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Journal articles on the topic 'Well Log Analysis'

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Published: 4 June 2021

Last updated: 5 February 2022

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1

KOK, MUSTAFA VERSAN, BAHADIR GOKCAL, and GIZEM ERSOY. "Reservoir Analysis by Well Log Data." Energy Sources 27, no. 5 (2005): 399–404. http://dx.doi.org/10.1080/00908310490441791.

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2

Buoro, Alvaro Bueno, and João B. C. Silva. "Ambiguity analysis of well‐log data." GEOPHYSICS 59, no. 3 (1994): 336–44. http://dx.doi.org/10.1190/1.1443595.

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Ambiguity in a geophysical interpretation problem is the possibility of accepting more than one solution caused either by solution nonuniqueness or instability. Nonuniqueness is related to the existence of more than one solution regardless of the precision of observations. On the other hand, instability is related to the acceptance of different solutions producing data fittings within the expected observational errors. We studied the ambiguity in the inversion of well‐logging data using a method based on the analysis of a finite number of acceptable solutions, which are ordered, in the solutio

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3

Nguyen, Nha Xuan. "LITHOLOGY ANALYSIS PROGRAM BASED ON WELL LOG DATA." Science and Technology Development Journal 12, no. 6 (2009): 104–10. http://dx.doi.org/10.32508/stdj.v12i6.2259.

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So far lithological analysis based on well logging data has been has been carried out manually and its results have been plotted by Excel. Analytical results depend on subjective assessment and analytical process requires more time and labor. The paper is to present an automatical program for lithological analysis of well logging data and a program establishing graph of analytical results using AutoCAD and MapInfor software.

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4

Ashida, Yuzuru, and Akira Itoh. "Well log analysis by use of neural network." Journal of the Japanese Association for Petroleum Technology 61, no. 4 (1996): 300–310. http://dx.doi.org/10.3720/japt.61.300.

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5

Zou, Ying, and Laurence R. Bentley. "Time-lapse well log analysis, fluid substitution, and AVO." Leading Edge 22, no. 6 (2003): 550–66. http://dx.doi.org/10.1190/1.1587675.

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6

Hayat, Umar, Aamir Ali, Ghulam Murtaza, et al. "Classification of Well Log Data Using Vanishing Component Analysis." Pure and Applied Geophysics 177, no. 6 (2019): 2719–37. http://dx.doi.org/10.1007/s00024-019-02374-2.

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7

Robinson, Joseph E. "Correcting well-log information for computer processing and analysis." Computers & Geosciences 12, no. 4 (1986): 493–98. http://dx.doi.org/10.1016/0098-3004(86)90064-6.

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8

Sari, Tri Wulan, and Sujito Sujito. "LITHOLOGY INTERPRETATION BASED ON WELL LOG DATA ANALYSIS IN “JS” FIELD." Applied Research on Civil Engineering and Environment (ARCEE) 1, no. 01 (2019): 31–37. http://dx.doi.org/10.32722/arcee.v1i01.1955.

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Reservoir lithology types in a prospect zone of hydrocarbon can be known through well log data analysis, both qualitatively and quantitatively. Lithology interpretation based on qualitatively well log data analysis, has been successfully carried out by K-1 and K-3 well log data on JS Field, West Natuna basin, Riau Islands.Main focus of the research is types of lithology indicated by response the petrophysical well data log of Lower-Middle Miocene Arang Formation. Arang Formation was deposited immediately on top Barat formation and depositional environment in this formation is transitional mari

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9

Gairola, Gaurav S., and E. Chandrasekhar. "Heterogeneity analysis of geophysical well-log data using Hilbert–Huang transform." Physica A: Statistical Mechanics and its Applications 478 (July 2017): 131–42. http://dx.doi.org/10.1016/j.physa.2017.02.029.

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10

Hamdi, Z., M. S. Momeni, B. Meyghani, et al. "Oil well compressive strength analysis from sonic log; a case study." IOP Conference Series: Materials Science and Engineering 495 (June 7, 2019): 012077. http://dx.doi.org/10.1088/1757-899x/495/1/012077.

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11

Zhao, Hank, Natalie B. Givens, and Brad Curtis. "Thermal maturity of the Barnett Shale determined from well-log analysis." AAPG Bulletin 91, no. 4 (2007): 535–49. http://dx.doi.org/10.1306/10270606060.

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12

Hernandez-Martinez, Eliseo, Teresa Perez-Muñoz, Jorge X. Velasco-Hernandez, Armando Altamira-Areyan, and Luis Velasquillo-Martinez. "Facies Recognition Using Multifractal Hurst Analysis: Applications to Well-Log Data." Mathematical Geosciences 45, no. 4 (2013): 471–86. http://dx.doi.org/10.1007/s11004-013-9445-6.

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13

Mann, Ulrich, and Peter J. Müller. "Source rock evaluation by well log analysis (Lower Toarcian, Hils syncline)." Organic Geochemistry 13, no. 1-3 (1988): 109–19. http://dx.doi.org/10.1016/0146-6380(88)90031-9.

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14

S S, Paul, Okwueze ., E. E, and Udo K I. "Petrophysical Analysis of Well Logs for the Estimation of Oil Reserves in Southern Niger Delta." International Journal of Advanced Geosciences 6, no. 1 (2018): 145. http://dx.doi.org/10.14419/ijag.v6i1.11815.

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Gamma Ray log, Resistivity log, Density log, Micro-spherical focus log (MSFL), Deep Induction log (ILD) , Medium Induction log(ILM) and Spontaneous Potential (SP) log were collected for 2 wells in onshore Niger Delta. These insitu well logs were analyzed and interpreted. Porosity, permeability, water saturation, reservoir thickness and Shale volume were estimated for each hydrocarbon bearing zone delineated for each well. The parameters obtained were further analyzed and interpreted quantitatively to estimate the hydrocarbon potentials of each well. Twelve reservoir zones of interest (sand bod

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15

Zhang, Jia, Shiqing Cheng, Shiying Di, Zhanwu Gao, Rui Yang, and Pengliang Cao. "A Two-Phase Numerical Model of Well Test Analysis to Characterize Formation Damage in Near-Well Regions of Injection Wells." Geofluids 2021 (February 18, 2021): 1–15. http://dx.doi.org/10.1155/2021/6693965.

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Formation damage usually occurs in near-well regions for injection wells completed in offshore oilfields under the development of line drive patterns. However, current works on characterizing the damage by well test analysis were basically focused on using single-phase analogy to solve two-phase flow issues, resulting in errors on the diagnosis and interpretation of transient pressure data. In this paper, we developed a two-phase model to simulate the pressure transient behavior of a water injection well in a multiwell system. To solve the model more efficiently, we used the finite volume meth

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16

Amosu, Adewale, and Yuefeng Sun. "MinInversion: A Program for Petrophysical Composition Analysis of Geophysical Well Log Data." Geosciences 8, no. 2 (2018): 65. http://dx.doi.org/10.3390/geosciences8020065.

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17

Subhakar, D., and E. Chandrasekhar. "Reservoir characterization using multifractal detrended fluctuation analysis of geophysical well-log data." Physica A: Statistical Mechanics and its Applications 445 (March 2016): 57–65. http://dx.doi.org/10.1016/j.physa.2015.10.103.

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18

Chandrasekhar, E., and V. Eswara Rao. "Wavelet Analysis of Geophysical Well-log Data of Bombay Offshore Basin, India." Mathematical Geosciences 44, no. 8 (2012): 901–28. http://dx.doi.org/10.1007/s11004-012-9423-4.

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19

Inichinbia, Sonny, Peter O. Sule, Aminu L. Ahmed, Halidu Hamza, and Kolawole M. Lawal. "Petro physical analysis of among hydrocarbon field fluid and lithofaciesusing Well Log Data." IOSR Journal of Applied Geology and Geophysics 2, no. 2 (2014): 86–96. http://dx.doi.org/10.9790/0990-02218696.

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20

O.A, Omoregbe, Oloyede D.A, and Momoh H.N. "Volumetric Analysis and Characterization of D_7 Reservoir using Well log and Seismic Data." International Journal of Scientific and Research Publications (IJSRP) 10, no. 7 (2020): 68–79. http://dx.doi.org/10.29322/ijsrp.10.07.2020.p10308.

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21

Lomakina, N. Y., V. B. Belozerov, and N. V. Bukhanov. "Lithology evaluation of a Bazhenov formation reservoir using seismic and well log analysis." IOP Conference Series: Earth and Environmental Science 24 (January 1, 2015): 012047. http://dx.doi.org/10.1088/1755-1315/24/1/012047.

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22

Song, Man-Hyok, Kyong-Ho Li, and Song-Nam Kim. "Evaluation of periodicities and fractal characteristics by wavelet analysis of well log data." Computers & Geosciences 119 (October 2018): 29–38. http://dx.doi.org/10.1016/j.cageo.2018.05.002.

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23

Nasr, Maher, Jasmin Raymond, Michel Malo, and Erwan Gloaguen. "Geothermal potential of the St. Lawrence Lowlands sedimentary basin from well log analysis." Geothermics 75 (September 2018): 68–80. http://dx.doi.org/10.1016/j.geothermics.2018.04.004.

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24

Feng, Runhai. "Uncertainty analysis in well log classification by Bayesian long short-term memory networks." Journal of Petroleum Science and Engineering 205 (October 2021): 108816. http://dx.doi.org/10.1016/j.petrol.2021.108816.

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25

Feng, Runhai, Dario Grana, and Niels Balling. "Imputation of missing well log data by random forest and its uncertainty analysis." Computers & Geosciences 152 (July 2021): 104763. http://dx.doi.org/10.1016/j.cageo.2021.104763.

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26

Snyder, Donald D., and David B. Fleming. "Well logging—A 25‐year perspective." GEOPHYSICS 50, no. 12 (1985): 2504–29. http://dx.doi.org/10.1190/1.1441881.

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Developments in the field of well logging over the last 25 years are reviewed. Surface and borehole instrumentation have evolved significantly, taking advantage of modern digital and analog integrated circuits. Most open‐hole petroleum well logs are now recorded digitally. Digital logs are also frequently acquired in cased‐hole petroleum, mineral, and geotechnical applications. Nuclear well‐log measurements have become accepted and reliable. New measurements include borehole compensated density and neutron‐porosity, sidewall epithermal neutron‐porosity, and most recently litho‐density. The neu

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27

Baker, P. L. "Log analysis systems incorporating artificial intelligence techniques ? some examples." Exploration Geophysics 20, no. 2 (1989): 331. http://dx.doi.org/10.1071/eg989331.

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Artificial Intelligence (Al) systems have been used with some success in the areas of dipmeter interpretation, quantitative log interpretation and well-to-well correlation. A prototype expert system has been developed using a rule-based approach to lithology identification. Extensions of the system are now being considered to do mineral identification for the problem of mineral model construction for multi-mineral log interpretation algorithms.

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28

Escobar, Freddy-Humberto, Laura-Jimena Vega, and Luis-Fernando Bonilla. "Determination of well-drainage area for power-law fluids by transient pressure analysis." CT&F - Ciencia, Tecnología y Futuro 5, no. 1 (2012): 45–56. http://dx.doi.org/10.29047/01225383.214.

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Since conventional oil is almost depleted, oil companies are focusing their efforts on exploiting heavy oil reserves. A modern and practical technique using the pressure and pressure derivative, log-log plot for estimating the well-drainage area in closed and constant-pressure reservoirs, drained by a vertical well is presented by considering a non-Newtonian flow model for describing the fluid behavior. Several synthetic examples were presented for demonstration and verification purposes.Such fluids as heavy oil, fracturing fluids, some fluids used for Enhanced Oil Recovery (EOR) and drilling

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29

Nie, Xiang Rong, and Shi Qing Cheng. "Pressure Transient Analysis of Polymer Injection Wells." Advanced Materials Research 361-363 (October 2011): 370–76. http://dx.doi.org/10.4028/www.scientific.net/amr.361-363.370.

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Polymer solution is known as non-Newtonian Fluid. Hence, when a well is injected by polymer solution, the well test data analysis using Newtonian fluid flow model will be erroneous. However, the analysis results usually were inaccurate when generalized non-Newtonian fluid model which considering polymer solution as power law fluid and taking no account of physical and chemical behaviors. These results clearly suggest the need for a study to come up with a new model considering both physical and chemical behaviors when polymer solution flowing in the reservoirs. At first, this study modified tw

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30

Einstein, Elizabeth E., and Ken W. Edwards. "Comparison of an Expert System to Human Experts in Well-Log Analysis and Interpretation." SPE Formation Evaluation 5, no. 01 (1990): 39–45. http://dx.doi.org/10.2118/18129-pa.

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31

Feng, Runhai. "Improving uncertainty analysis in well log classification by machine learning with a scaling algorithm." Journal of Petroleum Science and Engineering 196 (January 2021): 107995. http://dx.doi.org/10.1016/j.petrol.2020.107995.

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32

Oluwatoyin, Ologe. "Reservoir evaluation of “T-X” field (Onshore, Niger delta) from well log petrophysical analysis." Bayero Journal of Pure and Applied Sciences 9, no. 2 (2017): 132. http://dx.doi.org/10.4314/bajopas.v9i2.25.

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33

Zong, Jingjing, Robert R. Stewart, Nikolay Dyaur, and Michael T. Myers. "Elastic properties of rock salt: Laboratory measurements and Gulf of Mexico well-log analysis." GEOPHYSICS 82, no. 5 (2017): D303—D317. http://dx.doi.org/10.1190/geo2016-0527.1.

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Rock salt (essentially halite) is a special type of sedimentary rock that has played a large role throughout tectonic and economic history. The unique physical properties of halite (ductility, low density, flowability, and impermeability) can be critical factors in hydrocarbon traps and underground storage. However, seismic imaging and interpretation can be challenging when salt structures are present due to their complex geometry and large impedance contrasts relative to surrounding rocks. To investigate the properties of rock salt in terms of elastic parameters, we use ultrasonic laboratory

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34

Esmailzadeh, Akbar, Sina Ahmadi, Reza Rooki, and Reza Mikaeil. "Oil Reservoir Permeability Estimation from Well Logging Data Using Statistical Methods (A Case Study: South Pars Oil Reservoir)." Civil Engineering Journal 3, no. 10 (2017): 831. http://dx.doi.org/10.28991/cej-030918.

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Permeability is a key parameter that affects fluids flow in reservoir and its accurate determination is a significant task. Permeability usually is measured using practical approaches such as either core analysis or well test which both are time and cost consuming. For these reasons applying well logging data in order to obtaining petrophysical properties of oil reservoir such as permeability and porosity is common. Most of petrophysical parameters generally have relationship with one of well logged data. But reservoir permeability does not show clear and meaningful correlation with any of log

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35

Grassinger, Julia Maria, Andreas Floren, Tobias Müller, et al. "Digital Lesions in Dogs: A Statistical Breed Analysis of 2912 Cases." Veterinary Sciences 8, no. 7 (2021): 136. http://dx.doi.org/10.3390/vetsci8070136.

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Breed predispositions to canine digital neoplasms are well known. However, there is currently no statistical analysis identifying the least affected breeds. To this end, 2912 canine amputated digits submitted from 2014–2019 to the Laboklin GmbH & Co. KG for routine diagnostics were statistically analyzed. The study population consisted of 155 different breeds (most common: 634 Mongrels, 411 Schnauzers, 197 Labrador Retrievers, 93 Golden Retrievers). Non-neoplastic processes were present in 1246 (43%), tumor-like lesions in 138 (5%), and neoplasms in 1528 cases (52%). Benign tumors (n = 335

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36

Imran, Qazi Sohail, Numair Ahmad Siddiqui, Abdul Halim Abdul Latif, Yasir Bashir, Almasgari Abdalsalam Abduh Saeed Ali, and Muhammad Jamil. "Integrated Well Data And 3D Seismic Inversion Study For Reservoir Delineation And Description." Bulletin Of The Geological Society Of Malaysia 70, no. 1 (2020): 209–20. http://dx.doi.org/10.7186/bgsm70202016.

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Offshore petroleum systems are often very complex and subtle because of a variety of depositional environments. Characterizing a reservoir based on conventional seismic and well-log stratigraphic analysis in intricate settings often leads to uncertainties. Drilling risks, as well as associated subsurface uncertainties can be minimized by accurate reservoir delineation. Moreover, a forecast can also be made about production and performance of a reservoir. This study is aimed to design a workflow in reservoir characterization by integrating seismic inversion, petrophysics and rock physics tools.

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37

Leem, Kook-Mook, Jong-Oh Park, Young-Chul Yu, and Moo-Young Song. "Geophysical Well-log Analysis of Andesite and Sedimentary Rocks in Myodo-dong, Yeosu, Southern Korea." Journal of the Korean earth science society 30, no. 4 (2009): 401–8. http://dx.doi.org/10.5467/jkess.2009.30.4.401.

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38

Siregar, Irdian, Yufu Niu, Peyman Mostaghimi, and Ryan T. Armstrong. "Coal ash content estimation using fuzzy curves and ensemble neural networks for well log analysis." International Journal of Coal Geology 181 (August 2017): 11–22. http://dx.doi.org/10.1016/j.coal.2017.08.003.

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39

Al-Areeq, Nabil M., and Abdulwahab S. Alaug. "Well log analysis and hydrocarbon potential of the Sa'ar–Nayfa reservoir, Hiswah Oilfield, eastern Yemen." Arabian Journal of Geosciences 7, no. 7 (2013): 2941–56. http://dx.doi.org/10.1007/s12517-013-1003-5.

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40

Grana, Dario, Marco Pirrone, and Tapan Mukerji. "Quantitative log interpretation and uncertainty propagation of petrophysical properties and facies classification from rock-physics modeling and formation evaluation analysis." GEOPHYSICS 77, no. 3 (2012): WA45—WA63. http://dx.doi.org/10.1190/geo2011-0272.1.

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Formation evaluation analysis, rock-physics models, and log-facies classification are powerful tools to link the physical properties measured at wells with petrophysical, elastic, and seismic properties. However, this link can be affected by several sources of uncertainty. We proposed a complete statistical workflow for obtaining petrophysical properties at the well location and the corresponding log-facies classification. This methodology is based on traditional formation evaluation models and cluster analysis techniques, but it introduces a full Monte Carlo approach to account for uncertaint

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41

SAUCIER, ANTOINE, and JIRI MULLER. "USE OF MULTIFRACTAL ANALYSIS IN THE CHARACTERIZATION OF GEOLOGICAL FORMATIONS." Fractals 01, no. 03 (1993): 617–28. http://dx.doi.org/10.1142/s0218348x93000654.

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We use multifractal analysis as a tool for the characterization of geological well log signals. The signals investigated come from dipmeter microresistivity log devices. It is suggested that the multifractal spectra computed from these signals could be used to distinguish geological formations and lithofacies containing different types of oil reservoir heterogeneities.

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42

Essien, Ubong. "Shale volume and porosity delineation of coast swamp depobelt in Niger delta region, Nigeria, using well log." International Journal of Advanced Geosciences 7, no. 2 (2019): 142. http://dx.doi.org/10.14419/ijag.v7i2.29772.

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Well log data from two wells were evaluated for shale volume, total and effective porosity. Well log data were obtained from gamma ray, neutron-density log, resistivity, sonic and caliper log respectively. This study aimed at evaluating the effect of shale volume, total and effective porosity form two well log data. The results of the analysis depict the presence of sand, sand-shale and shale formations. Hydrocarbon accumulation were found to be high in sand, fair in sand-shale and low in shale, since existence of shale reduces total and effective porosity and water saturation of the reservoir

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43

Tang, Hong, Niall Toomey, and W. Scott Meddaugh. "Using an Artificial-Neural-Network Method To Predict Carbonate Well Log Facies Successfully." SPE Reservoir Evaluation & Engineering 14, no. 01 (2011): 35–44. http://dx.doi.org/10.2118/123988-pa.

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Summary The Maastrichtian (Upper Cretaceous) reservoir is one of five prolific oil reservoirs in the giant Wafra oil field. The Maastrichtian oil production is largely from subtidal dolomites at an average depth of 2,500 ft. Carbonate deposition occurred on a very gently dipping, shallow, arid, and restricted ramp setting that transitioned between normal marine conditions to restricted lagoonal environments. The average porosity of the reservoir interval is approximately 15%, although productive zones have porosity values up to 30–40%. The average permeability of the reservoir interval is appr

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44

Bintarto, Bambang, Rizky Rahmat Auliya, Riza Andhika Mahendra Putra, Afif Surya Pradipta, and Rafli Arie Kurnia. "Production Data Analysis and Sonolog for Determining Artificial Lift Design and Well Characteristic." Journal of Petroleum and Geothermal Technology 1, no. 1 (2020): 28. http://dx.doi.org/10.31315/jpgt.v1i1.3321.

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Tarakan Field, North Kalimantan is a part of PT. Pertamina EP Asset 5. The Tarakan Field has 5 structures in the form of Pamusian, Juata, Sesanip, Mangatal, and Sembakung. The Tarakan Field has 57 production wells and 6 injection wells. The wells at Tarakan field are produced with artificial lifts in the form of Sucker Rod Pump (SRP) totaling 25, Hydraulic Pumping Unit (HPU) totaling 11, Electric Submersible Pump (ESP) totaling 19 and Progressive Cavity Pump (PCP) totaling 2. The determination of artificial lifts is carried out by the design of well characteristics and production history. The

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45

Grigorash, Alexander, Siobhan O'Neill, Raymond Bond, Colette Ramsey, Cherie Armour, and Maurice D. Mulvenna. "Predicting Caller Type From a Mental Health and Well-Being Helpline: Analysis of Call Log Data." JMIR Mental Health 5, no. 2 (2018): e47. http://dx.doi.org/10.2196/mental.9946.

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Background This paper presents an analysis of call data records pertaining to a telephone helpline in Ireland among individuals seeking mental health and well-being support and among those who are in a suicidal crisis. Objective The objective of our study was to examine whether rule sets generated from decision tree classification, trained using features derived from callers’ several initial calls, could be used to predict what caller type they would become. Methods Machine learning techniques were applied to the call log data, and five distinct patterns of caller behaviors were revealed, each

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46

S Mulyanto, Bagus, Ordas Dewanto, and Sri Rizky. "Determining Layer Oil Shale as New Alternative Energy Sources Using Core Analysis and Well Log Method." International Journal of Engineering & Technology 7, no. 4.36 (2018): 941. http://dx.doi.org/10.14419/ijet.v7i4.36.24925.

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Oil shale is a type of shale containing organic material is not yet mature. When heated to a certain temperature, the organic content to mature so that it can produce petroleum. Exploration with a reliable method to energy sources of the future needs to be done, because it has a particularly important role in the context of the national energy supply security in the future. Oil deposits in shale oil is quite high, estimated as relatively large reserves spread across several regions of Indonesia. To determine the content of oil shale in the basin necessary to evaluate the condition of the reser

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47

Kumar, Atul, Mohd Haris Mohd Khir, and Wan Ismail Wan Yusoff. "A model-based approach for integration analysis of well log and seismic data for reservoir characterization." Geosciences Journal 20, no. 3 (2016): 331–50. http://dx.doi.org/10.1007/s12303-015-0045-y.

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48

Bueno, Juliana Finoto, Bruno César Zanardo Honório, Michelle Chaves Kuroda, Alexandre Campane Vidal, and Emilson Pereira Leite. "Structural and stratigraphic feature delineation and facies distribution using seismic attributes and well log analysis applied to a Brazilian carbonate field." Interpretation 2, no. 1 (2014): SA83—SA92. http://dx.doi.org/10.1190/int-2013-0087.1.

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Identification of structural and stratigraphic components within a hydrocarbon reservoir is essential for the construction of geologic models that represent the facies distribution as accurately as possible. Such construction may represent a challenge for ancient carbonate reservoirs, which exhibit greater heterogeneity than siliciclastic reservoirs. We developed a workflow that incorporated seismic attribute analysis and well log data to highlight structural and architectural elements with the benefit of the understanding the distribution of facies in this features in an Albian offshore carbo

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49

J. Sunday, Abe, and Lurogho S. Ayoleyi. "Petrophysical analysis of “explorer” wells using well log and core data(a case study of “explorer” field, offshore Niger Delta, Nigeria)." International Journal of Advanced Geosciences 8, no. 2 (2020): 219. http://dx.doi.org/10.14419/ijag.v8i2.31114.

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Reservoir characterization involves computing various petrophysical parameters and defining them in terms of their quantity and quality so as to ascertain the yield of the reservoir. Petrophysical well log and core data were integrated to analyze the reservoir characteristics of Explorer field, Offshore, Niger Delta using three wells. The study entails determination of the lithology, shale volume (Vsh), porosity (Φ), permeability (K), fluid saturation and cross plotting of petrophysical and core values at specific intervals to know their level of correlation. The analysis identified twelve hyd

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50

Alimohammadi, Davood, Ebrahim Analouei Adegani, Teodor Bulboacă, and Nak Eun Cho. "Logarithmic Coefficient Bounds and Coefficient Conjectures for Classes Associated with Convex Functions." Journal of Function Spaces 2021 (June 13, 2021): 1–7. http://dx.doi.org/10.1155/2021/6690027.

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It is well-known that the logarithmic coefficients play an important role in the development of the theory of univalent functions. If S denotes the class of functions f z = z + ∑ n = 2 ∞ a n z n analytic and univalent in the open unit disk U , then the logarithmic coefficients γ n f of the function f ∈ S are defined by log f z / z = 2 ∑ n = 1 ∞ γ n f z n . In the current paper, the bounds for the logarithmic coefficients γ n for some well-known classes like C 1 + α z for α ∈ 0 , 1 and C V hpl 1 / 2 were estimated. Further, conjectures for the logarithmic coefficients γ n for functions f belong

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