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  • 1. LOW RESISTIVITY LOW CONTRAST PAY OF CLASTIC RESERVOIRS WITH A STUDY CASE OF TERTIARY BASINS IN MALAYSIA By: Yulini ArediningsihI. Introduction This paper presents an overview of how petrophysical analysis applied in lowresistivity low contrast pay (LRLCP) in clastic reservoirs. The paper also reviews a studycase of low resistivity low contrast pay in some Tertiary basins in Malaysia. First chapterincludes historical background, some theoretical concepts on low resistivity low contrastpay. Second chapter presents geologic point of view on low resistivity low contrastformations, concepts on shaly sand and the causes related to low resistivity low contrastpay occurrence. Third chapter focuses on petrophysical analysis in evaluating typical payzones. The chapter also reviews problems in recognizing and evaluating low resistivitypay zones by well logs. In this part, contribution of NMR logging tool is brieflydiscussed. Fourth chapter mainly presents a LRLCP study case in Malaysian basins. Low resistivity low contrast pay (LRLCP) is a global challenging phenomenon information evaluation for over three decades, taking place in basins from the North Sea,Europe, Middle East, West Africa and Alaska to Malaysia, Indonesia and Australia(Boyd et al. 1995, Worthington, 2000). Problems of identifying low-resistivity pay in logdata have been recognized since first low resistivity low contrast formation discovered inTexas and Louisiana Gulf Coast of the United States (Tixier et al. 1968). Big numbers ofdocumented records of low resistivity low contrast pay fields worldwide have been listedbased on their causes in Worthington (2000). Low resistivity low contrast pay may not be 1
  • 2. identifiable through conventional log analysis. This may make it difficult to evaluate. Itspotentiality is often bypassed because of its over estimation on Sw values. “Low resistivity” refers to its characteristic of low value in deep resistivity logsranging from 0.5 to 5 ohm-m. The formations with such characteristics may occur insandstone and carbonates (Saha, 2003, Riepe et al, 2008), but they are described often insandstones, that mostly associated with thinly bedded low-resistivity shaly sandformations. The zones may have a combined resistivity only a few tenths of an ohm-mhigher than the adjacent shales. “Low contrast pay” is used as frequent concurrence withlow resistivity, indicating a lack of resistivity contrast between sands and adjacent shales(Fanini et al., 2001; Boyd at al. 1995). Inadequate vertical resolution of conventionalresistivity data that are applied to determine properties of the individual beds, makes thepotential intervals are difficult to distinguish from adjacent shales. Its potentiality isnormally underestimated or even bypassed, resulted by inadequate vertical resolution ofconventional resistivity data to determine the properties of the individual beds. The loganalysis gives high saturation as given by lower resistivity than would be obtained from athick, hydrocarbon bearing sandstone. The resistivity values noted earlier have evolved with time from initial range aslow as 1–3 ohm-m (Murphy and Owens, 1972) to less than 0.5 ohm-m (Boyd et al. 1995).This signifies that uncertain numbers of low-resistivity pay reservoirs have beendiscarded earlier over the years. Nowadays, there are no acceptable cut-off values givento the resistivity of economical pay zones (Worthington, 2000). 2
  • 3. II. Geologic Point of View on Low Resistivity Low Contrast Formations2.1 Characteristics Occurrence of high clay or shale within sand beds is considered as the majorcause of low-resistivity pay. Clay contribution to low-resistivity readings depends on thetype, volume and distribution of clay in the formation (Worthington, 1985). Othergeological causes of low resistivity low contrast pay include conductive minerals (such aspyrite), low salinity or fresh formation waters, grain size or pore size effects, bioturbationeffects (considerable bioturbated fine silts and shale), internal micro porosity andsuperficial micro porosity (Boyd et al, 1995; Worthington, 2000; Riepe et al, 2008). Saha(2003) also identifies that low resistivity low contrast pay can be brought about by deepinvasion by conductive mud, presence of fractures and capillary bound water, and highangle wells due to anisotropy effect.2.2 Basics on Shaly sands As pointed out earlier that occurrence of the high amount clay or shale withinsand beds, known as shaly sand, is considered as the major cause of low-resistivity pay.Problems in analysing and interpreting shaly-sand log data have challenged log analystsand petrophysicists since 1950. Numerous efforts have been made in developing morethan 30 shaly sand interpretation models in the last 60 years (Worthington, 1985).Difficulties in interpretation become apparent whenever clastic formations haveappreciable content of clays. Their presence in the formation may add up the overallconductivity. Their conductivity becomes as essential as the conductivity of the formation 3
  • 4. water (Worthington and Johnson, 1991). In fact, this also makes the shaly sand analysisbecomes complicated because of a wide variety of clay minerals and their distributionwithin the pore and rock structure. The analysis becomes more complex when conditionsof the shale content increases and the porosity and formation water salinity decreases.That explains the absence of a unique universally accepted approach to shaly sandanalysis (Worthington, 1985). Key parameters in hydrocarbon potential evaluation areporosity and water saturation. In a clay free formation comprising sand matrix, water,and gas, water saturation and porosity can be estimated accurately based well logdata using the Archie equation. Archie equation, the most renowned water saturationmodel, is empirically formulated, validated for sandstones that are free of clay mineralsand are (fully or partially) saturated with a high-salinity electrolyte (Archie, 1942). Theequation is expressed as : Sw n = R w φ m.Rt Where Sw = formation water saturation, fraction Rw = resistivity of formation water, ohm-m Rt = resistivity of formation rock, ohm-m φ = porosity, fraction n = saturation exponent m = cementation exponent The conditions for the Archie equation to relate resistivity solely to watersaturation no longer apply when clay is present significantly. The problem in analysingshaly sand formation is complicated by the difficulty of accurately estimating theshaliness from well log data. Slight changes, in the estimates of shaliness, can result inlarge changes in the derived values of saturation. Potentiality of formation bearing 4
  • 5. hydrocarbon is frequently underestimated, due to clay effect negligence, which giveshigher estimation in water saturation than the actual value. Therefore, when clay ispresent, the Archie equation must be modified to generate appropriate shaly sand modelsto compensate the effect of clay minerals on log response. Normally, the correctedequation will give more accurate results when more log data are available (Worthington,2005). Based on their different concept, the shaly-sand models can be divided into twomain groups: fractional volume of shale (Vsh) group and Cation Exchange Capacity(CEC) group. Simandoux model is commonly used in Vsh group while Waxman andSmits and Dual Water models are in Cation Exchange Capacity (CEC) group. The mainpitfall of Vsh models is that they disregard all aspects related to clay mineralogy such asdistribution, textures and composition of different clay types. These parametersessentially may give different shale effects for the same volume of shale fraction (Vsh).To tackle this problem, CEC models were developed, which consider electrochemicalproperties of clay mineral-electrolyte interfaces to produce more reliable models in shaly-sand interpretation. Terminology of “shale” and “clay” has been used synonymously in formationevaluation by log analysts or petrophysicists. In fact, in geologic term, they are different.Shale is a clastic sedimentary rock, composed of complex minerals. It is made up byalmost 60% of clay minerals and other constituents including minor amount clay to silt-sized grains of quartz, feldspar and other minerals (Blatt, 1982). In contrast, clay usuallyrefers to a grain size with diameter less than 0.004 mm. It may also refer toaluminosilicate minerals including illite, smectite, montmorillonite, chlorite, and 5
  • 6. kaolinite. Shaly sand itself, in simple terms, is clay rich sand or sandstone. It also can bedefined as sandstone in which quartz is present as the primary mineral, but clay and otherassociated minerals may be present in varying amounts, distributions, and particle sizes.When clay minerals are present in sandstone, type, volume, and distribution of the claywill affect the well log response to that sandstone (Worthington, 1985; Passey et al,2006). Increased volume of clay decreases the effective reservoir capacity. Concurrentlythe conductive clay may reduce the formation resistivity. It is a crucial task for thepetrophysicists to determine the effects of clay upon porosity, permeability and fluidsaturations. The clay minerals contained in sandstones can be from detrital origin ordiagenetic origin (Almon, 1977). The former is mainly present as discrete clay-sizeparticles to sand-size aggregates, and usually incorporated into the sandstones at orshortly after the time of deposition. The latter is naturally formed, mainly as clay cementthat develops after burial as product precipitation or recrystallization during diagenesis. As diagenetic or authigenic clays, they may occur as any of three types ofgrowths, shown in Figure 2.1. These authigenic clays are formed; mainly as disperse Figure 2.1. Formation of authigenic clays (Almon, 1979). 6
  • 7. materials throughout the pore system of the sandstones from the formation water or arethe products of the interaction between formation water and the mineral components ofthe rock, mainly within the sandstone pore system. Consequently, their occurrence canindicate the pore water chemistry at the time of clay mineral formation. Clay or shale in sandstones can also occur as laminar clay, structural clay anddisperse clay (Frost and Fertl, 1981) (Figure 2.2). Laminar shale can be present as detritalorigin, between clean sand layers. It tends to affect permeability and or porosity.Structural shale usually replaces matrix or detrital grains or feldspar. This type may notaffect porosity or permeability. Dispersed shale is usually formed as authigenic ordiagenetic origin spread throughout the sand. Volume and type of clay mineral maydetermine the degree of porosity and permeability reduction.Figure 2.2 Distribution of clays in relation to porosity volume (Frost, and Fertl, 1981)2.3 Geologic depositional environments Favourable stratigraphic settings of low resistivity pay are usually related tolaminated or thinly bedded sand-shale sequences. The most common depositionalenvironments associated with the low resistivity pays are shown in Figure 2.3. 7
  • 8. A. Low stand basin floor fan complexes B. Deep water levee- channel complexes and over bank deposits C. Transgressive marine sands D. Lower parts (toes) of delta front deposits and laminated silt-shales and intervals in the upper parts of alluvial and distributary channelsFigure 2.3 Model of the most common depositional environment of low resistivity lowcontrast pays (After Darling and Sneider, 1993 cited in Boyd et al 1995). 8
  • 9. In relation to deepwater environment, prospects of turbidite exploration aregeostatistically found to be worldwide at an undeveloped stage and provide a significantpart in the future projects of hydrocarbon exploration and production (Pettingill, 1998).For that reason, in general, it can be assumed that a noteworthy proportion of the world’sundiscovered hydrocarbon reserves is most likely associated with laminated, low-resistivity, low contrast, shaly sand formations (Fanini et al, 2001). Kuecher andMillington (2000) describe that turbidite sand deposits bearing low resistivity lowcontrast pay extend over a wide range of depositional energy environments. Typicalthinly bedded, laminar sands and shales are commonly found in the sub-systems ofchannel levee and over bank -levee environment and middle-to-distal fan complexes.They significantly contribute overall net pay and oil-in-place determination of mostdeepwater exploration plays as they are extremely prolific.III. Petrophysical Analysis of Low Resistivity Low Contrast Pay The challenge for interpreting low resistivity low contrast pay zones of thinlybedded shale-sand sequence focuses on estimating shaliness, extracting the correctresistivity measurement of formation and accurately deriving water saturation, Sw.Shaliness (clay volume) is typically calculated using appropriate shaly sand models,selected based on information of clay characteristics, types, compositions anddistribution, as discussed earlier. Improved vertical resolution of logging tools and dataprocessing techniques are essentially helpful in getting reliable resistivity data especiallyin the thin beds. 9
  • 10. Historically, in 1968 when Gulf Coast became a focus of frontier exploration inlow resistivity pay, their pay sands were not always noticeable on conventional resistivitylogs. Tixier et al. (1968) note that the pay sands commonly are high in porosity, claycontent but low Rw values. The finer-grain and silty sands are characterized by highirreducible water saturations. The clean water sands have resistivities ranging from 0.2 to1.0 ohm-meter; moreover shaliness increases this R value. Thus, identifying pay zoneswith only a resistivity log is often difficult. However, the problem can be resolved byresistivity logs combined with three porosity logs of density, sonic and neutron integratedwith SP and Gamma Ray curves, and sidewall samples. This implementation of thisintegrated logs and core data is beneficial in the study of shaly sands. Log evaluation in thin bedded sand-shale sequences is difficult because only bulkdensity and resistivity that are directly measured. Other important reservoir propertiesneed to be deduced using those two earlier properties. Other reasons are incapability oflogging tools to measure beds that are too thin to be measured individually andanisotropic petrophysical properties (Passey et al. 2006). The petrophysical techniques for evaluating low resistivity low contrast pay canbe grouped into two, namely low resolution and high resolution techniques. Othermethods include Nuclear Magnetic Resonance (NMR) and multi component induction. Inthe low-resolution techniques, properties of each individual thin bed are not necessarilyto be resolved, dissimilar to the high resolution techniques. NMR techniques are brieflydiscussed in the next section. A summary of those techniques especially applied in shaly-sand thin beds of low resistivity low contrast pay is given in Table 3.1, adapted fromreviews by Passey et al. (2006) and Hamada et al.(2001). 10
  • 11. In some points of view, when performing log analysis of shaly sand reservoirs,improper procedures sometimes result in overestimation of Sw (Riepe et al. 2008), asfollows :• Improper correction of resistivity logging tools, including borehole, shoulder bed and invasion effects, high dips or high well deviations, and thin bed effects (laminations, anisotropy). These may lead to underestimate the Rt values.• Incorrect value given to the resistivity of the formation water Rw,• Incorrect saturation equation and parameters, such as relationships between Sw and resistivity in Non Archie formations become more complex, as reflected by unknown variables of cementation exponent (m), saturation exponent (n), Cation Exchange Capacity (CEC). Overall, the solution becomes more complex, when formation has more than oneof these effects. However, as soon as the cause of low resistivity low contrast pay isrecognized and well understood, integrated logging tools and/or interpretation techniquescan be applied to compute accurate Sw. On the basis of particular reasons, related the occurrence of the low resistivity lowcontrast pay, Saha (2003) provides quite straightforward solutions, summarised in Table3.2 below. 11
  • 12. Techniques Objectives Advantages Limitations • Provide general output of No need to identify interval - average Volumetric To investigate the thin boundaries solution Laminated effects of thin bedsLow Sand analysis on standard • Valid only in certainresolution using resolution log data. limited assumptions on conventional Suitable for bed with Depth alignment the log response well logs thickness < 1 or 2 ft logs not required • Confirmation of the bed existence is needed. To detect bed • Require high resolution Log forward boundaries using logs to identify the modelling high-resolution data Able to show boundaries if each thinHigh and try to unravel detailed sand -shale beds.Resolution true log values in distribution of thin each thin bed. beds and pay zone Inversion Suitable for bed with • Uncertainty in solution thickness > 1 or 2 ft 1)To help confirm the • Provide strong • Distribution of the T2 presence of thin beds evidence for can be influenced by 2) Directly indicate indicator of pay many difference factors Nuclear zone even without presence of pay aside from pore size. magnetic any high zone • Require many resonance resolution data. 3) To differentiate consideration and other • Can estimate between bound and knowledge to apply the directly thickness free water. NMR of the pay zoneOther • Can reducespecial uncertainty in the • The multi componenttechniques low-resolution induction logs are evaluation of a sometimes unavailable To measure sensitive Multi thinly bedded as not widely used. perpendicular component reservoir. • Accuracy on transverse component in induction • Ability to provide resistivity measurement conductivity. influential evidence is unknown, and for indicator of pay environmental effects zone. are also uncertain Table 3.1. Summary of low and high resolutions techniques (After Passey et al, 2006 and Hamada et al., 2001) 12
  • 13. Reasons Facts Possible solutionsInvasion of Deep mud invasion, low reading 1) Run array laterolog or array induction log.conductive in Rt and computed Sw high 2) Run resistivity logging-while-drilling (LWD)mud Common in shaly sand 1) Run Gamma ray spectroscopy and ElementalHigh clay formations Capture Spectroscopy tools help estimate clay typecontent 2) Combine with lab based clay mineralogical analysis Mainly related to grain 1) Run NMR tools and even combined withPresence of size. resistivity LWD will greatly aid in thishigh capillary Affect resistivity logs to read low interpretation.bound water Mainly due to penetration of conductive muds into openPresence of fractures causing low reading in 1) Run borehole imaging tools with LWD, can be infractures Rt. water based and oil based mud. Common in carbonates Common in carbonate rock. May reduce reducing theMicro resistivity. Run NMR and or LWDporosity Example pyrite, may conceal thePresence of resistivity log reading. 1) Run photoelectric factor logconductive Various, uncertain effect based on 2) Run elemental spectroscopy log will helpminerals its distribution. effectively Makes resistivity logs becomeHigh angle 1) Implement an newly developed interpretation apparent and tend to read low.wells method in induction type tools. Averaging resistivity value in thin 1) To run higher vertical resolution tools with bed.Laminated deeper depth of investigation, or both. Unable to resolve characteristicsformations 2) integrate with borehole imaging tools, with water of individual thin beds. and oil based mud environments Table 3.2 Solutions with regards some causes of low resistivity low contrast pay (Adapted from Saha (2003). Following is a generalized work flow given by Saha (2003) for solution approach to low resistivity low contrast pay evaluation: 13
  • 14. 1. Carefully identify and define the pay zone, based on various data such as mud log and shows, wireline formation pressure and sample tests, or other tests such as drill stem or production tests.2. Find out the cause. This is the most important stage in the work flow because it determines selection of suitable solution or models to apply or develop to get reliable results.3. Make correction on the original high water saturation (Sw) to get lower a lower water saturation, unless Sw is high because of high capillary bound water4. Validate the results, preferably with core data.3.1.1 Nuclear Magnetic Resonance Technique Integrated log analysis of density, neutron and resistivity logs is proven to bevery effective in the evaluation of normal reservoirs. For low resistivity low contrast payzones, however, an accurate determination of the petrophysical parameters with theconventional logs is very difficult and frequently failed. Nuclear magnetic resonance(NMR) log has played an important role in providing advanced information on theproducibility of this typical reservoir. The technique provides a valuable measurement tohelp determine when the presence of thin beds of sand-shale sequences is assumed in alight oil bearing reservoir (Passey et al, 2006). NMR technique is applied to assist thepetrophysical evaluation especially to detect thin beds, determine fluid type, and establishthe hydrocarbon type and volume (Hamada et al. 2001). 14
  • 15. The main limitation of NMR is related to its high cost and time consumptionduring data collection. In the analysis of NMR data, several aspects of NMR techniquethat are used include: 1) Fluid identification based on T1/T2 ratio (Figure; 2) The types of clay minerals can be determined based on the porosity value difference between NMR derived porosity and total porosity; 3) NMR relaxation properties to identify fluids nature and rock properties. NMR technique has significantly contributed in identifying the producibility ofpay zones in low resistivity formations. It helps to verify lithology independent porosityand to differentiate between bound and free water. For the case of low contrast resistivityreservoir in which small resistivity variation exists between water bearing formation andoil bearing formation, interpretation on high contrast of NMR relaxation parameters hasenabled identification of the fluid nature of those formations as well as the oil columnthickness (Hamada et al., 2001).Figure 3.1. Distribution of T2 showing small and large pores (Hamada et al., 2001) 15
  • 16. IV. A Study Case of Low Resistivity Low Contrast Pay in Tertiary Basins in Malaysia This study case focuses on investigation of low resistivity low contrast zones inclastic reservoir of Tertiary basins in Malaysia. The basins are PETRONAS operatedfields including Malay, Sarawak and Sabah basins. These basins, among the mostproductive in South East Asia are moderately mature (Ghosh et al 2010) (Figure 4.1).The hydrocarbon exploration and exploitation within the areas were extensivelycommenced in 1882 when oil was discovered in Miri, Sarawak. Malay Basin is known to be one of the deepest basins (12 km at the center) in thispart of SE Asia. The lithology bearing the low resistivity low contrast pay zone, mainlycomprises of a thinly laminated sand-shale sequence. The other basins discussed includeSarawak (late Eocene to recent) and Sabah (mid-Miocene to recent). In general, reservoirrocks in Sabah basin are similar to Malay Basin (Ghosh et al, 2010). Low resistivity low contrast pay zones in these three basins specifically haveresistivity values ranging from 2-4 Ohm-m. These values are similar to the resistivities ofthe nearby shale beds. The values are within the resistivity value range (1-2Ohm-m) ofthe fresh formation water contained in the zones (Riepe et al, 2008). The pay zones werenot noticeable, so they were bypassed, due to insufficient conventional logging tools andformation evaluation techniques. 16
  • 17. Sabah Basin Malay Basin Sarawak Basin Figure 4.1. Location of Malay, Sabah and Sarawak basins (After Ghosh et al, 2010)4.1 Integrated Modern Petrophysical Techniques The revisited study by Riepe et al (2008) to investigate the low resistivity lowcontrast pay zones in these basins, aims at determining Sw cut-off. It is because of thezones significantly contain a high volume of “capillary bound” water. Geological factscausing the existence of low resistivity low contrast pay zones in the basins include ingrain size, high amount of bioturbated fine silts and shales and relatively high claycontent with high Cation Exchange Capacity. Recognition of the causes of the lowresistivity low contrast pay zone beneficially provides a guideline on selection ofadvanced petrophysical techniques to assess the zones. 17
  • 18. The study is performed based on petrophysical analysis of advanced log dataincluding Nuclear Magnetic Resonance (NMR) and Borehole Imaging. The log data areincorporated with Special Core Analysis (SCAL) data which consist of electrical,hydraulic and NMR properties. The study results in enhanced concepts and work flowsthat are established for the identification of cut-off criteria for “net pay”, log evaluationparameters and possible adjustment in saturation equations. The results provideguidelines for further evaluation in other PETRONAS basins bearing low resistivity lowcontrast pay zones.4.2 Work flow The study comprises three stages covering:1) Well selection: with a focus on wells representing LRLC zones. The wells should havesufficient amount of log and core data. If available, image logs were used to identifyhorizons with thinly bedded sand/shale sequences.2) Special Core Analysis: to assess three various independent measurements i.e. NMRT2-Spectra at different Sw; capillary type; and NMR properties. The schematic processof this stage is portrayed in Figure 4.2.3) Well log analysis: resistivity and NMR logs are set up as focus of the analysis to getand compare saturation profiles. Some corrections are carried out in resistivity data toproduce realistic profiles of Rt for the Sw evaluation from different saturation models andequations. In detailed, the steps of the analysis are shown in Figure 4.3. 18
  • 19. Figure 4.2. Flow chart showing the process of evaluation of Swirr performed in thestage of Special Core Analysis (Riepe et al., 2008) Figure 4.3. Flow chart showing the process of evaluation of Swirr performed in thestage of Well log Analysis (Riepe et al., 2008). 19
  • 20. To simplify, the Sw cut-off is essentially set based on its irreducible watersaturation (Swirr) so that the reservoir will be productive to verify permeabilitypredictions. The permeability is analyzed based on capillary pressure and relativepermeability data. The study applies NMR technology to obtain T2 spectra and correlateit with the Swirr data. The correlation is subsequently applied to NMR log derivedcontinuous Swirr and permeability profiles that have been calibrated. V. Conclusions Low resistivity low contrast pay (LRLCP) is a challenging universal phenomenonfaced in evaluating hydrocarbon bearing formations, for over three decades. Difficulty inidentifying low-resistivity pay in log analysis has been recognized since the firstdiscovery of major low resistivity low contrast pay in USA. Insufficient verticalresolution of conventional resistivity data and unsuitable techniques in log analysis causebypassing the hydrocarbon potentiality due to overestimation on Sw values. Low resistivity low contrast pay is commonly found in formations associated withthinly bedded sand-shale sequences, normally characterised by low value in deepresistivity logs ranging from 0.5 to 5 ohm-m. The occurrence of low resistivity lowcontrast pay can be caused by a range of different factors including formation waters (lowor fresh); conductive minerals; grain or pore size effects; bioturbation effects, invasion ofconductive muds, presence of fractures and capillary bound water, and high angle wellsdue to anisotropy effect. When evaluating the shale-sand sequence in the low resistivity low contrast pay,appreciation on detailed information about clay minerals, such as type, volume, and 20
  • 21. distribution is essential. It is because those clay parameters will greatly affect the logresponse. By understanding those clay parameters, interpretation on log response willprovide better and reliable solution. are present in the sequence tone, type, volume, anddistribution of the clay will affect the well log response to that sandstone. Various techniques can be applied to resolve problems in the low resistivity lowcontrast pay, comprising low and high resolution techniques. Above all, NMR techniqueappears to be the powerful one, mainly because its ability to identify fluids naturewhether free and clay bound water using T1/T2 ratio as the major cause of low resistivitylow contrast pay. The main workflow of solution approach that can effectively help copewith low resistivity low contrast pay is identification and definition of the pay zone,identification the causes of the pay zone which determine proper techniques to apply andvalidation the results with core data.ReferencesAlmon, W.R., 1977, Sandstone diagenesis is stimulation design factor: Oil and Gas Journal, 13, 56-59.Almon, W.R., 1979, A Geologic Appreciation Of Shaly Sands : SPWLA 20th Annual Logging Symposium.Archie, G.E., 1942, The electrical resistivity log as an aid in determining some reservoir characteristics: Transactions of the American Institute of Mining and Metallurgical Engineers, 146, 54-62.Blatt, H., 1992, Sedimentary Petrology, W H Freeman & Co (Sd) , 2nd ed. 514 pages 21
  • 22. Boyd, A., Darling, H., Tobano, J., Davis, B., Lyon, B., Flaum, C., Klein, J., Sneider, R.J., Sibbit, A., Singer, J., 1995, The Lowdown on Low-Resistivity Pay : Oilfield Review, Autumn edition, 4-18.Darling H.L. and Sneider R.M., 1993, Productive Low Resistivity Well Logs of the Offshore Gulf of Mexico: Causes and Analysis,” in Moore D (ed), 1993: Productive Low Resistivity Well Logs of the Offshore Gulf of Mexico. New Orleans, Louisiana, USA: Houston and New Orleans Geological Societies.Fanini, O. N., Kriegshäuser, B. F., Mollison, R. A., Schön, J.H., and Yu, L., 2001, Enhanced, Low-Resistivity Pay, Reservoir Exploration and Delineation with the Latest Multicomponent Induction Technology Integrated with NMR, Nuclear, and Borehole Image Measurements: OTC 13279, Offshore Technology ConferenceFrost, Jr., E. and Fertl, W.H., 1981, Integrated core and log analysis concepts in shaly clastic reservoirs : Log Analyst, 22, 3-16Ghosh, D., M., Halim, FAH., Brewer M., Viratno, B., and Darman, N., 2010, Geophysical issues and challenges in Malay and adjacent basins from an E & P perspective: The Leading Edge, 29 (4), 436-449,Hamada, G.M., Al-Blehed, M.S., Al-Awad, M.N., Al-Saddique, M.A., 2001, Petrophysical evaluation of low-resistivity sandstone reservoirs with nuclear magnetic resonance log: Journal of Petroleum Science and Engineering 29, 129–138.Kuecher, G., and Millington , J., 2000. Turbidites Hold Great Potential for Deepwater Exploration : Depth , 6 (1), 30-35.Murphy, R. P., and Owens, W. W., 1972. A new approach for low-resistivity sand log analysis :Journal of Petroleum Technology, 24, 1302–1306.Passey, Q. R., Dahlberg, K. E. , Sullivan, K. B., Yin, H. , Brackett, R. A. , Xiao, Y. H. and Guzmán-Garcia, A. G., 2006, Petrophysical Evaluation of Hydrocarbon Pore-Thickness in Thinly Bedded Clastic Reservoirs, AAPG Archie Series, 1, 1 – 197.Pettingill, H.S., 1998, Worldwide Turbidite E&P: A Globally Immature Play with Opportunities in Stratigraphic Traps: SPE paper 49245.Riepe. L., Hamid, A.S.B.A, Hamzah, M.H.R.B., and Zain, Zain, M.N.B.M., 2008, Integrated Petrophysical Analysis to Evaluate Low Resistivity Low Contrast (LRLC) Pays In Clastic Reservoirs In Se Asia: International Symposium of the Society of Core Analysts held in Abu Dhabi, UAE 29 October-2 November, 2008 22
  • 23. Saha. S., 2003, Low-Resistivity Pay (LRP) : Ideas for Solution, SPE 85675Tixier, M. P., Morris, R. L., and Connell, J. G., 1968, Log evaluation of low-resistivity pay sands in the Gulf Coast : The Log Analyst, 9(6), 3–20.Worthington, P., 1985, The Evolution of Shaly-sand Concepts in Reservoir Evaluation : The Log Analyst, Jan-Feb, 23-40.Worthington, P.F., and Johnson, P.W., 1991, Quantitative Evaluation of Hydrocarbon Saturation in Shaly Freshwater Reservoir : The Log Analyst, v.32, no.4, 356-368.Worthington, 2000, Recognition and evaluation of low-resistivity pay : Petroleum Geoscience, 6 , 77–92Worthington, P.F., 2005, An Electrical Analog Facility for Hydrocarbon Reservoirs: SPE 96718 23