CHALMERS UNIVERSITY OF TECHNOLOGY SE 412 96 Göteborg, Sweden Phone: + 46 - (o)31 772 10 00 Web: www.chalmers.se s h a h z a d a h m e d C la y C o n d u c t iv it y a n d W a t e r S a t u r a t io n M Clay Conductivity and Water Saturation o d e ls Models Master’s Thesis in the International Master’s Programme Applied Environmental Measurement Techniques shahzad ahmed Department of Civil and Environmental Engineering Water Environment Technology chalmers university of technology 2 0 Göteborg, Sweden 2005 0 5 :6 Master’s Thesis 2005:67 7 MASTERS THESIS 2005:67 Clay Conductivity and Water Saturation Models Shahzad Ahmed Department of Civil and Environment Engineering Water Environment Technology CHALMERS UNIVERSITY OF TECHNOLOGY Göteborg, Sweden 2005 Clay conductivity and water saturation models © Shahzad Ahmed, 2005 Master’s Thesis 2005:67 Department of Civil and Environment Engineering Water Environment Technology Chalmers University of Technology SE-412 96 Göteborg Sweden Telephone +46(0)31-772 1000 Reproservice, Chalmers University of Technology, Göteborg, Sweden 2005 Clay Conductivity and water Saturation Models SHAHZAD AHMED Department of Civil and Environmental Engineering, Institute of Environment & Resources, Hydrocarbon and Mineral Resources, Technical University of Denmark, DTU, Chalmers University of Technology ABSTRACT Shales have great influence on the determination of fluid saturations. Clay in the shaly formation also conducts the electrical current in addition to formation water. Waxman and Smits saturation resistivity relationship related the conductivity of shale to CEC of clay. In absence of core CEC measurements, different models were proposed to account the effect of shale conductivity on total conductivity of formation and to predict effective water saturation. In this work CEC of cores samples (obtained from well # 03) was measured and water saturation results obtained by using Waxman and Smits saturation resistivty relationship were compared with water saturation results obtained from other water saturation methods. Water saturation predicted by Waxman and Smits equation is found to be higher than water saturation calculated by using Laminated Sand and Shale Model, Total Shale relation, Volan model, and Normalised Waxman and Smits equation, while lower than water saturation obtained by using Cyber Look program and Archie Model. Differences in water saturation results were attributed to differences in estimation of shale conductivity contribution to total formation conductivity by different water saturation methods. Key words, water saturation, conductivity, porosity, log, shale, Cation Exchange Capacity (CEC) ACOKNOWLEDGEMENT This is a master thesis from Department of Environment and Resources, Technical University of Denmark worked out in the period of 14 Sep. 2003 to 29 May 2004. The project has been supervised by Ida Lyke Fabricius (DTU) and Greg Morrison (Chalmers). First of all I would be thankful to almighty God who give me wealth of knowledge and make me able to know his miseries in universe. Grate thanks to my supervisor “Ida Lyke Fabricius” who invited me as guest student in DTU. She is one of best teachers ever in my life. She created determination in my study approach. She always welcomed me, whenever, I knocked her door for seeking guideline about my project work. Thanks to all my teachers at Chalmers University of Technology Gothenburg, Sweden who taught me. Special thanks to my Program Director “Mr Greg Morison” who allowed me to do project work at DTU (Copenhagen). Many thanks to Mr Sink, who showed his keen interests in completing my lab works. I am also thankful to Hector who cleaned core samples one and half month with patience. I am also thankful to my parents and all my family members who prayed for me and showed patience in bearing my absence from home. Many thanks to Chief chemist “Abdul Wahid Butt” (O.G.D.L) and Deputy Chief Engineer “Abdur Rashid Watoo” (O.G.D.L) who encouraged me to study in abroad. I would like to say special thanks to my brother Amjad Ali (O.G.D.C.L) who always stood beside me and he is key behind my successes in studies. Thanks to my beloved Uzma who constantly encouraged me, during my whole Master studies. She always spared some time for me from her very busy daily life to give me moral support. Many thanks to Mr Mushtaq for his kind help who trusted on me. My thanks to my class fellow Khalid for his all time help. Thanks to Mr Ahmed Yar Cheema (DTU) and Adnan Qadir Chemma (DTU) who gave shelter in Copenhagen and for their moral support. Many thanks to Mr Yousaf Cheema (DTU), who formatted my thesis report with his full devotion. I am also thankful to Javed Bahtee (DTU) and Irfan Ahmed (Neil’s Brock College) who gave me good company in Copenhagen. In the end thanks to “MAERSK OIL COMPANY” for providing log data and core samples for project work. Table of Contents 1. Introduction 1 1.1 Lithology in Shaly Sands 1 1.2 Lithology in Shale Model 1 1.3 Lithology in Clay Model 2 1.4 Porosity in Shaly Sands 4 1.5 Effective- Porosity from the Shale Model. 4 1.6 Effective-Porosity from Clay Model 5 1.7 Resistiviyt logging 5 1.8 Water Resistivity 5 1.9 Formation Factor and Porosity 6 1.10 Water Saturation 6 1.11 Water-Saturation Using Shale Model. 8 1.11.1 Laminated Sand-shale simplified Models 8 1.11.2 Dispersed Shale Simplified Model 8 1.11.3 Total Shale Relationship 10 1.12 Water-Saturation Using the Clay Model. 10 1.12.1 Waxman-Smits Model. 10 1.11.2 Dual Water Model 12 2. Material and Methods 17 2.1 Samples Preparation 17 2.2 Conductivity 17 2.3 Grain Density and Porosity 17 2.4 Specific Surface Area 17 2.5 X-Ray Diffraction 18 2.6 Cation Exchange Capacity 18 3. Characterisation of Chalk 19 3.1 x-Ray Diffraction 19 3.1.1 Impurities in Chalk Samples 19 3.2 Specific Surface Area 22 3.3 Cation Exchange Capacity 23 3.4 a, m, B Values 26 3.5 Formation Water R and R 27 w wb 4. Comparison of Water Saturations between Waxman and Smits Saturation Resistivity Relationship and Different Water Saturation Models 28 4.1 Comparison of Water Saturations between Waxman and Smits Saturation Resistivity Relationship and Archie’s Water Saturation Equation Model 28 4.2 Comparison of Water Saturations between Waxman and Smits Saturation Resistivity Relationship and Laminated Sand and Shale Model 30 4.3 Comparison of Water Saturations between Waxman and Smits Saturation Resistivity Relationship and Total Shale Relation 32 4.4 Comparison of Water Saturations between Waxman and Smits Saturation Resistivity Relationship and Volan Model 34 4.5 Comparison of Water Saturations Between Waxman and Smits Saturation Resistivity Relationship and Cyber Look Program 36 4.6 Comparison of Water Saturations between Waxman and Smits Saturation Resistivity Relationship and Normalised Waxman And Smits Saturation Equation 38 4.7 Comparison of Water Saturations Between Waxman and Smits Saturation Resistivity Relationship and Dispersed Shale Model 40 5 Inter Comparison of Water Saturation Results Obtained by each method in Well No 3A and 3 P 44 6 Conclusion 55 7 References 56 List of Appendices A X-ray Diffraction B BET of Chalk Samples C BET of IR OF Chalk Samples D CEC E Core conductivity and Porosity F Miscellaneous Introduction 1 INTRODUCTION Physical properties such as density, porosity, resistivity, shale contents of subsurface formations varies with depth. The plots of these properties against depth are called well logs. Well Logs are run to obtain the information such as porosity, resistivty of rock formation in subsurface evaluation. Both porosity and resistivity measurements are used to compute water saturation,S in rock formation. From water saturation measurements, wt quantity of hydrocarbon in formation is estimated. The resistivty and porosity parameters are measured with logging tools. It has been considered that hydrocarbon bearing formation rock have very low or zero conductivity. Conductivity of rock is only due to water present in clean sand formation. Archie proposed water saturation determination for clean water bearing sand formation. Presence of clay or shale increases the conductivity of rock formation and also affects the porosity readings. Therefore, the conductivity measurements obtained from logging data are higher than true resistivity due to extra conductivity caused by shale. The shale contents are usually estimated by gamma-ray log. Different water saturation models have been developed to account the extra conductivity caused by clay. The log derived porosity is corrected by calibrating with core porosity (1). Formations rock matrix consist of sand and shale. Shale can be distributed in the formation in three ways e.g. (i) Laminated shale (ii) Dispersed shale (iii) Structural shale. The way of shale distribution affects log measurement differently. In water saturation determination two approaches are used to model the shale in shaly formation. One is Shale Sand Model and other is Clay Sand Model. 1.1 Lithology in Shaly Sands In shaly sands, the rock matrix is composed of shale and quartz. In shale model such lithology is described as shale and quartz. In the particular formation shale consists of clay, mica, feldspar, iron oxide and organics. In Clay Model formation rock matrix can be described as clay and sand (2). In clay models, sand comprises quartz, mica, and feldspar. 1.2 Lithology in Shale Model. To evaluate shaly sand subsurface formation, it is necessary to know much quantity of shale is present in typical formation to estimate the true conductivity and porosity of formation from logging data. Three types of different logs like gamma-ray, spontaneous potential and sonic log can be use to measure the amount of shale (3,4). The gamma-ray log measures the natural radioactivity of formations. In sedimentary formation the log normally reflects the shale content of formations due to tendency of radioactive elements to concentrate in clays and shales. Uranium, Potassium and Thorium are the common radio active elements present in shale and clay. Clean formations exhibit very low radioactivity. Spontaneous Potential curve record the electrical potential (voltage) produced by the interaction of formation connate water, conductivity of drilling fluid and certain-ion-selective rock (shale). Above mentioned techniques use a common method to estimate the quantity of shale given below. 1 Clay Conductivity and Water Saturation Models Introduction (Log −Log ) V = reading min_sh (1) sh (Log −Log ) max_sh min−sh Here, V is the estimated shale volume, Log is reading of shale indicator log, e.g. sh reading gamma ray, spontaneous potential or sonic. Log is the reading of shale indicator max−sh from 100 % log shale section and Log is the reading of shale indicator across the min_sh clean quartz (0.0% shale ) sections. Density log can also be used to determine the amount of shale present in typical sand formation .The density log reading of a formation is the sum of densities of all formation constituents weighted in unit bulk volume of formation and is given by Equation(2) ρ =ρ S +ρφ(1−S )+ρ (1−φ−V )+ρ V (2) b w w h w qtz sh sh sh Here, ρ,ρ ,ρ ,ρ ,ρ corresponds to the formation bulk density, water density, b w h qtz sh hydrocarbon density, quartz density and shale density respectively. φ and S w corresponds to formation porosity and water saturation respectively. Another method to quantify the shale is the neutron-density cross plot (5). In this method neutron and density logs are plotted on neutron-density cross plot. The clean sand points lie along the quartz sandstone and shaly points fall below that line towards a far point (shale point). Shale volume is estimated by dividing the distance of any point P from the quartz sand stone with distance of shaly point line S from the same line. Actually, these plots are made by assuming 100 % water. Since the density of oil is close to water, therefore these plots can be used with some approximation. Use of such cross plots is difficult if the gas or light hydrocarbons are present in the formation because the gas and light hydrocarbons have very low density as compared to water density. Points correspond to gas bearing section in the formation shift the data point above the quartz sandstone. It is very hard to get reliable results in presence of gas (5,6). Most of above mentioned techniques over estimate shale volume in formation. Gamma ray technique is convenient and practical but it can be inaccurate. Shale volume estimated by using gamma ray technique can be calibrated by shale volume obtained from experimental measurements on representative formation rock. Clay minerals present in shale can be determined by the X-ray Diffraction analysis of core samples. Cation exchange capacity of core sample is measured to determine actual amount of shale volume present in rock formation. 1.3 Lithology in Clay Model Clay Model describes formation lithology in term of sand and clay. The clay comprises all the clay minerals, e.g. illite, montmorillonite, chlorite, kaolinite, which may present in the formation. Abundance of clay can be estimated by using Elemental Capture Spectroscopy log (7). Most of oil companies avoid (ECS) technique because it is very expensive. X-ray diffraction technique determines the types of clay minerals present in rock formation. Clay abundance obtained from experimental measurement on representative formation rock can be used to calibrate clay abundance estimated from clay indicator logging data. Above described techniques measure the clay abundance as 2 Clay Conductivity and Water Saturation Models Introduction weight-percent of formation rock matrix,W , which is then latter transferred in to dry−clay volume-percent of formation bulk volume using following Equation-3. W ρ (1−φ ) Vol = dry−clay matrix totlal (3) dry−clay ρ dry−clay Here, φ is the formation total porosity. ρ is the dry clay density, which can be totlal dry−clay determined by XRD analysis of core samples. ρ is the shaly sand matrix porosity and matix can be obtained from representative core analysis measurements. Vol is clay dry−clay abundance as volume percentage of shaly sand bulk volume. Also there are some other techniques developed for the estimation of clay volume but those are not accurate (8). In clay model to calculate sand volume in shaly sands both pore volume and shale are excluded. Clay minerals have the property to bind the formation water. The water bound to clay minerals is known as clay-bound water. The volume of clay bound water can be estimated form following Equation-4 & Equation-5 (9,10,11). Vol =V Qφ (4) clay−bound−water Q v total Vol =V *CEC*ρ *Vol (5) clay−bound−water Q dry−clay dry−clay Here, φ is the formation total porosity. Q in Equation -4 is the clay cation-exchange- totlal v capacity in milliequivalent per unit volume of pore fluids. Q can be determined by v experimental measurement on representative core samples and brine sloution. V is the Q amount clay-bound water bind with one milliequivalent of clay counter ions. Vol is dry−clay the volume of dry clay. ρ is the dry-clay density. In Equation-5, CEC is the clay dry−clay Cation Exchange-Capacity in milli equivalents per unit mass of dry clay. There are different methods for the determination of CEC of core samples (12, 13). CEC can also be determined, if we know about dominant clay mineral abundance in typical formation (2).Vol is the volume of clay bound water per unit bulk volume of formation. clay−bound−water The clay bound water saturation in the pores S can be obtained using the Equation-6. cbw S =Vol /φ (6) cbw clay−bound−water totlal Clay- bound-water affects the porosity and resistivity reading of logging tools. It is necessary to estimate all these effect in order to improve accuracy of calculated effective- porosity and water-saturation in shaly sands evaluation. For this, it is necessary to have knowledge of clay minerals abundance in formation for the estimation of clay bound water on logging tools. Therefore, estimating dry-clay volume is essential to measure the accurate effective porosity and water saturation in shaly sands. 3 Clay Conductivity and Water Saturation Models