U. Prasad, A. Hanif, I. McGlynn, F. Walles, A. Abouzaid, O. Hamid
The influences of mineralogy on rock mechanical properties have profound application in oil and gas exploration and production processes, including hydraulic fracturing operations. In conventional resources, the rock mechanical properties are predominantly controlled by porosity; however, in unconventional tight formations, the importance of mineralogy as a function of rock mechanical properties has not been fully investigated. In unconventional tight formations, mechanical properties are often derived from mineralogy weight fraction together with the best estimate of porosity, assumption of fluid types, the extent of pore fillings, and fluid properties. These properties are then adjusted for their volumetric fractions and subsequently calibrated with acoustics or geomechanical lab measurements. A new method is presented that utilizes mineralogy weight fractions (determined from well logs or laboratory measurements). This process uses public domain information of minerals using Voigt and Reuss averaging algorithms as upper and lower bounds, respectively. An average of these bounds (also known as Hill average) provides a representative value for these parameters. Further, based on isotropic conditions, all the elastic properties are calculated. A typical output consisting of bulk-, shear-, and Young's - modulus, together with Poisson's ratio obtained from traditional methods of volume fractions and this new method using weight fractions is discussed and analyzed along with the sensitivity and the trends for individual rock properties. Furthermore, corresponding strengths, hardness, and fracture toughness could also be estimated using well known public domain algorithms. Data from carbonate reservoirs has been discussed in this work. This method shows how to estimate grain compressibility that can be challenging to be measured in the lab for unconventional tight rock samples. In low-porosity samples, the relative influence of porosity is negligible compared to the mineralogy composition. This approach reduces several assumptions and uncertainties associated with accurate porosity determination in tight rocks as it does not require the amount of pore fluids and fluid properties in calculations. The grain-compressibility and bulk-compressibility (measured by hydrostatic tests in the laboratory on core plugs or calculated from density and cross-dipole log) are used to calculate poroelastic Biot's coefficient, as this coefficient will be used to calculate in-situ principal effective stresses (overburden, minimum horizontal, and maximum horizontal stresses), which are, together with rock properties and pore pressure, constitutes the geomechanical model. The geomechanical model is used for drilling, completions, and hydraulic fracture modeling, including wellbore stability, and reservoir integrity analyses.
{"title":"An Innovative Methodology for Estimating Rock Mechanical Properties from Weight or Volume Fractions of Mineralogy and its Application to Middle East Reservoirs","authors":"U. Prasad, A. Hanif, I. McGlynn, F. Walles, A. Abouzaid, O. Hamid","doi":"10.2118/204687-ms","DOIUrl":"https://doi.org/10.2118/204687-ms","url":null,"abstract":"\u0000 The influences of mineralogy on rock mechanical properties have profound application in oil and gas exploration and production processes, including hydraulic fracturing operations. In conventional resources, the rock mechanical properties are predominantly controlled by porosity; however, in unconventional tight formations, the importance of mineralogy as a function of rock mechanical properties has not been fully investigated.\u0000 In unconventional tight formations, mechanical properties are often derived from mineralogy weight fraction together with the best estimate of porosity, assumption of fluid types, the extent of pore fillings, and fluid properties. These properties are then adjusted for their volumetric fractions and subsequently calibrated with acoustics or geomechanical lab measurements. A new method is presented that utilizes mineralogy weight fractions (determined from well logs or laboratory measurements). This process uses public domain information of minerals using Voigt and Reuss averaging algorithms as upper and lower bounds, respectively. An average of these bounds (also known as Hill average) provides a representative value for these parameters. Further, based on isotropic conditions, all the elastic properties are calculated.\u0000 A typical output consisting of bulk-, shear-, and Young's - modulus, together with Poisson's ratio obtained from traditional methods of volume fractions and this new method using weight fractions is discussed and analyzed along with the sensitivity and the trends for individual rock properties. Furthermore, corresponding strengths, hardness, and fracture toughness could also be estimated using well known public domain algorithms.\u0000 Data from carbonate reservoirs has been discussed in this work. This method shows how to estimate grain compressibility that can be challenging to be measured in the lab for unconventional tight rock samples. In low-porosity samples, the relative influence of porosity is negligible compared to the mineralogy composition. This approach reduces several assumptions and uncertainties associated with accurate porosity determination in tight rocks as it does not require the amount of pore fluids and fluid properties in calculations. The grain-compressibility and bulk-compressibility (measured by hydrostatic tests in the laboratory on core plugs or calculated from density and cross-dipole log) are used to calculate poroelastic Biot's coefficient, as this coefficient will be used to calculate in-situ principal effective stresses (overburden, minimum horizontal, and maximum horizontal stresses), which are, together with rock properties and pore pressure, constitutes the geomechanical model. The geomechanical model is used for drilling, completions, and hydraulic fracture modeling, including wellbore stability, and reservoir integrity analyses.","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87288757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dissolvable tools have been used more in unconventional oil and gas operations in recent years. Sealing element is one of the important parts of the dissolvable tools. The dissolvable rubbers in the market either have low strength or the dissolution rate was low. A series of high strength dissolvable rubbers with various dissolution rate have been developed by CNPC-USA to meet the industrial requirements. The mechanical properties of the dissolvable rubbers were tested at ambient and high temperatures. The dissolvable rubber coupons were soaked in water, 0.3%, 1% KCl at 80, 90 and 120 °C for various durations up to 47 days. The mass, dimensions, volume, hardness, density, and tensile properties of the samples were measured after different durations to characterize the dissolution rate. In addition, the pressure rating of dissolvable rubber sealing element was tested in water environment at 90 °C or 100 °C and in oil environment at 120 °C for 24 hours. The dissolution rate of the dissolvable rubber sealing element was tested at 90 °C or 80 °C in brine. It was found that the tensile strength of the dissolvable rubber at high temperature was in the range of 800-3000 psi and the elongation of the dissolvable rubber at high temperature was higher than 500%, which was higher than that of the most of the commercial dissolvable rubbers. For 90-120°C rated dissolvable rubbers, the dissolvable rubber coupons were disintegrated in brine at 90 °C in 5-15 days and the dissolvable rubber was completely dissolved in brine at 120°C in 4 days. The dissolvable rubber sealing elements hold 10,000 psi pressure differential at 90 °C in water and at 120 °C in oil environment for more than 24 hours. On the other hand, the dissolvable rubber sealing element were disintegrated in 90°C, 1% KCl in 7-11 days. For 80-120°C rated dissolvable rubbers, the dissolvable rubber coupons were disintegrated in brine at 80°C in 3-10 days. The dissolvable rubber sealing elements hold 8,700 psi pressure differential for 24 hours and 10,000 psi pressure differential at 100 °C for 15 minutes. On the other hand, the dissolvable rubber sealing elements were disintegrated at 80°C in 1% KCl in 3-5 days. The pressure rating properties and dissolution rate properties of the dissolvable rubber sealing elements met the field operation requirements. The dissolvable plugs with the dissolvable rubber sealing elements have been successfully used in multiple tight-oil wells and more than 15 shale gas wells fracturing operations in China. The dissolution rate of the dissolvable rubber could be controlled by adjusting the formulations. The dissolution rate of the dissolvable rubber was independent of brine concentration. CNPC-USA has developed a series of dissolvable rubbers in the temperature range from 40°C to 175°C applications to meet different operation requirements.
{"title":"Dissolvable Rubbers Development and its Applications in Downhole Tools","authors":"Jiaxiang Ren, Pengyu Cheng, Xu Wang","doi":"10.2118/204622-ms","DOIUrl":"https://doi.org/10.2118/204622-ms","url":null,"abstract":"\u0000 Dissolvable tools have been used more in unconventional oil and gas operations in recent years. Sealing element is one of the important parts of the dissolvable tools. The dissolvable rubbers in the market either have low strength or the dissolution rate was low. A series of high strength dissolvable rubbers with various dissolution rate have been developed by CNPC-USA to meet the industrial requirements.\u0000 The mechanical properties of the dissolvable rubbers were tested at ambient and high temperatures. The dissolvable rubber coupons were soaked in water, 0.3%, 1% KCl at 80, 90 and 120 °C for various durations up to 47 days. The mass, dimensions, volume, hardness, density, and tensile properties of the samples were measured after different durations to characterize the dissolution rate. In addition, the pressure rating of dissolvable rubber sealing element was tested in water environment at 90 °C or 100 °C and in oil environment at 120 °C for 24 hours. The dissolution rate of the dissolvable rubber sealing element was tested at 90 °C or 80 °C in brine. It was found that the tensile strength of the dissolvable rubber at high temperature was in the range of 800-3000 psi and the elongation of the dissolvable rubber at high temperature was higher than 500%, which was higher than that of the most of the commercial dissolvable rubbers.\u0000 For 90-120°C rated dissolvable rubbers, the dissolvable rubber coupons were disintegrated in brine at 90 °C in 5-15 days and the dissolvable rubber was completely dissolved in brine at 120°C in 4 days. The dissolvable rubber sealing elements hold 10,000 psi pressure differential at 90 °C in water and at 120 °C in oil environment for more than 24 hours. On the other hand, the dissolvable rubber sealing element were disintegrated in 90°C, 1% KCl in 7-11 days.\u0000 For 80-120°C rated dissolvable rubbers, the dissolvable rubber coupons were disintegrated in brine at 80°C in 3-10 days. The dissolvable rubber sealing elements hold 8,700 psi pressure differential for 24 hours and 10,000 psi pressure differential at 100 °C for 15 minutes. On the other hand, the dissolvable rubber sealing elements were disintegrated at 80°C in 1% KCl in 3-5 days.\u0000 The pressure rating properties and dissolution rate properties of the dissolvable rubber sealing elements met the field operation requirements. The dissolvable plugs with the dissolvable rubber sealing elements have been successfully used in multiple tight-oil wells and more than 15 shale gas wells fracturing operations in China.\u0000 The dissolution rate of the dissolvable rubber could be controlled by adjusting the formulations. The dissolution rate of the dissolvable rubber was independent of brine concentration. CNPC-USA has developed a series of dissolvable rubbers in the temperature range from 40°C to 175°C applications to meet different operation requirements.","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86213044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
During the evolution of the petroleum industry, surface seismic imaging has played a critical role in reservoir characterization. In the early days, borehole seismic (BHS) was developed to complement surface seismic. However, in the last few decades, a wide range of BHS surveys has been introduced to cater to new and unique objectives over the oilfield lifecycle. In the exploration phase, vertical seismic profiling (VSP) provides critical time-depth information to bridge time indexed subsurface images to log/reservoir properties in depth. This information can be obtained using several methods like conventional wireline checkshot or zero-offset vertical seismic profiling (ZVSP), seismic while drilling (SWD) or distributed acoustic sensing (DAS) techniques. SWD is a relatively new technique to record real-time data using tool deployed in the bottomhole assembly without disturbing the drilling. It helps to improve decision making for safer drilling especially in new areas in a cost-effective manner. Recently, a breakthrough technology, distributed acoustic sensing (DAS), has been introduced, where data are recorded using a fiber-optic cable with lots of saving. ZVSP also provides several parameters like, attenuation coefficient (Q), multiples prediction, impedance, reflectivity etc., which helps with characterizing the subsurface and seismic reprocessing. In the appraisal phase, BHS applications vary from velocity model update, anisotropy estimation, well- tie to imaging VSPs. The three-component VSP data is best suited for imaging and amplitude variation with offset (AVO) due to several factors like less noise interference due to quiet downhole environment, higher frequency bandwidth, proximity to the reflector, etc. Different type of VSP surveys (offset, walkaway, walkaround etc.) were designed to fulfill objectives like imaging, AVO, Q, anisotropy, and fracture mapping. In the development phase, high-resolution images (3D VSP, walkaway, or crosswell) from BHS surveys can assist with optimizing the drilling of new wells and, hence reduce costs. it can help with landing point selection, horizontal section placement, and refining interpretation for reserve calculation. BHS offers a wide range of surveys to assist the oilfield lifecycle during the production phase. Microseismic monitoring is an industry-known service to optimize hydraulic fracturing and is the only technique that captures the induced seismicity generated by hydraulic fracturing and estimate the fracture geometry (height, width, and azimuth) and in real time. During enhanced oil recovery (EOR) projects, BHS can be useful to optimize the hydrocarbon drainage strategies by mapping the fluid movement (CO2, water, steam) using time-lapse surveys like walkaway, 3D VSP and/or crosswell. DAS has brought a new dimension to provide vital information on injection or production evaluation, leak detection, flow behind tubing, crossflow diagnosis, and cement evaluation during production phas
{"title":"Borehole Seismic: Essential Contributions Over the Oilfield Lifecycle","authors":"Rajeev Kumar, P. Bettinelli","doi":"10.2118/204889-ms","DOIUrl":"https://doi.org/10.2118/204889-ms","url":null,"abstract":"\u0000 During the evolution of the petroleum industry, surface seismic imaging has played a critical role in reservoir characterization. In the early days, borehole seismic (BHS) was developed to complement surface seismic. However, in the last few decades, a wide range of BHS surveys has been introduced to cater to new and unique objectives over the oilfield lifecycle.\u0000 In the exploration phase, vertical seismic profiling (VSP) provides critical time-depth information to bridge time indexed subsurface images to log/reservoir properties in depth. This information can be obtained using several methods like conventional wireline checkshot or zero-offset vertical seismic profiling (ZVSP), seismic while drilling (SWD) or distributed acoustic sensing (DAS) techniques. SWD is a relatively new technique to record real-time data using tool deployed in the bottomhole assembly without disturbing the drilling. It helps to improve decision making for safer drilling especially in new areas in a cost-effective manner. Recently, a breakthrough technology, distributed acoustic sensing (DAS), has been introduced, where data are recorded using a fiber-optic cable with lots of saving. ZVSP also provides several parameters like, attenuation coefficient (Q), multiples prediction, impedance, reflectivity etc., which helps with characterizing the subsurface and seismic reprocessing.\u0000 In the appraisal phase, BHS applications vary from velocity model update, anisotropy estimation, well- tie to imaging VSPs. The three-component VSP data is best suited for imaging and amplitude variation with offset (AVO) due to several factors like less noise interference due to quiet downhole environment, higher frequency bandwidth, proximity to the reflector, etc. Different type of VSP surveys (offset, walkaway, walkaround etc.) were designed to fulfill objectives like imaging, AVO, Q, anisotropy, and fracture mapping.\u0000 In the development phase, high-resolution images (3D VSP, walkaway, or crosswell) from BHS surveys can assist with optimizing the drilling of new wells and, hence reduce costs. it can help with landing point selection, horizontal section placement, and refining interpretation for reserve calculation.\u0000 BHS offers a wide range of surveys to assist the oilfield lifecycle during the production phase. Microseismic monitoring is an industry-known service to optimize hydraulic fracturing and is the only technique that captures the induced seismicity generated by hydraulic fracturing and estimate the fracture geometry (height, width, and azimuth) and in real time. During enhanced oil recovery (EOR) projects, BHS can be useful to optimize the hydrocarbon drainage strategies by mapping the fluid movement (CO2, water, steam) using time-lapse surveys like walkaway, 3D VSP and/or crosswell. DAS has brought a new dimension to provide vital information on injection or production evaluation, leak detection, flow behind tubing, crossflow diagnosis, and cement evaluation during production phas","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87552063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Salim, M. Thiel, Beate Nesttun Øyen, Kong Bakti Tan, J. Denichou, Vera Krissetiawati Wibowo, Desheng Zhang, K. Harms, M. Etchebes, F. Antonsen, Maria Emilia De Oliveira
The successful drilling of horizontal wells targeting reservoir zones of interest can be challenged by uncertainties in geological interpretation, identification of structure, and properties of reservoirs and fluid distribution. Optimizing the well placement of high-angle wells in order to intercept the sweet spots is crucial for the total hydrocarbon recovery in any development field. Thus, the geosteering domain was implemented to provide in real time a reservoir mapping characterization together with directional control to achieve the key performance objectives. In the past, many innovative technologies have been introduced in geosteering discipline, among them lately the deep EM directional resistivity tool that provides 1D formation resistivity mapping while drilling. However, despite the fact of delivering a multilayer mapping of the reservoir structure up to tens of meters away from wellbore, the real-time interpretation can be limited by this type of inversion. Since it is a 1D approach, these inversions map resistive boundaries on the vertical axis and assume infinite extend in all other directions. Consequently, in a complex geological setting, 1D approximation may fall short of properly describing the reservoir structure. This communication describes how the introduction of the 2D azimuthal resistivity inversions while drilling was conducted and details the various innovations required in the domains of downhole logging while drilling (LWD) measurements transmission in addition to adaptation of inversion methodology for real-time deployment, mainly through the use of high-performance cloud computing. The final enablement was the execution of automated workflows to process and deliver these advanced inversions into an integrated 3D geomodelling software within the turnaround time of drilling operations. This novel technology provides, while drilling, a better understanding of the 3D geological environment and fluid distribution with a deep depth of investigation, as well as the required information to make support for geosteering decisions for optimal well positioning. Initial field deployments were successfully conducted in horizontal wells, and three examples are presented here. Those real cases, executed with wire-drilled-pipe or mud-pulse telemetries, demonstrated the benefits of integrating 2D azimuthal inversions into the current geosteering workflow to provide a complete 3D structural understanding of the reservoir while drilling. This communication documents in detail how such an approach led to operational efficiency improvements in the form of 3D reservoir mapping in real-time, supporting a strategic change in the original well to turn toward the sweet spot, which was located sideways from the planned trajectory.
{"title":"High Performance Computing on the Cloud Successfully Deployed for 3D Geosteering and Reservoir Mapping While Drilling","authors":"D. Salim, M. Thiel, Beate Nesttun Øyen, Kong Bakti Tan, J. Denichou, Vera Krissetiawati Wibowo, Desheng Zhang, K. Harms, M. Etchebes, F. Antonsen, Maria Emilia De Oliveira","doi":"10.2118/204828-ms","DOIUrl":"https://doi.org/10.2118/204828-ms","url":null,"abstract":"\u0000 The successful drilling of horizontal wells targeting reservoir zones of interest can be challenged by uncertainties in geological interpretation, identification of structure, and properties of reservoirs and fluid distribution. Optimizing the well placement of high-angle wells in order to intercept the sweet spots is crucial for the total hydrocarbon recovery in any development field. Thus, the geosteering domain was implemented to provide in real time a reservoir mapping characterization together with directional control to achieve the key performance objectives. In the past, many innovative technologies have been introduced in geosteering discipline, among them lately the deep EM directional resistivity tool that provides 1D formation resistivity mapping while drilling.\u0000 However, despite the fact of delivering a multilayer mapping of the reservoir structure up to tens of meters away from wellbore, the real-time interpretation can be limited by this type of inversion. Since it is a 1D approach, these inversions map resistive boundaries on the vertical axis and assume infinite extend in all other directions. Consequently, in a complex geological setting, 1D approximation may fall short of properly describing the reservoir structure.\u0000 This communication describes how the introduction of the 2D azimuthal resistivity inversions while drilling was conducted and details the various innovations required in the domains of downhole logging while drilling (LWD) measurements transmission in addition to adaptation of inversion methodology for real-time deployment, mainly through the use of high-performance cloud computing. The final enablement was the execution of automated workflows to process and deliver these advanced inversions into an integrated 3D geomodelling software within the turnaround time of drilling operations.\u0000 This novel technology provides, while drilling, a better understanding of the 3D geological environment and fluid distribution with a deep depth of investigation, as well as the required information to make support for geosteering decisions for optimal well positioning. Initial field deployments were successfully conducted in horizontal wells, and three examples are presented here. Those real cases, executed with wire-drilled-pipe or mud-pulse telemetries, demonstrated the benefits of integrating 2D azimuthal inversions into the current geosteering workflow to provide a complete 3D structural understanding of the reservoir while drilling. This communication documents in detail how such an approach led to operational efficiency improvements in the form of 3D reservoir mapping in real-time, supporting a strategic change in the original well to turn toward the sweet spot, which was located sideways from the planned trajectory.","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"138 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86773176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Enrique Villarroel, G. Chochua, Alex Garro, A. Gnanavelu
Hydraulic fracturing is a well stimulation treatment that has been around since the 1940s, becoming more popular in recent years because of the unconventional hydraulic fracturing boom in North America. Between the 1990s and 2000s, the oil and gas industry found an effective way to extract hydrocarbons from formations that were previously uneconomical to produce. Consolidated unconventional formations such as shale and other tight rocks can now be artificially fractured to induce connectivity among the pores containing hydrocarbons, enabling them to easily flow into the wellbore for recovery at the surface. The method of fracturing unconventional reservoirs requires a large amount of surface equipment, continuously working to stimulate the multiple stages perforated along the horizontal section of the shale formation. The operations normally happen on a single or multi-wells pad with several sets of perforations fractured by using the zipper-fracturing methodology (Sierra & Mayerhofer, 2014). Compared with conventional hydraulic fracturing, the surface equipment must perform for extended pump time periods with only short stops for maintenance and replacement of damaged components. This paper addresses improvements made to the fracturing fluid delivery systems as an alternative to the fracturing iron traditionally used in fracture stimulation services. The improvement aims to enhance equipment reliability and simplify surface setup while reducing surface friction pressure during the hydraulic fracturing treatment.
{"title":"High-Pressure Flexible Pipe for Fracturing Fluid Delivery","authors":"Enrique Villarroel, G. Chochua, Alex Garro, A. Gnanavelu","doi":"10.2118/204530-ms","DOIUrl":"https://doi.org/10.2118/204530-ms","url":null,"abstract":"\u0000 Hydraulic fracturing is a well stimulation treatment that has been around since the 1940s, becoming more popular in recent years because of the unconventional hydraulic fracturing boom in North America.\u0000 Between the 1990s and 2000s, the oil and gas industry found an effective way to extract hydrocarbons from formations that were previously uneconomical to produce. Consolidated unconventional formations such as shale and other tight rocks can now be artificially fractured to induce connectivity among the pores containing hydrocarbons, enabling them to easily flow into the wellbore for recovery at the surface.\u0000 The method of fracturing unconventional reservoirs requires a large amount of surface equipment, continuously working to stimulate the multiple stages perforated along the horizontal section of the shale formation. The operations normally happen on a single or multi-wells pad with several sets of perforations fractured by using the zipper-fracturing methodology (Sierra & Mayerhofer, 2014). Compared with conventional hydraulic fracturing, the surface equipment must perform for extended pump time periods with only short stops for maintenance and replacement of damaged components.\u0000 This paper addresses improvements made to the fracturing fluid delivery systems as an alternative to the fracturing iron traditionally used in fracture stimulation services. The improvement aims to enhance equipment reliability and simplify surface setup while reducing surface friction pressure during the hydraulic fracturing treatment.","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84145009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohammad Rasheed Khan, S. Kalam, Abdul Asad, Rizwan Ahmed Khan, M. Kamal
Research into the use of polymers for enhanced oil recovery (EOR) processes has been going on for more than 6 decades and is now classified as a techno-commercially viable option. A comprehensive evaluation of the polymer's rheology is pivotal to the success of any polymer EOR process. Laboratory-based evaluation is critical to EOR success; however, it is also a time/capital consuming process. Consequently, any tool which can aid in optimizing lab tests design can bring in great value. Accordingly, in this study a novel predictive correlation for viscosity estimation of commonly used "FP 3330S" EOR polymer is presented through use of cutting-edge machine learning neural networks. Mathematical equation for polymer viscosity is developed using machine learning algorithms as a function of polymer concentration, NaCl concentration, and Ca2+ concentration. The measured input data was collected from the literature and sub-divided into training and test sets. A wide-ranging optimization was performed to select the best parameters for the neural network which includes the number of neurons, neuron layers, activation functions between multiple layers, weights, and bias. Furthermore, the Levenberg-Marquardt back-propagation algorithm was utilized to train the model. Finally, measured and estimated viscosities were compared based on error-analysis. Novel correlation is developed for the polymer that can be used in predictive mode. This established correlation can predict polymer viscosity when applied to the test dataset and outperforms other published models with average error in the range of 3-5% and coefficient of determination in excess of 0.95. Moreover, it is shown that neural networks are faster and relatively better than other machine learning algorithms explored in this study. The proposed correlation can map non-linear relationships between polymer viscosity and other rheological parameters such as molecular weight, polymer concentration, and cation concentration of polymer solution. Lastly, through machine learning validation approach, it was possible to examine feasibility of the proposed models which is not done by traditional empirical equations.
{"title":"Intelligent Predictor for Polymer Viscosity to Enhance Support for EOR Processes","authors":"Mohammad Rasheed Khan, S. Kalam, Abdul Asad, Rizwan Ahmed Khan, M. Kamal","doi":"10.2118/204839-ms","DOIUrl":"https://doi.org/10.2118/204839-ms","url":null,"abstract":"\u0000 Research into the use of polymers for enhanced oil recovery (EOR) processes has been going on for more than 6 decades and is now classified as a techno-commercially viable option. A comprehensive evaluation of the polymer's rheology is pivotal to the success of any polymer EOR process. Laboratory-based evaluation is critical to EOR success; however, it is also a time/capital consuming process. Consequently, any tool which can aid in optimizing lab tests design can bring in great value. Accordingly, in this study a novel predictive correlation for viscosity estimation of commonly used \"FP 3330S\" EOR polymer is presented through use of cutting-edge machine learning neural networks.\u0000 Mathematical equation for polymer viscosity is developed using machine learning algorithms as a function of polymer concentration, NaCl concentration, and Ca2+ concentration. The measured input data was collected from the literature and sub-divided into training and test sets. A wide-ranging optimization was performed to select the best parameters for the neural network which includes the number of neurons, neuron layers, activation functions between multiple layers, weights, and bias. Furthermore, the Levenberg-Marquardt back-propagation algorithm was utilized to train the model. Finally, measured and estimated viscosities were compared based on error-analysis.\u0000 Novel correlation is developed for the polymer that can be used in predictive mode. This established correlation can predict polymer viscosity when applied to the test dataset and outperforms other published models with average error in the range of 3-5% and coefficient of determination in excess of 0.95. Moreover, it is shown that neural networks are faster and relatively better than other machine learning algorithms explored in this study. The proposed correlation can map non-linear relationships between polymer viscosity and other rheological parameters such as molecular weight, polymer concentration, and cation concentration of polymer solution. Lastly, through machine learning validation approach, it was possible to examine feasibility of the proposed models which is not done by traditional empirical equations.","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85755596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Employers commonly use time-consuming screening tools or online matching engines that are driven by manual roles and predefined keywords, to search for potential job applicants. Such traditional techniques have not kept pace with the new digital revolution in machine learning and big data analytics. This paper presents advanced artificial intelligent solutions employed for ranking resumes and CV-to-Job Description matching. Open source resumes and job descriptions' documents were used to construct and validate the machine learning models in this paper. Documents were converted to images and processed via Google cloud using Optical Character Recognition algorithm (OCR) to extract text information from all resumes and job descriptions' documents, with more than 97% accuracy. Prior to modeling, the extracted text were processed via a series of Natural Language Processing (NLP) techniques by splitting/tokenizing common words, grouping together inflected form of words, i.e. lemmatization, and removal of stop words and punctuation marks. After text processing, resumes were trained using the unsupervised machine learning algorithm, Latent Dirichlet Allocation (LDA), for topic modeling and categorization. Given the type of resumes used, the algorithm was able to categorize them into 4 main job sectors: marketing and business, engineering, computer science/IT and health. Scores were assigned to each resume to represent the maximum LDA probability for ranking. Another more advanced deep learning algorithm, called Doc2Vec, was also used to train and match potential resumes to relevant job descriptions. In this model, resumes are represented by unique vectors that can be used to group similar documents, match and retrieve resumes related to a given job description document provided by HR. The similarity is measured between each resume and the given job description file to query the top job candidates. The model was tested against several job description files related to engineering, IT and human resources, and was able to identify the top-ranking resumes from over hundreds of trained resumes. This paper presents an innovative method for processing, categorizing and ranking resumes using advanced computational models empowered by the latest fourth industrial resolution technologies. This solution is beneficial to both job seekers and employers, providing efficient and unbiased data-driven method for finding top applicants for a given job.
{"title":"Talent Acquisition Process Optimization Using Machine Learning in Resumes’ Ranking and Matching to Job Descriptions","authors":"Mohammed Alghazal","doi":"10.2118/204534-ms","DOIUrl":"https://doi.org/10.2118/204534-ms","url":null,"abstract":"\u0000 Employers commonly use time-consuming screening tools or online matching engines that are driven by manual roles and predefined keywords, to search for potential job applicants. Such traditional techniques have not kept pace with the new digital revolution in machine learning and big data analytics. This paper presents advanced artificial intelligent solutions employed for ranking resumes and CV-to-Job Description matching.\u0000 Open source resumes and job descriptions' documents were used to construct and validate the machine learning models in this paper. Documents were converted to images and processed via Google cloud using Optical Character Recognition algorithm (OCR) to extract text information from all resumes and job descriptions' documents, with more than 97% accuracy. Prior to modeling, the extracted text were processed via a series of Natural Language Processing (NLP) techniques by splitting/tokenizing common words, grouping together inflected form of words, i.e. lemmatization, and removal of stop words and punctuation marks.\u0000 After text processing, resumes were trained using the unsupervised machine learning algorithm, Latent Dirichlet Allocation (LDA), for topic modeling and categorization. Given the type of resumes used, the algorithm was able to categorize them into 4 main job sectors: marketing and business, engineering, computer science/IT and health. Scores were assigned to each resume to represent the maximum LDA probability for ranking. Another more advanced deep learning algorithm, called Doc2Vec, was also used to train and match potential resumes to relevant job descriptions. In this model, resumes are represented by unique vectors that can be used to group similar documents, match and retrieve resumes related to a given job description document provided by HR. The similarity is measured between each resume and the given job description file to query the top job candidates. The model was tested against several job description files related to engineering, IT and human resources, and was able to identify the top-ranking resumes from over hundreds of trained resumes.\u0000 This paper presents an innovative method for processing, categorizing and ranking resumes using advanced computational models empowered by the latest fourth industrial resolution technologies. This solution is beneficial to both job seekers and employers, providing efficient and unbiased data-driven method for finding top applicants for a given job.","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82600456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Salaheldeen S Almasmoom, G. Santoso, Naif M Rubaie, Javier O Lagraba, David B Stonestreet, O. Faraj, A. Belowi, J. Alomoush
This paper presents a success story of deploying new technology to improve geosteering operations in an unconventional horizontal well. A new-generation logging-while-drilling (LWD) imaging tool, that provides high resolution resistivity and ultrasonic images in an oil-based mud environment, was tested while drilling a long lateral section of an unconventional horizontal well. In addition to improving the geosteering operations, this tool has proven the ability to eliminate the wireline image log requirements (resistivity and ultrasonic), hence reducing rig time significantly. The LWD bottomhole-assembly (BHA) included the following components: gamma ray (GR), density, neutron, resistivity, sonic, density imager, and the newly deployed dual imager (resistivity and ultrasonic). The dual imager component adds an additional 15-ft sub to the drilling BHA, which includes four ultrasonic sensors orthogonal to each other, and two electromagnetic sensors diametrically opposite to each other (reference figure 1). This new technology was deployed in an unconventional horizontal well to help geosteer the well in the intended zone, which led to an improvement in well placement, enhanced the evaluation of the lateral facies distribution, and allowed better identification of natural fractures. The dual images provided the necessary information for interpreting geological features, drilling induced features, and other sedimentological features, thus enhancing the multistage hydraulic fracturing stimulation design. In addition, an ultrasonic caliper was acquired while drilling the curve and lateral section, providing a full-coverage image of the borehole walls and cross-sectional borehole size. The unique BHA was designed to fulfill all the directional drilling, formation evaluation and geosteering requirements. A dynamic simulation was done to confirm the required number of stabilizers, and their respective locations within the BHA, to reduce shock and vibration, borehole tortuosity and drilling related issues, thereby improving over-all performance. Real-time drilling monitoring included torque and drag trending, back-reaming practices and buckling avoidance calculations, which were implemented to support geosteering, and for providing a smooth wellbore for subsequent wireline and completion operations run in this well. A new generation dual-image oil-based mud environment LWD tool was successfully deployed to show the multifaceted benefits of enhanced geo-steering/well placement, formation evaluation, and hydraulic fracturing design in an unconventional horizontal well. Complexities in the multifunctioning nature of the BHA were strategically optimized to support all requirements without introducing any significant risk in operation.
{"title":"Unconventional Engineering Toward Efficient Geosteering and Well Placement - Logging-While-Drilling in an Oil-Based Mud Environment","authors":"Salaheldeen S Almasmoom, G. Santoso, Naif M Rubaie, Javier O Lagraba, David B Stonestreet, O. Faraj, A. Belowi, J. Alomoush","doi":"10.2118/204870-ms","DOIUrl":"https://doi.org/10.2118/204870-ms","url":null,"abstract":"\u0000 This paper presents a success story of deploying new technology to improve geosteering operations in an unconventional horizontal well. A new-generation logging-while-drilling (LWD) imaging tool, that provides high resolution resistivity and ultrasonic images in an oil-based mud environment, was tested while drilling a long lateral section of an unconventional horizontal well. In addition to improving the geosteering operations, this tool has proven the ability to eliminate the wireline image log requirements (resistivity and ultrasonic), hence reducing rig time significantly. The LWD bottomhole-assembly (BHA) included the following components: gamma ray (GR), density, neutron, resistivity, sonic, density imager, and the newly deployed dual imager (resistivity and ultrasonic). The dual imager component adds an additional 15-ft sub to the drilling BHA, which includes four ultrasonic sensors orthogonal to each other, and two electromagnetic sensors diametrically opposite to each other (reference figure 1).\u0000 This new technology was deployed in an unconventional horizontal well to help geosteer the well in the intended zone, which led to an improvement in well placement, enhanced the evaluation of the lateral facies distribution, and allowed better identification of natural fractures. The dual images provided the necessary information for interpreting geological features, drilling induced features, and other sedimentological features, thus enhancing the multistage hydraulic fracturing stimulation design. In addition, an ultrasonic caliper was acquired while drilling the curve and lateral section, providing a full-coverage image of the borehole walls and cross-sectional borehole size.\u0000 The unique BHA was designed to fulfill all the directional drilling, formation evaluation and geosteering requirements. A dynamic simulation was done to confirm the required number of stabilizers, and their respective locations within the BHA, to reduce shock and vibration, borehole tortuosity and drilling related issues, thereby improving over-all performance. Real-time drilling monitoring included torque and drag trending, back-reaming practices and buckling avoidance calculations, which were implemented to support geosteering, and for providing a smooth wellbore for subsequent wireline and completion operations run in this well.\u0000 A new generation dual-image oil-based mud environment LWD tool was successfully deployed to show the multifaceted benefits of enhanced geo-steering/well placement, formation evaluation, and hydraulic fracturing design in an unconventional horizontal well. Complexities in the multifunctioning nature of the BHA were strategically optimized to support all requirements without introducing any significant risk in operation.","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78757887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. R. Cherdasa, T. Ariadji, B. Sapiie, Ucok W. R. Siagian
East Natuna is well known for its huge natural gas reserves with a very high CO2 content. The appearance of CO2 content in an oil and gas field is always considered as waste material and will severely affect the economic value of the field. The higher the content, the more costly the process, both technically and environmentally. In this research, the newly proposed reservoir management approach called CSSU (Carbon Sequestration Storage and Utilization) method is trying to change the paradigm of CO2 from waste material into economic materials. The novelty of this research is the combined optimization of deterministic and stochastic methods with the Particle Swarm Optimization (PSO) algorithm to answer complex and non-linear problems in the CSSU (Carbon Sequestration Storage and Utilization) method. The CSSU method is an integration of geological, geophysical, reservoir engineering and engineering economics with the determination of technical and economic optimization of the use of CO2 produced as working fluid in a power generation system that has been conditioned through an injection-production system in geological formations. The CSSU research area is located in a sedimentary basin that has a giant gas field with 70% CO2 content. The Volumetric Storage Capacity for CO2 injection process in research area is 1,749.14 BCF or 94.01 MMTon which being calculated based on static modeling considering geological, geophysical and petrophysical aspects. A combination of Compositional, Geomechanics and Thermal reservoir simulation model had been conducted to determines the Storage Injection capacity and later to prove the CSSU method in which CO2 fluids will be utilized as working fluid, 1 case was built using 2 Injection Wells and 1 CO2 fluid Production Well. The simulation results show with 1 production well the total of CO2 fluid injected from 2 Injection wells can almost double the injection total capacity up to 1,150 BCF. The utilization of supercritical CO2 fluid as working fluid can produce 55 – 133.5 MMBTU/Day or 0.67 - 1.63 MW from 1 production well for 25 years timeframe. The CSSU method is optimized by deterministic and stochastic methods using the Particle Swarm Optimization (PSO) algorithm by looking the technical and economical aspects. The technical optimization aspect is being analyzed by electricity production versus well counts. The economical optimization is being analyzed by operational expenditure saving versus well counts and electricity produced versus NPV 10%. From both aspects the 4 injector wells case and NPV 200.00 MM US$ gives the most optimum result within technically and economically. The CSSU economic model proved with CSSU scheme the economical value is being increased by 57 MMUS$ after operating cost efficiency due to the electricity savings, 92 MMUS$ due to Carbon Trading which resulting the NPV 10% is 172.77 MMUS$.
{"title":"Reservoir Management Optimization Model Employing Combination Deterministic and Probabilistic Approach for Carbon Sequestration Storage and Utilization: A Case Study from East Natuna","authors":"J. R. Cherdasa, T. Ariadji, B. Sapiie, Ucok W. R. Siagian","doi":"10.2118/204761-ms","DOIUrl":"https://doi.org/10.2118/204761-ms","url":null,"abstract":"\u0000 East Natuna is well known for its huge natural gas reserves with a very high CO2 content. The appearance of CO2 content in an oil and gas field is always considered as waste material and will severely affect the economic value of the field. The higher the content, the more costly the process, both technically and environmentally. In this research, the newly proposed reservoir management approach called CSSU (Carbon Sequestration Storage and Utilization) method is trying to change the paradigm of CO2 from waste material into economic materials.\u0000 The novelty of this research is the combined optimization of deterministic and stochastic methods with the Particle Swarm Optimization (PSO) algorithm to answer complex and non-linear problems in the CSSU (Carbon Sequestration Storage and Utilization) method. The CSSU method is an integration of geological, geophysical, reservoir engineering and engineering economics with the determination of technical and economic optimization of the use of CO2 produced as working fluid in a power generation system that has been conditioned through an injection-production system in geological formations.\u0000 The CSSU research area is located in a sedimentary basin that has a giant gas field with 70% CO2 content. The Volumetric Storage Capacity for CO2 injection process in research area is 1,749.14 BCF or 94.01 MMTon which being calculated based on static modeling considering geological, geophysical and petrophysical aspects.\u0000 A combination of Compositional, Geomechanics and Thermal reservoir simulation model had been conducted to determines the Storage Injection capacity and later to prove the CSSU method in which CO2 fluids will be utilized as working fluid, 1 case was built using 2 Injection Wells and 1 CO2 fluid Production Well. The simulation results show with 1 production well the total of CO2 fluid injected from 2 Injection wells can almost double the injection total capacity up to 1,150 BCF. The utilization of supercritical CO2 fluid as working fluid can produce 55 – 133.5 MMBTU/Day or 0.67 - 1.63 MW from 1 production well for 25 years timeframe.\u0000 The CSSU method is optimized by deterministic and stochastic methods using the Particle Swarm Optimization (PSO) algorithm by looking the technical and economical aspects. The technical optimization aspect is being analyzed by electricity production versus well counts. The economical optimization is being analyzed by operational expenditure saving versus well counts and electricity produced versus NPV 10%. From both aspects the 4 injector wells case and NPV 200.00 MM US$ gives the most optimum result within technically and economically. The CSSU economic model proved with CSSU scheme the economical value is being increased by 57 MMUS$ after operating cost efficiency due to the electricity savings, 92 MMUS$ due to Carbon Trading which resulting the NPV 10% is 172.77 MMUS$.","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88344944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Elsayed, H. Kwak, A. El-Husseiny, Mohamed Mahmoud
Tortuosity, in general characterizes the geometric complexity of porous media. It is considered as one of the key factors in characterizing the heterogonous structure of porous media and has significant implications for macroscopic transport flow properties. There are four widely used definitions of tortuosity, that are relevant to different fields from hydrology to chemical and petroleum engineering, which are: geometric, hydraulic, electrical, and diffusional. Recent work showed that hydraulic, electrical and diffusional tortuosity values are roughly equal to each other in glass beads. Nevertheless, the relationship between the different definitions of Tortuosity in natural rocks is not well understood yet. Understanding the relationship between the different Tortuosity definitions in rocks can help to establish a workflow that allows us to estimate other types from the available technique. Therefore, the objective of this study is to investigate the relationship between the different tortuosity definitions in natural rocks. A major focus of this work is to utilize Nuclear Magnetic Resonance (NMR) technology to estimate Tortuosity. Such technique has been traditionally used to obtain diffusional tortuosity which can be defined as the ratio of the free fluid self-diffusion coefficient to the restricted fluid self-diffusion coefficient inside the porous media. In this study, the following techniques were used to quantify hydraulic, electrical, and diffusional tortuosity respectively on the same rock sample: (1) Microcomputed Tomography 3D imaging (2) Four-Electrodes resistivity measurements (3) Pulsed-Field Gradient Nuclear Magnetic Resonance (PFG NMR). PFG NMR is very powerful, non-invasive technique employed to measure the self-diffusion coefficient for free and confined fluids. The measurements were done based on two carbonate rock core plugs characterized by variable porosity, permeability and texture complexity. Results show that PFG NMR can be applied directionally to quantify the pore network anisotropy created by fractures. For both samples, hydraulic tortuosity was found to have the lowest magnitude compared to geometric, electrical and diffusional tortuosity. This could be explained by the more heterogeneous microstructure of carbonate rocks. NMR technique has however advantages over the other electrical and imaging techniques for tortuosity characterization: it is faster, non-destructive and can be applied in well bore environment (in situ). We therefore conclude that NMR can provide a tool for estimating not only diffusional tortuosity but also for indirectly obtaining hydraulic and electrical tortuosity.
{"title":"The Measurement of Tortuosity of Porous Media Using Imaging, Electrical Measurements, and Pulsed Field Gradient NMR","authors":"M. Elsayed, H. Kwak, A. El-Husseiny, Mohamed Mahmoud","doi":"10.2118/204629-ms","DOIUrl":"https://doi.org/10.2118/204629-ms","url":null,"abstract":"\u0000 Tortuosity, in general characterizes the geometric complexity of porous media. It is considered as one of the key factors in characterizing the heterogonous structure of porous media and has significant implications for macroscopic transport flow properties. There are four widely used definitions of tortuosity, that are relevant to different fields from hydrology to chemical and petroleum engineering, which are: geometric, hydraulic, electrical, and diffusional. Recent work showed that hydraulic, electrical and diffusional tortuosity values are roughly equal to each other in glass beads. Nevertheless, the relationship between the different definitions of Tortuosity in natural rocks is not well understood yet. Understanding the relationship between the different Tortuosity definitions in rocks can help to establish a workflow that allows us to estimate other types from the available technique. Therefore, the objective of this study is to investigate the relationship between the different tortuosity definitions in natural rocks. A major focus of this work is to utilize Nuclear Magnetic Resonance (NMR) technology to estimate Tortuosity. Such technique has been traditionally used to obtain diffusional tortuosity which can be defined as the ratio of the free fluid self-diffusion coefficient to the restricted fluid self-diffusion coefficient inside the porous media.\u0000 In this study, the following techniques were used to quantify hydraulic, electrical, and diffusional tortuosity respectively on the same rock sample: (1) Microcomputed Tomography 3D imaging (2) Four-Electrodes resistivity measurements (3) Pulsed-Field Gradient Nuclear Magnetic Resonance (PFG NMR). PFG NMR is very powerful, non-invasive technique employed to measure the self-diffusion coefficient for free and confined fluids. The measurements were done based on two carbonate rock core plugs characterized by variable porosity, permeability and texture complexity.\u0000 Results show that PFG NMR can be applied directionally to quantify the pore network anisotropy created by fractures. For both samples, hydraulic tortuosity was found to have the lowest magnitude compared to geometric, electrical and diffusional tortuosity. This could be explained by the more heterogeneous microstructure of carbonate rocks. NMR technique has however advantages over the other electrical and imaging techniques for tortuosity characterization: it is faster, non-destructive and can be applied in well bore environment (in situ). We therefore conclude that NMR can provide a tool for estimating not only diffusional tortuosity but also for indirectly obtaining hydraulic and electrical tortuosity.","PeriodicalId":11320,"journal":{"name":"Day 3 Tue, November 30, 2021","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89140373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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