - results of the mineralogical, lithological and geochemical analysis of cuttings samples from radioactive silurian shales of a palaeozoic basin, SW Algeria. Paper presented at the North Africa Technical Conference and Exhibition, Cairo, Egypt. http://doi.org/10.2118/164695-MS.
Cannon, S., 2015. Petrophysics: a practical guide. John Wiley & Sons.
Chen, H., Sarili, M., Wang, C., Naito, K., Morikami, Y., Shabibi, H., Frese, D. and Pfeiffer, T., 2020. Calibrated formation water resistivity sensor. In: SPWLA Annual Logging Symposium. SPWLA. p.D083S008R003. http://doi.org/10.30632/SPWLA-5021.
Cornish, R., 2007. Statistics: cluster analysis. Mathematics Learning Support Centre, 3, pp.1–5.
Díaz, G., Mendez, F., Alarcon, N., Paris, M., Lopez, A. and Gade, S., 2016, June. Comparative study of pulsed-neutron derived openhole and casedhole lithology, mineralogy and total organic carbon in unconventional reservoir. In SPWLA Annual Logging Symposium (pp. SPWLA-2016). SPWLA.
Doveton, J.H., 1994. Geologic log analysis using computer methods. Canadian Society of Petroleum Geologists. http://doi.org/10.1306/CA2580.
Ferguson, G.J., Willis, J.J., McIntosh Jr, D.S., Zwennes, J.W., Pasley, J. and Goettel, G.M., 2018. Influence of shale distribution types on the effective porosity of sandstone reservoirs: Gulf Coast Association of Geological Societies Transactions, 67.
Hamada, G.M., 1996. An integrated approach to determine shale volume and hydrocarbon potential in shaly sand. in SCA International Symposium.
Hosseini, E., Gholami, R. and Hajivand, F., 2019. Geostatistical modeling and spatial distribution analysis of porosity and permeability in the Shurijeh-b reservoir of Khangiran gas field in Iran. Journal of Petroleum Exploration and Production Technology, 9(2), pp.1051–1073.
Hossin, A., 1965. Feature article calculation of useful porosity in shaly sandstones. In: SPWLA Annual Logging Symposium. SPWLA. p.SPWLA-1965.
Hussein, R.A.M. and Ahmed, M.E.B., 2012. Petrophysical evaluation of shaly sand reservoirs in Palouge-fal oilfield, melut basin, south east of Sudan. Journal of science and technology, 13(2).
Ing. R. S. Rudi Rubiandini, 2008. Extended reach drilling ERD design in deepwater application. Paper presented at the IADC/SPE Asia Pacific Drilling Technology Conference and Exhibition, Jakarta, Indonesia,. http://doi.org/10.2118/115286-MS.
Al Jawad, M.S. and Tariq, B.Z., 2019. Estimation of cutoff values by using regression lines method in mishrif reservoir/missan oil fields. Journal of Engineering, 25(2), pp.82–95. http://doi.org/10.31026/j.eng.2019.02.06.
Kamel, M.H. and Mohamed, M.M., 2006. Effective porosity determination in clean/shaly formations from acoustic logs with applications. Journal of Petroleum Science and Engineering, 51(3–4), pp.267–274. http://doi.org/10.1016/j.petrol.2006.01.007.
Al Kattan, W., Jawad, S.N.A.L. and Jomaah, H.A., 2018. Cluster analysis approach to identify rock type in tertiary reservoir of khabaz oil field case study. Iraqi Journal of Chemical and Petroleum Engineering, 19(2), pp.9–13.
Kennedy, D., 2016. Conducting connected porosity: a concept for unifying resistivity-porosity models. Paper presented at the SPWLA 57th Annual Logging Symposium, Reykjavik, Iceland.
Kennedy, D. and Garcia, F., 2019. Tutorial: introduction to resistivity principles for formation evaluation: a tutorial primer. Petrophysics, 60(02), pp.208–227. http://doi.org/10.30632/PJV60N2-2019t2.
Ko Ko Kyi, 2019. Petrophysical cutoff a touchy subject. presentation course published.
Kolodzie Jr, S., 1980. Analysis of pore throat size and use of the waxman-smits equation to determine ooip in spindle field, colorado. In: SPE Annual Technical Conference and Exhibition? SPE. p.SPE-9382. http://doi.org/10.2118/9382-MS.
Lorentzen, R.J., Naevdal, G., Valles, B., Berg, A.M. and Grimstad, A.-A., 2005. Analysis of the ensemble kalman filter for estimation of permeability and porosity in reservoir models. In: SPE Annual Technical Conference and Exhibition? SPE. p.SPE-96375. http://doi.org/10.2118/96375-MS.
Lucia, F.J., Kerans, C. and Jennings Jr, J.W., 2003. Carbonate reservoir characterization. Journal of Petroleum Technology, 55(06), pp.70–72. http://doi.org/10.2118/82071-JPT.
Mabrouk, W.M., Soliman, K.S. and Anas, S.S., 2013. New method to calculate the formation water resistivity (Rw). Journal of Petroleum science and Engineering, 104, pp.49–52. http://doi.org/10.1016/j.petrol.2013.03.010.
Mahdi, Z.A. and Farman, G.M., 2023a. A review on models for evaluating rock petrophysical properties. Iraqi Journal of Chemical and Petroleum Engineering, 24(1), pp.125–136. http://doi.org/10.31699/IJCPE.2023.1.14.
Mahdi, Z.A. and Farman, G.M., 2023b. Estimation of petrophysical properties for Zubair reservoir in Abu-Amood Oil field. Iraqi Geological Journal, 56(1), pp.32–39. http://doi.org/10.46717/igj.56.1B.3ms-2023-2-11.
Mahdi, Z.A. and Farman, G.M., 2023c.3D Geological Model for Zubair Reservoir in Abu-Amood Oil Field. Iraqi Geological Journal, 56(1b), pp. 40-50. http://doi.org/10.46717/igj.56.1B.4ms-2023-2-12.
Maignant, G. and Staccini, P., 2018. Statistical, Mapping and Digital Approaches in Healthcare. Elsevier.
Mamaseni, W.J., Naqshabandi, S.F. and Al-Jaboury, F.K., 2018. Petrophysical properties of the early cretaceous formations in the Shaikhan oilfield/northern Iraq. Earth Sciences Research Journal, 22(1), pp.45–52.
Mazzullo, S.J., Rieke, H.H. and Chilingarian, G. V, 1996. Carbonate reservoir characterization: A geologic-engineering analysis, part II. Elsevier.
Mihai, D. and Mocanu, M., 2015. Statistical considerations on the k-means algorithm. Annals of the University of Craiova-Mathematics and Computer Science Series, 42(2), pp.365–373.
Mohamad, A.M. and Hamada, G.M., 2017. Determination techniques of archie’s parameters: a, m and n in heterogeneous reservoirs. Journal of Geophysics and Engineering, 14(6), pp.1358–1367.
Najeeb, M., Kadhim, F.S. and Saed, G.N., 2020. Using different methods to predict oil in place in Mishrif Formation/Amara oil field. Iraqi Journal Chemical Petroleum Engineering, 21(1), pp.33–38. http://doi.org/10.31699/IJCPE.2020.1.5.
Najlaa Fathi Hasan, 2021., Evaluation of reservoir characterization with 3d modeling in Mishrif formation - Amara oil field, M.Sc. thesis, Petroleum Engineering, University of Baghdad.
Ngo, V.T., Lu, V.D., Nguyen, M.H., Hoang, T.M., Nguyen, H.M. and Le, V.M., 2015. A comparison of permeability prediction methods using core analysis data. In: SPE Reservoir Characterisation and Simulation Conference and Exhibition? SPE. p.D011S001R003. http://doi.org/10.2118/175650-MS.
Nielsen, A.A., 2009. Geostatistics and analysis of spatial data. Informatics and Mathematical Modelling, Technical University of Denmark, DTU, pp.7–12.
Osterloh, W.T., Mims, D.S. and Meddaugh, W.S., 2013. Probabilistic forecasting and model validation for the first-eocene large-scale pilot Steamflood, Partitioned Zone, Saudi Arabia and Kuwait. SPE Reservoir Evaluation & Engineering, 16(01), pp.97–116. http://doi.org/10.2118/150580-PA.
Paul, F. and Gaffney, W., 2003. The application of cutoffs in integrated reservoir studies. Society of Petroleum Engineers, 84387, pp.1–16. http://doi.org/10.2118/95428-PA.
Pickett, G.R., 1966. A review of current techniques for determination of water saturation from logs’. Journal of Petroleum Technology. http://doi.org/10.2118/1446-PA.
Pittman, E.D., 1992. Relationship of porosity and permeability to various parameters derived from mercury injection-capillary pressure curves for sandstone. AAPG bulletin, 76(2), pp.191–198. http://doi.org/10.1306/BDFF87A4-1718-11D7-8645000102C1865D.
Pius, T.O. and Olamigoke, O., 2020. Investigating the correlation between water saturation obtained from cased-hole saturation tool measurements and produced water cut in strong water drive reservoirs. In: SPE Nigeria Annual International Conference and Exhibition. OnePetro. http://doi.org/10.2118/203620-MS.
Policky, B.R. and Iverson, W.P., 1988. Water resistivity from spontaneous potential logs in the minnelusa formation, powder river basin, wyoming. In: SPE Rocky Mountain Petroleum Technology Conference/Low-Permeability Reservoirs Symposium. SPE. p.SPE-17516. http://doi.org/10.2118/17516-MS.
Porras, J.C., Barbato, R. and Salazar, D., 2001. Upscaling from core data to production: Closing the cycle. A Case Study in the Santa Barbara and Pirital Fields, Eastern Venezuela Basin. In: International Symposium of the SCA. Murrayfield, Edinburgh. pp.17–19.
Qiu, M. and Yi, J., 2023. Reservoir rock typing: integration of geological attributes and petrophysical properties: Case Study from Yamama Reservoir. In: SPE Gas & Oil Technology Showcase and Conference. SPE. p.D021S024R002. http://doi.org/10.2118/214247-MS.
Rezaee, M.R., Kadkhodaie-Ilkhchi, A. and Alizadeh, P.M., 2008. Intelligent approaches for the synthesis of petrophysical logs. Journal of Geophysics and Engineering, 5(1), pp.12–26. htttp://doi.org/10.1088/1742-2132/5/1/002.
Riazi, Z., 2018. Application of integrated rock typing and flow units identification methods for an iranian carbonate reservoir. Journal of petroleum science and engineering, 160, pp.483–497. http://doi.org/10.1016/j.petrol.2017.10.025.
Salem, H.S. and Chilingarian, G. V, 1999. The cementation factor of archie’s equation for shaly sandstone reservoirs. Journal of Petroleum Science and Engineering, 23(2), pp.83–93. http://doi.org/10.1016/S0920-4105(99)00009-1.
Salman, O., Al-Fatlawi, O. and Al-Jawad, S., 2023. Reservoir characterization and rock typing of carbonate reservoir in the southeast of iraq. Iraqi Geological Journal, 56(1), pp.221–237. http://doi.org/10.46717/igj.56.1A.17ms-2023-1-29.
Schön, 2015. Physical properties of rocks: fundamentals and principles of Petrophysics. Second Edition. Elsevier.
Shahi, M., Salehi, M.M. and Kamari, M., 2018. New correlation for estimation of cementation factor in asmari carbonate rock reservoirs. Egyptian journal of petroleum, 27(4), pp.663–669. http://doi.org/10.1016/j.ejpe.2017.10.002.
Shedid, S.A. and Saad, M.A., 2017. Comparison and sensitivity analysis of water saturation models in shaly sandstone reservoirs using well logging data. Journal of Petroleum Science and Engineering, 156, pp.536–545. http://doi.org/10.1016/j.petrol.2017.06.005.
Simandoux, P., 1963. Dielectric measurements on porous media, application to the measurements of water saturation: study of behavior of argillaceous formations. Revue de L’institut Francais du Petrole, 18(Supplementary Issue), pp.193–215.
Singh, K.H. and Joshi, R.M., 2020. Petro-physics and rock physics of carbonate reservoirs. Springer.
Skalinski, M. and Kenter, J.A.M., 2015. Carbonate petrophysical rock typing: integrating geological attributes and petrophysical properties while linking with dynamic behaviour. Geological Society, London, Special Publications, 406(1), pp.229–259. http://doi.org/10.1144/SP406.6.
Su, K., Barlet, P., Borgomano, J.V.M., Castets, M., Caillet, C., Okullo, R., Azevedo, C., Ferreira, F., Beele, M. and
Coelho, D., 2022. Short and long-term fracture permeability tests under stress on pre-salt low permeability carbonates after acid treatment or with proppants. In: Abu Dhabi International Petroleum Exhibition and Conference. SPE. p.D032S170R007. http://doi.org/10.2118/211404-MS.
Svirsky, D., Ryazanov, A., Pankov, M., Corbett, P.W.M. and Posysoev, A., 2004. Hydraulic flow units resolve reservoir description challenges in a siberian oil field. in: SPE Asia Pacific conference on integrated modelling for asset management. SPE. p.SPE-87056. http://doi.org/10.2118/87056-MS.
Taslimi, M., Kazemzadeh, E. and Kamali, M.R., 2008. Determining rock mass permeability in a carbonate reservoir, southern iran using hydraulic flow units and intelligent systems. in Tehran, Iran, Wseas International Conference On Geology And Seismology (Ges’ 08), Cambridge, Uk. http://doi.org/10.1111/j.1747-5457.2009.00435.x.
Wang, Y., Cao, Y., Song, G., Song, L., Yang, T. and Zhang, S., 2014. Analysis of petrophysical cutoffs of reservoir intervals with production capacity and with accumulation capacity in clastic reservoirs. Petroleum Science, 11, pp.211–219.
Winsauer, W.O., Shearin Jr, H.M., Masson, P.H. y and Williams, M., 1952. Resistivity of brine-saturated sands in relation to pore geometry. AAPG bulletin, 36(2), pp.253–277. http://doi.org/10.1306/3D9343F4-16B1-11D7-8645000102C1865D.
Yaming Zou; Wenling Liu; Hui Zhou; Shoujun Guan; Hanming Chen, 2013. A new implementation procedure of sequential gaussian simulation in stochastic seismic inversion. Paper presented at the 2013 SEG Annual Meeting, Houston, Texas. http://doi.org/10.1190/segam2013-0490.1.
Yarmohammadi, S., Kadkhodaie, A. and Shirzadi, A., 2013. Determination of hydraulic flow units in sandstone reservoirs by integration of petrophysical data, well logs and seismic inversion results. In: the Second Conference on Hydrocarbon Reservoirs and Related Industries, Tehran, Iran.
Zhang, Y., 2011. Introduction to geostatistics-course notes. Laramie: University of Wyoming, Department of Geology and Geophysics.