Untitled

Slob, Evert; Groenenboom, Jeroen; Fokkema, J.T.

doi:10.1023/a:1023007313060

Cited by 18 publications

(3 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By moving back to their original position and setting a coal velocity of 0.14 m/ns in the "Stolt F-K Migration" tool, the form of the reflectors and the actual positions of the reflecting limits were restored [30]. In the last phase, a "deconvolution tool" was used to eliminate the influences of the surface wavelet in order to better understand GPR profiles as an image of the Earth's subsurface [31,32].…”

Section: Geophysical Studiesmentioning

confidence: 99%

Integrated Geophysical and Geochemical Analyses for Assessment of Potential Coal Prospects in Tirah Area, Khyber Pakhtunkhwa, Pakistan

Sajid,

Ali,

Khan

et al. 2023

Energies

View full text Add to dashboard Cite

This study presents a comprehensive investigation of the Paleocene coal in the Tirah area, District Khyber, Khyber Pakhtunkhwa, Pakistan, utilizing onsite Electrical Resistivity Tomography (ERT) and Ground Penetrating Radar (GPR) experiments combined with geochemical analyses of obtained coal-rock samples. ERT and GPR profiles, along with geochemical data, were collected and meticulously analyzed to assess the potential and quality of coal seams based on coal ranking, aiming to delineate their spatial distribution and future exploitation prospects. The study reveals a wide range of resistivity values, spanning from 8.93 Ωm to 2472 Ωm. The uppermost layer, comprising silt and clay with water saturation, exhibits resistivity values ranging from 8.93 Ωm to 50 Ωm. The subsequent stratum, characterized by wet sandstone with minor shale and clay, has resistivity values between 50 Ωm and 95.3 Ωm. Significantly, the zone with resistivity values between 95.3 Ωm and 800 Ωm is identified as the probable host of the coal seams. Based on the results, the coal seams are estimated to exist at depths ranging from 14 to 23 m, with resistivity values between 95.3 Ωm and 800 Ωm. GPR results further corroborate these findings, revealing coal-bearing strata at various depths, thus confirming the ERT results. Additionally, proximate and ultimate analysis provided insights into the quality of the coal, with average concentration values of moisture content (6.95%), ash content (22.12%), volatile matter (28.55%), fixed carbon (42.40%), carbon content (55.35%), hydrogen (4.7%), nitrogen (0.95%), sulfur (4.82%), and oxygen (10.06%). Comparative analyses of the obtained results with local coals from the Salt Range in Punjab, Pakistan, and coal from Ogboyaga, Nigeria, confirm that the studied coal ranks as sub-bituminous. This comprehensive assessment offers valuable insights into the potential and quality of Paleocene coal in the studied region and is applicable to other areas with similar geological settings.

show abstract

Section: Geophysical Studiesmentioning

confidence: 99%

Integrated Geophysical and Geochemical Analyses for Assessment of Potential Coal Prospects in Tirah Area, Khyber Pakhtunkhwa, Pakistan

Sajid,

Ali,

Khan

et al. 2023

Energies

View full text Add to dashboard Cite

show abstract

“…Yet, the manual reading of radargrams is often challenging due to the intrinsic differences in material properties of targets and soil characteristics. Several AI tools were developed and applied to assist the interpretation of GRP-collected data, in particular for applications regarding underground utilities [49][50][51][52]. One popular tool is the Hough transform (HT), used to extract geometrical features in images [53].…”

Section: Terrestrial Mappingmentioning

confidence: 99%

Review of Artificial Intelligence Applications for Virtual Sensing of Underground Utilities

Oguntoye

Laflamme

Sturgill

et al. 2023

Sensors

View full text Add to dashboard Cite

Accurately identifying the location and depth of buried utility assets became a considerable challenge in the construction industry, for which accidental strikes can cause important economic losses and safety concerns. While the collection of as-built utility locations is becoming more accurate, there still exists an important need to be capable of accurately detecting buried utilities in order to eliminate risks associated with digging. Current practices typically involve the use of trained agents to survey and detect underground utilities at locations of interest, which is a costly and time-consuming process. With advances in artificial intelligence (AI), an opportunity arose in conducting virtual sensing of buried utilities by combining robotics (e.g., drones), knowledge, and logic. This paper reviewed methods that are based on AI in mapping underground infrastructure. In particular, the use of AI in aerial and terrestrial mapping of utility assets was reviewed, followed by a summary of AI techniques used in fusing multi-source data in creating underground infrastructure maps. Key observations from the consolidated literature were that (1) when leveraging computer vision methods, automatic mapping techniques vastly focus on manholes localized from aerial imagery; (2) when applied to non-intrusive sensing, AI methods vastly focus on empowering ground-penetrating radar (GPR)-produced data; and (3) data fusion techniques to produce utility maps should be extended to any utility assets/types. Based on these observations, a universal utility mapping model was proposed, one that could enable mapping of underground utilities using limited information available in the form of different sources of data and knowledge.

show abstract

“…However, the influence of GPR scan distribution on 3D images has not yet been considered. Slob et al [17] developed an automatic indoor GPR data-acquisition system for slab imaging. BETOSCAN [18] combines different non-destructive sensors on a mobile robot system for large-area reinforced concrete floor diagnoses.…”

Section: Introductionmentioning

confidence: 99%

GPR Virtual Guidance System for Subsurface 3D Imaging

et al. 2021

View full text Add to dashboard Cite

Three-dimensional GPR imaging requires evenly and densely distributed measurements, ideally collected without the need for ground surface markings, which is difficult to achieve in large-scale surveys. In this study, a guidance system was developed to guide the GPR operator to walk along a predesigned traverse, analogous to the flight path design of an airborne drone. The guidance system integrates an auto-track total station unit (ATTS), and by estimating the real-time offset angle and distance, guidance corrections can be provided to the operator in real time. There are two advantages: (1) reduced survey time as grid marking on the ground is no longer needed and (2) accurate positioning of each traverse. Lab and field experiments were conducted in order to validate the guidance system. The results show that with the guidance system, the survey paths were better defined and followed in terms of feature connectivity and resolution of images, and the C-scans generated were closer to the real subsurface world.

show abstract

Untitled

Cited by 18 publications

References 11 publications

Integrated Geophysical and Geochemical Analyses for Assessment of Potential Coal Prospects in Tirah Area, Khyber Pakhtunkhwa, Pakistan

Integrated Geophysical and Geochemical Analyses for Assessment of Potential Coal Prospects in Tirah Area, Khyber Pakhtunkhwa, Pakistan

Review of Artificial Intelligence Applications for Virtual Sensing of Underground Utilities

GPR Virtual Guidance System for Subsurface 3D Imaging

Contact Info

Product

Resources

About