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The present study interprets the subsurface structure of the Rajian area using seismic sections and the identification of hydrocarbon-bearing zones using petrophysical analysis. The Rajian area lies within the Upper Indus Basin in the southeast (SE) of the Salt Range Potwar Foreland Basin. The marked horizons are identified using formation tops from two vertical wells. Seismic interpretation of the given 2D seismic data reveals that the study area has undergone severe distortion illustrated by thrusts and back thrusts, forming a triangular zone within the subsurface. The final trend of those structures is northwest–southeast (NW–SE), indicating that the area is part of the compressional regime. The zones interpreted by the study of hydrocarbon potential include Sakessar limestone and Khewra sandstone. Due to the unavailability of a petrophysics log within the desired investigation depths, lithology cross-plots were used for the identification of two potential hydrocarbon-bearing zones in one well at depths of 3740–3835 m (zone 1) and 4015–4100 m (zone 2). The results show that zone 2 is almost devoid of hydrocarbons, while zone 1 has an average hydrocarbon saturation of about 11%.
Naveed Ahmad; Sikandar Khan; Eisha Fatima Noor; Zhihui Zou; Abdullatif Al-Shuhail. Seismic Data Interpretation and Identification of Hydrocarbon-Bearing Zones of Rajian Area, Pakistan. Minerals 2021, 11, 891 .
AMA StyleNaveed Ahmad, Sikandar Khan, Eisha Fatima Noor, Zhihui Zou, Abdullatif Al-Shuhail. Seismic Data Interpretation and Identification of Hydrocarbon-Bearing Zones of Rajian Area, Pakistan. Minerals. 2021; 11 (8):891.
Chicago/Turabian StyleNaveed Ahmad; Sikandar Khan; Eisha Fatima Noor; Zhihui Zou; Abdullatif Al-Shuhail. 2021. "Seismic Data Interpretation and Identification of Hydrocarbon-Bearing Zones of Rajian Area, Pakistan." Minerals 11, no. 8: 891.
Well logging is a significant procedure that assists geophysicists and geologists with making predictions regarding boreholes and efficiently utilizing and optimizing the drilling process. The current study area is positioned in the Punjab Territory of Pakistan, and the geographic coordinates are 30020′10 N and 70043′30 E. The objective of the current research work was to interpret the subsurface structure and reservoir characteristics of the Kabirwala area Tola (01) well, which is located in the Punjab platform, Central Indus Basin, utilizing 2D seismic and well log data. Formation evaluation for hydrocarbon potential using the reservoir properties is performed in this study. For the marked zone of interest, the study also focuses on evaluating the average water saturation, average total porosity, average effective porosity, and net pay thickness. The results of the study show a spotted horizon stone with respect to time and depth as follows: Dunghan formation, 0.9 s and 1080.46 m; Cretaceous Samana Suk formation, 0.96 s and 1174.05 m; Datta formation, 1.08 s and 1400 m; and Warcha formation, 1.24 s and 1810 m. Based on the interpretation of well logs, the purpose of petrophysical analysis was to identify hydrocarbon-bearing zones in the study area. Gamma ray, spontaneous potential, resistivity, neutron, and density log data were utilized. The high zone present in the east–west part of the contour maps may be a possible location of hydrocarbon entrapment, which is further confirmed by the presence of the Tola-01 well.
Naveed Ahmad; Sikandar Khan; Abdullatif Al-Shuhail. Seismic Data Interpretation and Petrophysical Analysis of Kabirwala Area Tola (01) Well, Central Indus Basin, Pakistan. Applied Sciences 2021, 11, 2911 .
AMA StyleNaveed Ahmad, Sikandar Khan, Abdullatif Al-Shuhail. Seismic Data Interpretation and Petrophysical Analysis of Kabirwala Area Tola (01) Well, Central Indus Basin, Pakistan. Applied Sciences. 2021; 11 (7):2911.
Chicago/Turabian StyleNaveed Ahmad; Sikandar Khan; Abdullatif Al-Shuhail. 2021. "Seismic Data Interpretation and Petrophysical Analysis of Kabirwala Area Tola (01) Well, Central Indus Basin, Pakistan." Applied Sciences 11, no. 7: 2911.
The semiautomatic seismic refraction supervirtual interferometry (SVI) algorithm has been developed to improve the conventional SVI method. The conventional SVI method uses convolution techniques and involves the raw trace, which reintroduces noise back into the enhanced trace. However, the semiautomatic method uses a first-arrival reference picked from a raw trace to compute the arrival times of all enhanced virtual traces. The semiautomatic SVI method has been extended recently from 2D to 3D geometry and applied on a synthetic 3D seismic data set using the raw traces of only one inline. We have developed a case study of the semiautomatic 3D SVI method by applying the algorithm on an active seismic refraction data set that consists of 82,944 raw traces from 288 shot gathers that use an accelerated weight drop source. Due to possible differences in the source wavelet among shots, the semiautomatic 3D SVI method is applied on the 288 raw traces from each shot gather separately. The SVI technique generates 41,328 distinct correlograms from one shot, which results in the production of a trace with a much better signal-to-noise ratio.
Paul Edigbue; Abdullatif Al-Shuhail; Sherif M. Hanafy. Three-dimensional supervirtual seismic refraction interferometry: A case study in western Saudi Arabia. GEOPHYSICS 2021, 86, B123 -B133.
AMA StylePaul Edigbue, Abdullatif Al-Shuhail, Sherif M. Hanafy. Three-dimensional supervirtual seismic refraction interferometry: A case study in western Saudi Arabia. GEOPHYSICS. 2021; 86 (3):B123-B133.
Chicago/Turabian StylePaul Edigbue; Abdullatif Al-Shuhail; Sherif M. Hanafy. 2021. "Three-dimensional supervirtual seismic refraction interferometry: A case study in western Saudi Arabia." GEOPHYSICS 86, no. 3: B123-B133.
The Rub’ Al-Khali basin in Saudi Arabia remains unexplored and lacks data availability due to its remoteness and the challenging nature of its terrain. Thus far, there are neither digital geologic models nor synthetic seismic data from this specific area accessible for testing research techniques and analysis. In this study, we build a 2D viscoelastic model of the eastern part of the Rub’ Al-Khali basin and generate a corresponding dual-component seismic data set. We compile high-resolution depth models of compressional- and shear-wave velocities, density, as well as compressional- and shear-wave quality factors from published data. The compiled models span Neoproterozoic basement up to Quaternary sand dunes. We then use the finite-difference technique to model the propagation of seismic waves in the compiled viscoelastic medium of eastern Rub’ Al-Khali desert. In particular, we generate vertical and horizontal components of the shot gathers with accuracy to the fourth and second orders in space and time, respectively. The viscoelastic models and synthetic seismic datasets are made available in an open-source site for prospective re-searchers who desire to use them for their research. Users of these datasets are urged to make their findings also accessible to the geoscience community as a way of keeping track of developments related to the Rub’ Al-Khali desert.
Septriandi Chan; Paul Edigbue; Sikandar Khan; Abdul Ashadi; Abdullatif Al-Shuhail. Viscoelastic Model and Synthetic Seismic Data of Eastern Rub’Al-Khali. Applied Sciences 2021, 11, 1401 .
AMA StyleSeptriandi Chan, Paul Edigbue, Sikandar Khan, Abdul Ashadi, Abdullatif Al-Shuhail. Viscoelastic Model and Synthetic Seismic Data of Eastern Rub’Al-Khali. Applied Sciences. 2021; 11 (4):1401.
Chicago/Turabian StyleSeptriandi Chan; Paul Edigbue; Sikandar Khan; Abdul Ashadi; Abdullatif Al-Shuhail. 2021. "Viscoelastic Model and Synthetic Seismic Data of Eastern Rub’Al-Khali." Applied Sciences 11, no. 4: 1401.
The release of large quantities of CO2 into the atmosphere is one of the major causes of global warming. The most viable method to control the level of CO2 in the atmosphere is to capture and permanently sequestrate the excess amount of CO2 in subsurface geological reservoirs. The injection of CO2 gives rise to pore pressure buildup. It is crucial to monitor the rising pore pressure in order to prevent the potential failure of the reservoir and the subsequent leakage of the stored CO2 into the overburden layers, and then back to the atmosphere. In this paper, the Minjur sandstone reservoir in eastern Saudi Arabia was considered for establishing a coupled geomechanical model and performing the corresponding stability analysis. During the geomechanical modeling process, the fault passing through the Minjur and Marrat layers was also considered. The injection-induced pore-pressure and ground uplift profiles were calculated for the case of absence of a fault across the reservoir, as well as the case with a fault. The stability analysis was performed using the Mohr–Coulomb failure criterion. In the current study, the excessive increase in pore pressure, in the absence of geological faults, moved the reservoir closer to the failure envelope, but in the presence of geological faults, the reservoir reached to the failure envelope and the faults were activated. The developed geomechanical model provided estimates for the safe injection parameters of CO2 based on the magnitudes of the reservoir pore pressure and stresses in the reservoir.
Sikandar Khan; Yehia Khulief; Abdullatif Al-Shuhail; Salem Bashmal; Naveed Iqbal. The Geomechanical and Fault Activation Modeling during CO2 Injection into Deep Minjur Reservoir, Eastern Saudi Arabia. Sustainability 2020, 12, 9800 .
AMA StyleSikandar Khan, Yehia Khulief, Abdullatif Al-Shuhail, Salem Bashmal, Naveed Iqbal. The Geomechanical and Fault Activation Modeling during CO2 Injection into Deep Minjur Reservoir, Eastern Saudi Arabia. Sustainability. 2020; 12 (23):9800.
Chicago/Turabian StyleSikandar Khan; Yehia Khulief; Abdullatif Al-Shuhail; Salem Bashmal; Naveed Iqbal. 2020. "The Geomechanical and Fault Activation Modeling during CO2 Injection into Deep Minjur Reservoir, Eastern Saudi Arabia." Sustainability 12, no. 23: 9800.
We have addressed the problem of measuring the compressional wave velocity at a very shallow depth in unconsolidated dune sand. Because the overburden stress is very small at shallow depths, the respective velocity is small and the seismic signal is weak. This is why such data are scarce, in the lab and in the field. Our approach is to stage a high-resolution seismic experiment with a dense geophone line with spacing varying between 10 and 25 cm, allowing us to produce a velocity-depth relation in the upper 1 m interval. These results are combined with another survey in which the geophone spacing is 2 m and the dominant frequency is an order of magnitude lower than in the first survey. The latter results give us the velocity profile in the deeper interval between 1 and 7 m, down to the base of the dune. The velocity rapidly increases from about 48 m/s in the first few centimeters to 231 m/s at 1 m depth and then gradually increases to 425 m/s at 7 m depth. This is the first time when such a low velocity has been recorded at extremely shallow depths in sand in situ. The velocity profile thus generated is statistically fitted with a simple analytical equation. Our velocity values are higher than those published previously for beach sand. We find that using replacement or tomogram velocities instead of an accurately measured velocity profile may result in 23%–44% error in the static correction.
Sherif M. Hanafy; Ammar El-Husseiny; Mohammed Benaafi; Abdullatif Al-Shuhail; Jack Dvorkin. P-wave velocity profile at very shallow depths in sand dunes. GEOPHYSICS 2020, 85, U129 -U137.
AMA StyleSherif M. Hanafy, Ammar El-Husseiny, Mohammed Benaafi, Abdullatif Al-Shuhail, Jack Dvorkin. P-wave velocity profile at very shallow depths in sand dunes. GEOPHYSICS. 2020; 85 (5):U129-U137.
Chicago/Turabian StyleSherif M. Hanafy; Ammar El-Husseiny; Mohammed Benaafi; Abdullatif Al-Shuhail; Jack Dvorkin. 2020. "P-wave velocity profile at very shallow depths in sand dunes." GEOPHYSICS 85, no. 5: U129-U137.
The excessive burning of the fossil fuels has caused severe global climatic changes such as increasing the global temperature, causing initiation of the wild fire, rising the sea level, increasing the floods, storms, amount of rain and snow. One of the effective global mitigation strategies is sequestration of huge quantity of CO2 deep below the ground level for a long period of time. An important issue is to ensure the permanency and safety of the sequestration process due to the associated pore-pressure buildup. It is necessary to have correct estimates of the pore-pressure buildup, ground uplift and re-activation of any existing fault during the process of CO2 injection and long-term storage. In this investigation, the effects of reservoir size and boundary conditions are investigated by means of geomechanical modeling of the deep Biyadh sandstone reservoir in Saudi Arabia. Currently, carbon dioxide is not injected into the actual Biyadh reservoir. In this investigative modeling, CO2 is injected for an injection period of ten years using a single injection well at the center of the reservoir. The developed modeling scheme for a single injection well has been extended further to include multiple injection wells. For multiple injection wells, the reservoir size and locations of injection wells are varied to evaluate their effect on the pore-pressure buildup and ground uplift. The reservoir stability analysis has been performed using Mohr–Coulomb failure criterion for both small and large reservoir models, with the same injection parameters. The simulation results demonstrated that pressure buildup and ground uplift are relatively higher for reservoirs with small sizes and closed boundaries; while in the case of large sizes and open boundaries, the pore-pressure buildup and ground uplift are relatively lower. Moreover, the effect of the reservoir size and boundary conditions on the reactivation of faults during CO2 injection has been evaluated. The stability analysis performed in this study shows that injecting CO2 into larger size reservoir is safer as compared to smaller size reservoir. Injecting CO2 with multiple injection wells will cause pore-pressure buildup of huge magnitudes. The modeling results show that suggesting a representative volume for the reservoir during CO2 injection can under-estimate the pore-pressure buildup and fault re-activation that can cause the reservoir failure and leakage of the stored CO2.
Sikandar Khan; Y. A. Khulief; A. A. Al-Shuhail. Effects of reservoir size and boundary conditions on pore-pressure buildup and fault reactivation during CO2 injection in deep geological reservoirs. Environmental Earth Sciences 2020, 79, 1 -23.
AMA StyleSikandar Khan, Y. A. Khulief, A. A. Al-Shuhail. Effects of reservoir size and boundary conditions on pore-pressure buildup and fault reactivation during CO2 injection in deep geological reservoirs. Environmental Earth Sciences. 2020; 79 (12):1-23.
Chicago/Turabian StyleSikandar Khan; Y. A. Khulief; A. A. Al-Shuhail. 2020. "Effects of reservoir size and boundary conditions on pore-pressure buildup and fault reactivation during CO2 injection in deep geological reservoirs." Environmental Earth Sciences 79, no. 12: 1-23.
The Middle East is one of the world's most prolific regions in terms of petroleum reserves and production. It accounts for one-third of global oil production, one-sixth of gas production, about half of proved oil reserves, and two-fifths of proved gas reserves. Recent discoveries of unconventional resources have added even more reserves to the area's vast resources. Historically, many of the conventional fields in the Middle East were discovered by using conventional geophysical exploration methods. The continuing search for conventional and unconventional reservoirs has led to a rapid advancement of geophysical technologies in data acquisition, processing, and interpretation. These advanced technologies are aimed at solving region-specific challenges in defining the complexity of the near surface and subsurface. This is evidenced by the increasing activities in the development and application of new geophysical technologies in the exploration, development, and production of petroleum resources.
Abdullatif Al-Shuhail; Youcef Bouzidi; Saleh Al-Dossary; Yongyi Li. Introduction to this special section: Middle East. GEOPHYSICS 2020, 39, 381 -381.
AMA StyleAbdullatif Al-Shuhail, Youcef Bouzidi, Saleh Al-Dossary, Yongyi Li. Introduction to this special section: Middle East. GEOPHYSICS. 2020; 39 (6):381-381.
Chicago/Turabian StyleAbdullatif Al-Shuhail; Youcef Bouzidi; Saleh Al-Dossary; Yongyi Li. 2020. "Introduction to this special section: Middle East." GEOPHYSICS 39, no. 6: 381-381.
In arid countries such as Saudi Arabia, aeolian sand often covers a large area of the country. Understanding the variations of sand properties in dunes, including grain size, sorting, mineral composition and water content, can be important for groundwater recharge, environmental, and construction applications. Earlier studies examined properties of sand dunes by collecting samples from the surface. This study aims to investigate variations of sand properties within a Barchan sand dune in the coastal area of Saudi Arabia, by collecting samples and measurements from two vertically drilled boreholes up to the ground water level; one drilled in the dune crest and another one in the limb. Representative samples were collected and analyzed for their texture parameters, water content, and mineralogy. Electrical resistivity survey data was also acquired to map water content variation in the dune limb, and for comparison with well bore data. The reported results show no vertical variations in grain size or sorting in the dune crest. In contrast, the upper 0.5 m of the dune limb shows a relatively poorer sorting than found in deeper parts of the dune. Laterally, no variations in minerology were observed between crest and limb sands while grain size tended to be slightly coarser in the dune limb compared to the crest. Regarding the water content, it was found to vary vertically, probably due to previous cycles of rainfall infiltration through the sand body. Such observed variation in water content is consistent with the measured resistivity profile which could clearly identify the water table and areas with higher water content. This study concludes that beyond the upper 0.5 m, the Barchan sand dune body can be treated as a homogeneous medium in terms of mineralogy and sorting while grain size increases slightly toward the limb side.
Mohammed Benaafi; Sherif Hanafy; Abdullatif Al-Shuhail; Ammar El-Husseiny; Jack Dvorkin. Integrated Geological, Hydrogeological, and Geophysical Investigations of a Barchan Sand Dune in the Eastern Region of Saudi Arabia. Water 2020, 12, 682 .
AMA StyleMohammed Benaafi, Sherif Hanafy, Abdullatif Al-Shuhail, Ammar El-Husseiny, Jack Dvorkin. Integrated Geological, Hydrogeological, and Geophysical Investigations of a Barchan Sand Dune in the Eastern Region of Saudi Arabia. Water. 2020; 12 (3):682.
Chicago/Turabian StyleMohammed Benaafi; Sherif Hanafy; Abdullatif Al-Shuhail; Ammar El-Husseiny; Jack Dvorkin. 2020. "Integrated Geological, Hydrogeological, and Geophysical Investigations of a Barchan Sand Dune in the Eastern Region of Saudi Arabia." Water 12, no. 3: 682.
In this chapter, we consider the case when performing EPS on noisy section with impulse noise. Vector median filter has been applied to dip vector smoothing and prestack source separation, etc. However, in these applications, the local structure is not fully explored.
Abdullatif Al-Shuhail; Saleh Al-Dossary. Advanced Topics. Geostatistical Methods for Reservoir Geophysics 2019, 153 -170.
AMA StyleAbdullatif Al-Shuhail, Saleh Al-Dossary. Advanced Topics. Geostatistical Methods for Reservoir Geophysics. 2019; ():153-170.
Chicago/Turabian StyleAbdullatif Al-Shuhail; Saleh Al-Dossary. 2019. "Advanced Topics." Geostatistical Methods for Reservoir Geophysics , no. : 153-170.
The filters in previous chapters utilized some features of the image and/or noise to attenuate noise.
Abdullatif Al-Shuhail; Saleh Al-Dossary. Denoising Using Signal Model. Geostatistical Methods for Reservoir Geophysics 2019, 129 -151.
AMA StyleAbdullatif Al-Shuhail, Saleh Al-Dossary. Denoising Using Signal Model. Geostatistical Methods for Reservoir Geophysics. 2019; ():129-151.
Chicago/Turabian StyleAbdullatif Al-Shuhail; Saleh Al-Dossary. 2019. "Denoising Using Signal Model." Geostatistical Methods for Reservoir Geophysics , no. : 129-151.
It is well-known that the classical mean filter is optimal for estimating the mean value of a sequence of random numbers taken from white Gaussian distributed source.
Abdullatif Al-Shuhail; Saleh Al-Dossary. Robust Filter—Dealing with Impulse Noise. Geostatistical Methods for Reservoir Geophysics 2019, 61 -80.
AMA StyleAbdullatif Al-Shuhail, Saleh Al-Dossary. Robust Filter—Dealing with Impulse Noise. Geostatistical Methods for Reservoir Geophysics. 2019; ():61-80.
Chicago/Turabian StyleAbdullatif Al-Shuhail; Saleh Al-Dossary. 2019. "Robust Filter—Dealing with Impulse Noise." Geostatistical Methods for Reservoir Geophysics , no. : 61-80.
This chapter intends to provide background knowledge and set notation for later chapters. Mean filter and median filter are two most commonly used filters for suppressing seismic noise.
Abdullatif Al-Shuhail; Saleh Al-Dossary. Classical Filters. Geostatistical Methods for Reservoir Geophysics 2019, 51 -60.
AMA StyleAbdullatif Al-Shuhail, Saleh Al-Dossary. Classical Filters. Geostatistical Methods for Reservoir Geophysics. 2019; ():51-60.
Chicago/Turabian StyleAbdullatif Al-Shuhail; Saleh Al-Dossary. 2019. "Classical Filters." Geostatistical Methods for Reservoir Geophysics , no. : 51-60.
In this chapter, we go one-step further from last chapter, i.e., from structure preservation to structure enhancement. The flow-like structures are commonly observed in seismic images. These structures usually are related to subsurface structures, such as channel, curved stratum. So, enhancing these structures and making it more prominent may help the interpreter to pick important information. To enhance the local structure while suppressing noise, the noise suppressing filter must be structure-aware. Local orientation and its coherence are fundamental to the formation of structures, so it should be analyzed and incorporated into the filter. Furthermore, geometry of the image surface can also be utilized. To promote the effect of structure enhancement, the structure-aware filters are usually iterated several times.
Abdullatif Al-Shuhail; Saleh Al-Dossary. Structure-Enhancing Filtering. Geostatistical Methods for Reservoir Geophysics 2019, 89 -127.
AMA StyleAbdullatif Al-Shuhail, Saleh Al-Dossary. Structure-Enhancing Filtering. Geostatistical Methods for Reservoir Geophysics. 2019; ():89-127.
Chicago/Turabian StyleAbdullatif Al-Shuhail; Saleh Al-Dossary. 2019. "Structure-Enhancing Filtering." Geostatistical Methods for Reservoir Geophysics , no. : 89-127.
The main objective of the seismic exploration method is to map the structure of subsurface formations to infer the existence of possible petroleum traps.
Abdullatif Al-Shuhail; Saleh Al-Dossary. Introduction to Seismic Exploration. Geostatistical Methods for Reservoir Geophysics 2019, 1 -39.
AMA StyleAbdullatif Al-Shuhail, Saleh Al-Dossary. Introduction to Seismic Exploration. Geostatistical Methods for Reservoir Geophysics. 2019; ():1-39.
Chicago/Turabian StyleAbdullatif Al-Shuhail; Saleh Al-Dossary. 2019. "Introduction to Seismic Exploration." Geostatistical Methods for Reservoir Geophysics , no. : 1-39.
In previous chapters, we deal with the problem of attenuating or removing different type of noise from image. A side effect of noise removal is the damage of image structure, such as edges and lines. In this chapter, we consider the noise removal and structure preservation at the same time.
Abdullatif Al-Shuhail; Saleh Al-Dossary. Edge-Preserving Smoothing. Geostatistical Methods for Reservoir Geophysics 2019, 81 -88.
AMA StyleAbdullatif Al-Shuhail, Saleh Al-Dossary. Edge-Preserving Smoothing. Geostatistical Methods for Reservoir Geophysics. 2019; ():81-88.
Chicago/Turabian StyleAbdullatif Al-Shuhail; Saleh Al-Dossary. 2019. "Edge-Preserving Smoothing." Geostatistical Methods for Reservoir Geophysics , no. : 81-88.
After studying this chapter, you should be able to:Understand the various types of noise that appear in seismic images and volumes.Simulate some commonly used type of noise.Estimate noise parameters.
Abdullatif Al-Shuhail; Saleh Al-Dossary. Noise in Seismic Image. Geostatistical Methods for Reservoir Geophysics 2019, 41 -50.
AMA StyleAbdullatif Al-Shuhail, Saleh Al-Dossary. Noise in Seismic Image. Geostatistical Methods for Reservoir Geophysics. 2019; ():41-50.
Chicago/Turabian StyleAbdullatif Al-Shuhail; Saleh Al-Dossary. 2019. "Noise in Seismic Image." Geostatistical Methods for Reservoir Geophysics , no. : 41-50.
In this study, a data-driven linear filtering method is proposed to recover microseismic signals from noisy data/observations. The proposed method is based on the statistics of the background noise and the observation, which are directly extracted from the recorded data, obviating prior statistical knowledge of the microseismic source signal. The proposed method does not depend on any specific underlying noise statistics; therefore, it works for any type of noise, e.g. uncorrelated (random/white Gaussian), temporally correlated and spatially correlated noises. Consequently, the proposed method is suitable for microquake data sets that are recorded in contrastive noise environments. A mathematical analysis is presented to interpret the proposed method in two different ways. Furthermore, a number of practical concerns are discussed and their corresponding solutions are introduced. Finally, the proposed scheme is evaluated using both field and synthetic data sets and the experimental results show a reasonable and robust performance.
Naveed Iqbal; Bo Liu; Mohamed Deriche; Abdullatif Al-Shuhail; Sanlinn Kaka; Azzedine Zerguine. Blind noise estimation and denoising filter for recovery of microquake signals. Exploration Geophysics 2019, 50, 502 -513.
AMA StyleNaveed Iqbal, Bo Liu, Mohamed Deriche, Abdullatif Al-Shuhail, Sanlinn Kaka, Azzedine Zerguine. Blind noise estimation and denoising filter for recovery of microquake signals. Exploration Geophysics. 2019; 50 (5):502-513.
Chicago/Turabian StyleNaveed Iqbal; Bo Liu; Mohamed Deriche; Abdullatif Al-Shuhail; Sanlinn Kaka; Azzedine Zerguine. 2019. "Blind noise estimation and denoising filter for recovery of microquake signals." Exploration Geophysics 50, no. 5: 502-513.
Subsurface cavities occur naturally by dissolution of carbonates and evaporites or by human action, such as the construction of tunnels and tombs. They can be filled with air, water, sediments, or a combination. Gravity and ground penetrating radar (GPR) methods have been used widely to determine the location and size of subsurface cavities. The objective of this study is to present a quantitative approach to estimate the porosity and water saturation of cavity-filling materials from GPR and gravity measurements. The approach uses appropriate rock-physics models of the dielectric permittivity and density of a shallow cavity and estimates the porosity and water saturation inside the cavity by solving the two model equations simultaneously for these two variables. We test the proposed method using synthetic GPR and gravity data sets corresponding to three spherical-cavity models: air-filled, water-filled, and a partially-saturated sand filling. Results show that the method is accurate in retrieving the correct porosity within 0.76% error and water saturation within 2.4% error. We also apply the method on three published case studies over air-filled rectangular cavities. We found that the proposed method estimated the correct porosity and water saturation in one study but failed with the other studies. However, when the procedure was repeated with gravity values calculated from parameters reported in these studies, the proposed method estimated the correct porosity and water saturation accurately.
Fathi M. Abdullah; Abdullatif Al-Shuhail; Oluseun Sanuade. Characterization of Subsurface Cavities using Gravity and Ground Penetrating Radar. Journal of Environmental and Engineering Geophysics 2019, 24, 265 -276.
AMA StyleFathi M. Abdullah, Abdullatif Al-Shuhail, Oluseun Sanuade. Characterization of Subsurface Cavities using Gravity and Ground Penetrating Radar. Journal of Environmental and Engineering Geophysics. 2019; 24 (2):265-276.
Chicago/Turabian StyleFathi M. Abdullah; Abdullatif Al-Shuhail; Oluseun Sanuade. 2019. "Characterization of Subsurface Cavities using Gravity and Ground Penetrating Radar." Journal of Environmental and Engineering Geophysics 24, no. 2: 265-276.
Ghawar is the largest and most prolific oil field in the world. Yet, no digital geological models or synthetic seismic data of this important field are publicly available for testing algorithms to image, analyze, and understand its complex and interesting attributes. We construct a 2D viscoelastic model of the Ghawar field and calculate a corresponding multi-component synthetic seismic data set. The P-wave velocities and densities of the entire stratigraphic column from pre-Cambrian basement to present-day sediments were compiled from public sources. The S-wave velocities were calculated from the P-wave velocities using empirical VS–VP relations established from well logs. An empirical formula was also used to estimate the P-wave and S-wave quality factors from the P-wave and S-wave velocities, respectively. Vertical and horizontal components of viscoelastic seismic shot records were generated using a finite-difference algorithm accurate to the 4th order in space and 2nd order in time. We share the models and seismic data sets publicly hoping that this will motivate interested researchers to test their research ideas, which in turn will help advance the leading edge in hydrocarbon exploration seismology. Finally, we encourage researchers, who will use the models and data sets, to contribute to the geoscience community by sharing their results publicly as well.
Abdullatif A. Al-Shuhail; Abdullah A. Alshuhail; Yehia A. Khulief; Syed Abdul Salam; Septriandi A. Chan; Abdul Latif Ashadi; Ayman F. Al-Lehyani; Adnan M. Almubarak; Mohammed Zia Ullah Khan; Sikandar Khan; Salem G. AlJuhani; Khalid A. Abdulrahman. KFUPM Ghawar digital viscoelastic seismic model. Arabian Journal of Geosciences 2019, 12, 245 .
AMA StyleAbdullatif A. Al-Shuhail, Abdullah A. Alshuhail, Yehia A. Khulief, Syed Abdul Salam, Septriandi A. Chan, Abdul Latif Ashadi, Ayman F. Al-Lehyani, Adnan M. Almubarak, Mohammed Zia Ullah Khan, Sikandar Khan, Salem G. AlJuhani, Khalid A. Abdulrahman. KFUPM Ghawar digital viscoelastic seismic model. Arabian Journal of Geosciences. 2019; 12 (7):245.
Chicago/Turabian StyleAbdullatif A. Al-Shuhail; Abdullah A. Alshuhail; Yehia A. Khulief; Syed Abdul Salam; Septriandi A. Chan; Abdul Latif Ashadi; Ayman F. Al-Lehyani; Adnan M. Almubarak; Mohammed Zia Ullah Khan; Sikandar Khan; Salem G. AlJuhani; Khalid A. Abdulrahman. 2019. "KFUPM Ghawar digital viscoelastic seismic model." Arabian Journal of Geosciences 12, no. 7: 245.