Subsurface Utility Research Articles

Georadar Survey and Simulation for Subsurface Investigation at Historical Mosque of Sorghatmesh, Cairo, Egypt

Sorghatmesh mosque is a historical structure that was constructed in Cairo, Egypt, by Prince Saif El-Din Sorghatmesh in 1356. A dual-frequency ground-penetrating radar (GPR) with 250–700 MHz was used to investigate the subsurface of the Sorghatmesh mosque for restoration purposes. A total of 37 lines were surveyed on the ground floor of the mosque. The subsurface utilities were detected, and the status of the concrete base and the medium of the ground floor were assessed. A set of subsurface anomalies were detected and interpreted within the ground floor area of the mosque. In order to validate the interpretation, a trial pit was drilled on the ground floor, allowing for the visual inspection of the subsurface, and a Georadar numerical simulation was carried out to study the responses of the subsurface materials and conditions. For a better comprehension of the results, the ground floor area was categorized into five zones where the GPR interpretations between survey lines are almost similar. This work not only demonstrates the effectiveness of GPR as a non-invasive investigation tool but also highlights the potential of integrating advanced technologies into cultural heritage preservation by offering refined methodologies and insights for future research and restoration efforts.

Application of deep learning reduced-order modeling for single-phase flow in faulted porous media

AbstractOur research is positioned within the framework of subsurface resource utilization for sustainable economies. We concentrate on modeling the underground single-phase fluid flow affected by geological faults using numerical simulations. The study of such flows is characterized by strong uncertainites in the data defing the problem due to the difficulty of taking precise measurements in the subsoil. We aim to demonstrate the feasibility of a reduced order model that is both reliable and computationally efficient, thereby facilitating the incorporation of uncertainties. We account for the uncertainities of the properties of the rock and the geometry of the fault. The latter is achieved by using a radial basis function mesh deformation method. This approach benefits from a mixed-dimensional framework to model the rock matrix and faults as n and $${n-1}$$ n - 1 dimensional domains, allowing for non-conforming meshes. Our primary focus is on a reduced-order model capable of reproducing flow variables across the entire domain. We utilize the Deep Learning Reduced Order Model (DL-ROM), a nonintrusive neural network-based technique, and we compare it against the traditional Proper Orthogonal Decomposition (POD) method across various scenarios. The most relevant contributions of this work are: the proof of concept of the use of neural network for reduced order models for subsoil flow, dealing with non-affine problems and mixed dimensional domain. Additionally, we generalize an existing mesh deformation method for discontinuous deformation maps. Our analysis highlights the capability of reduced order model, highlighting DL-ROM’s capacity to expedite complex analyses with promising accuracy and efficiency, making multi-query analyses with various quantities of interest affordable.

A novel framework for predicting non-stationary production time series of shale gas based on BiLSTM-RF-MPA deep fusion model

Shale gas, as an environmentally friendly fossil energy resource, has gained significant commercial development and shows immense potential. However, accurately predicting shale gas production faces substantial challenges due to the complex law of decline, nonlinear and non-stationary features in production data, which greatly repair the robustness of current models in predicting shale gas production time series. To address these challenges and improve accuracy in production forecasting, this paper introduces a novel and innovative approach: a hybrid proxy model that combines the bi-directional long short-term memory (BiLSTM) neural network and random forest (RF) through deep learning. The BiLSTM neural network is adept at capturing long-term dependencies, making it suitable for understanding the intricate relationships between input and output variables in shale gas production. On the other hand, RF serves a dual purpose: reducing model variance and addressing the concept drift problem that arises in non-stationary time series predictions made by BiLSTM. By integrating these two models, the hybrid approach effectively captures the inherent dependencies present in long and nonstationary production time series, thereby reducing model uncertainty. Furthermore, the combination of BiLSTM and RF is optimized using the recently-proposed marine predators algorithm (MPA) to fine-tune hyperparameters and enhance the overall performance of the proxy model. The results demonstrate that the proposed BiLSTM-RF-MPA model achieves higher prediction accuracy and demonstrates stronger generalization capabilities by effectively handling the complex nonlinear and non-stationary characteristics of shale gas production time series. Compared to other models such as LSTM, BiLSTM, and RF, the proposed model exhibits superior fitting and prediction performance, with an average improvement in performance indicators exceeding 20%. This innovative framework provides valuable insights for forecasting the complex production performance of unconventional oil and gas reservoirs, which sheds light on the development of data-driven proxy models in the field of subsurface energy utilization.

Subsurface utility detection using ground penetrating radar and electromagnetic locator – a comparative study

The process of finding and mapping underground utilities is crucial for managing underground infrastructure effectively, especially to avoid damaging them during construction and digging. This research studies two main methods used for this purpose: Ground Penetrating Radar (GPR) and Electromagnetic Locator (EML). GPR works by using electromagnetic waves to detect and assess things underground, giving an idea of how deep they are. On the other hand, EM L help to find metal utilities by using electromagnetic fields. This shows how important it is to have accurate maps of these utilities. Having precise maps is like having a solid foundation for planning and maintaining infrastructure. It also points out that when combine information from GPR and EML and analyse the results together, it can make the findings even more accurate. In a nutshell, these methods are crucial for keeping us safe, preventing delays in projects, and making sure to use resources wisely across different industries. In this research, Root Mean Square Error (RMSE) is used to determine the correlation in depth accuracy error which is 0.05821 which is calculated based on the depth measured by GPR and EML.

Integrated assessment of available water volume for sustainable sponge city construction - A case study in Xi'an, China.

To address the lack of theoretical guidance for sponge city construction (SCC) in China, this study introduces a method to evaluate the available water volume (AWV) in urban watersheds. This evaluation is based on the water balance relationship, water volume, and ecological water demand (EWD). The Xi'an urban area was selected as a case study due to its water shortage and flooding issues. Results show monthly surface and subsurface AWV ranging between 53.06 and 53.98 million m3 and between 8,701.89 and 8,898.14 million m3, respectively. By maximizing the potential for surface AWV, an annual water supply of 527.75 million m3 could be provided, surpassing the annual artificial water consumption of 394.20 million m3, effectively addressing water scarcity. During the rainy season, implementing measures such as employing permeable paving materials, establishing wetlands and rainwater gardens, and constructing lakes and reservoirs can mitigate flooding caused by rainfall exceeding 32.8 mm. While the subsurface space in Xi'an holds significant potential for subsurface AWV utilization, revitalizing the ecological environment of subsurface water is crucial. Overall, the AWV theoretical framework offers a comprehensive solution to water shortage and flooding issues in the Xi'an urban area, serving as a vital theory for SCC.

Subsurface Utility Identification at ITERA Campus Using Multi-frequency Ground Penetrating Radar

Infrastructure development at the Sumatra Institute of Technology is growing rapidly, hence, it requires new utilities installation network such as cables and pipes to supply electricity and clean water. Installing new utility line, it is necessary to secure and know the existence and depth of the previously embedded utility network to avoid damage that could hamper the construction process or cause large losses. Accessing the sub-surface information, geophysical method, such as Ground Penetrating Radar (GPR) can be utilized for identifying buried utility networks, ensuring the safe installation of new utilities and preventing damage to existing embedded utilities. In this study, a GPR device with a frequency range 40 MHz-3.4 GHz comprising 5 tracks was employed. The acquired data underwent processing using GPR Insights software, generating a radargram cross-section that provides information about the subsurface.The results from the radargram reveal a hyperbolic reflection anomaly, signifying the presence of a utility network beneath the surface, suspected to be pipe and cable utilities. The utility network is detected at varying depths of 0.5 m, 0.8 m, 1 m, and 1.2 m at different distances. Furthermore, several anomalies in the form of hyperbolas are observed, suggesting potential utilities due to their continuity with other paths.

Instant Segmentation and Fitting of Excavations in Subsurface Utility Engineering.

Using augmented reality for subsurface utility engineering (SUE) has benefited from recent advances in sensing hardware, enabling the first practical and commercial applications. However, this progress has uncovered a latent problem - the insufficient quality of existing SUE data in terms of completeness and accuracy. In this work, we present a novel approach to automate the process of aligning existing SUE databases with measurements taken during excavation works, with the potential to correct the deviation from the as-planned to as-built documentation, which is still a big challenge for traditional workers at sight. Our segmentation algorithm performs infrastructure segmentation based on the live capture of an excavation on site. Our fitting approach correlates the inferred position and orientation with the existing digital plan and registers the as-planned model into the as-built state. Our approach is the first to circumvent tedious postprocessing, as it corrects data online and on-site. In our experiments, we show the results of our proposed method on both synthetic data and a set of real excavations.

Estimation of buried pipe depth in an artificial soil tank using ground-penetrating radar and moisture sensor

A method is required for accurate determination of the location (horizontal position and depth) of subsurface utilities with minimal digging. Ground-penetrating radars (GPRs) have been used at many sites as a nondestructive method for detecting underground structures. Previous studies have examined the accuracy and resolution of GPRs based on comparisons of exploration images and factors such as soil, pipe material, and environmental conditions. Although numerous studies have explored the influence of relative permittivity and water content on GPR surveys, only a limited number have conducted direct measurements of water content using a moisture sensor within a soil tank and applied this data to enhance the precision of depth estimation. In this study, the effects of pipe material, relative permittivity, and antenna frequency on the depth estimation accuracy were quantitatively investigated using an artificial soil tank made of silica sand with known physical properties. In addition to the GPR survey, relative permittivity measurements were conducted using time-domain reflectometry (TDR) sensors located at different water levels. The results show that the antenna frequency and pipe material affect the resolution but not the depth estimation accuracy. Furthermore, the GPR survey using the relative permittivity from the TDR sensors estimated the pipe depths with a relative error of <7.33% relative to the actual burial depth under the following conditions: a volumetric water content of 2.6–38.2%, the relative permittivity of 2.9–23.2, and buried pipes of 0.1 m in diameter and 1.5 m in depth. The study findings show that the selection of an appropriate frequency and the estimation of soil permittivity using a moisture sensor can improve the depth estimation accuracy of buried pipes by GPR survey.

Return on Investment of Implementing Subsurface Utility Engineering on Transportation Projects: A Review and Analysis of Previous Cost–Benefit Studies

Since the late 1990s, studies conducted on the implementation of the subsurface utility engineering (SUE) concept in the design and planning phase of highway infrastructure projects have repeatedly shown a significant return on investment (ROI). ROI values varied across all studies, influenced by project characteristics, such as the number of projects studied and quantity and quality of project information. This study examines previous ROI studies on the implementation of SUE and compares the methodologies and cost-saving models used to account for the benefits of performing SUE on diverse construction projects. The study further investigates the results of the various cost-saving items and benefit factors to identify the most significant and least cost-saving items. The reduction in utility relocations during construction was identified as the significant cost saving in using SUE, while the direct cost to the public was identified as the least cost saving and not adequately estimated by most studies. The study supports why the adoption of SUE is encouraged for projects involving infrastructure construction and should be considered an integral part of engineering risk management for construction projects.

3D geological modelling of the Bologna urban area (Italy)

Urban geological modelling plays a crucial role in facilitating the sustainable utilization of the urban subsurface and the development of effective strategies for geohazard mitigation. Traditionally, geological models of urban areas rely on lithological correlations of boreholes and well data. However, in complex depositional settings such as alluvial environments, where the standard concepts of superposition and lateral continuity of strata are often violated, lithostratigraphic correlation can be challenging even over short distances, leading to considerable uncertainty in the final geological model. Therefore, in such cases, lithofacies analysis can provide a more robust categorisation of subsurface geological units as lithofacies mainly reflect the depositional process, while their associations provide a reliable picture of sedimentary bodies and their geometries. In this work, we used the lithofacies correlation approach to develop a 3D geological model of the urban area of Bologna (Italy) where a complex, thick alluvial succession makes lithological correlations very difficult. To minimize subjectivity, we re-interpreted 940 existing borehole logs in terms of depositional facies and combined stratigraphic data with geophysical HSVR (Horizontal to Vertical Spectral Ratio) measurements and surface analysis (morphology and river network) based on a DTM (Digital Terrain Model). This led to the detailed reconstruction of the subsurface depositional architecture, forming the basis for the 3D geological model. The model revealed the presence of three distinct depositional domains with different stratigraphic architectures. From west to east: Domain A (Reno River) corresponds to the gravel-dominated fill of a river valley abruptly passing to Domain B (Bologna urban area) that represents a morphological and stratigraphical divide, topographically elevated with respect to the surrounding areas and characterised by fine-grained deposits with frequent paleosols. Lastly, Domain C (Savena River) exhibits the typical alluvial fan pattern, marked by a gentle convex-up surface morphology with gravelly-sandy deposits with a low degree of lateral amalgamation. The geological model effectively explains the distribution of ground subsidence in Bologna since the 1960s, which is attributable to significant groundwater pumping. This is evident from the comparison of the model with both the ground displacement contours resulting from the 1983–1987 topographic levelling campaign and the subsidence rate map derived from the 2006–2011 Radarsat interferometric survey. Subsidence shows strong variations at the domains' boundaries, especially at the limit between Domain A (Reno River) where high values prevail, and Domain B (Bologna city centre) characterised by the lowest values.

Current Benefits of ASCE 75 and its Potential to Affect Digital As-Built Initiatives at State Departments of Transportation

For the proactive documentation of utility infrastructure at the time of its installation, the American Society of Civil Engineering (ASCE) is finalizing their ASCE 75 “Standard Guideline for Recording and Exchanging Utility Infrastructure Data.” ASCE 75 provides guidance for collecting sufficient geospatial and attribute data of utilities to facilitate the development of precise 3D digital twins. Some state departments of transportation (DOTs) in the U.S. have already adopted draft versions of ASCE 75 and are attempting to use it to assist their efforts to standardize and expedite their utility accommodation, permitting, and highway project coordination regulations and procedures. In alignment with these efforts, the Federal Highway Administration’s “Every Day Counts Round Six” initiative illustrates the importance of digital as-built (DAB) records by stating that their implementation can enhance safety, quality, and cost savings. However, there is no standard practice for the general construction DABs. Therefore, this study illustrates the benefits of implementing the ASCE 75 utility as-built standard and its potential impact on DABs for general construction. This study used a research methodology comprised of interviewing state DOTs, and a comprehensive literature assessment. The benefits of implementing ASCE 75 include improved data exchange methods among the project stakeholders and the collection and exchange of data about subsurface and above-ground utilities’ location and other attributes. Moreover, ASCE 75 provides a framework for all infrastructure projects. Also, the study highlights how ASCE 75 is adopted across the state DOTs and how it presents a path forward beyond just developing a utility as-built standard.

Integrating GPR with ArcGIS Pro to map the Central Arkansas Water pipelines beneath the old Broadway Bridge, Little Rock

Central Arkansas Water (CAW) supplies fresh water to nearly 500,000 people in Arkansas. To prevent service interruptions and costly damages, the pipes and other potential utilities must be precisely located and mapped in three areas designated by the Arkansas Department of Transportation (ARDOT) prior to any excavation work. This research aimed to integrate Ground Penetrating Radar (GPR) with ArcGIS Pro to assist with locating, mapping, and analyzing the utility lines. The results of this study indicate that integrating GPR with ArcGIS Pro can be an efficient tool to locate, map, and analyze utility lines with great precision. The GPR technique was effective in locating the CAW pipelines and other subsurface utility lines at depths ranging from a few centimeters to less than two meters at the selected sites. ArcGIS Pro was highly effective in accurately mapping and analyzing both the detected and existing utilities in 2D and 3D spaces, providing comprehensive visualizations and analysis tools for the CAW service area. The findings of this study suggest that GPR, with ArcGIS Pro, could help protect utility infrastructure, reduce the cost of maintenance, and help with implementing mitigation strategies.

A Complex Brownfields Case Study—The Former Bannister Federal Complex, Kansas City, Missouri

AbstractIn November 2017, 225 acres (91 ha) of the former Bannister Federal Complex (BFC) in Kansas City, Missouri were transferred from the Federal Government to Bannister Transformation &amp; Development, LLC (BTD), for demolition; environmental corrective measures; and preparation of the site for redevelopment. This presented a once‐in‐a‐lifetime opportunity to reconfigure groundwater remedies and address long‐standing soil contamination issues. The property included more than 40 previously‐identified Solid Waste Management Units, 3.9 million square feet (362,000 m2) of buildings, subsurface utilities dating back to the 1940s, and an active groundwater containment system. Demolition of buildings and installation of an interim groundwater containment system began almost immediately after property transfer. In 2018, BTD substantially modified its project schedule to incorporate the construction of the first new buildings while demolition and remedial activities were ongoing. By October 2020, construction of the first new warehouse commenced while excavation and capping of contaminated soils, installation of a groundwater containment treatment systems, and abandonment of legacy utilities were still underway. Completion of this work, within the originally planned timeframe, was made possible by factors including up‐front multi‐year funding, early and ongoing engagement of regulators, an extended 3‐year due diligence program and planning stage, and establishment of well‐defined environmental targets. Both the soil and groundwater remedies were also designed with the flexibility needed to accommodate unknown conditions, changing schedules, and revisions to the regrading and redevelopment plans. This case study highlights key technical and management factors that led to the successful completion of this complex brownfields remediation project.

Evaluating and Incorporating Utility Coordination Practices into the Kentucky Transportation Cabinet Project Development Process

Utility relocations have been identified as one of the leading causes of delays in transportation projects. Over time, national perceptions about how state transportation agencies (STAs) should work with utility companies (UCs) have changed. The Kentucky Transportation Cabinet (KYTC), like other STAs, faces many challenges related to utility work. This paper presents the findings of a research project funded by KYTC, which aimed to evaluate the current KYTC utility coordination process to identify opportunities for improvement and propose a new approach for enhancing the alignment of this process and the highway design process. Researchers crafted this new approach based on the findings of a literature review, an evaluation of the current alignment between the utility coordination and highway design processes, and experiences and lessons learned from other STAs. This approach was developed iteratively in consultation with the project’s Study Advisory Committee. Research findings suggest viewing utility coordination as an opportunity to partner with UCs. In addition, the early identification of potential utility conflicts and minimizing utility-related project risks during the early stages of project development by avoiding, minimizing, and mitigating all utility conflicts when feasible are encouraged. Project findings were used to develop a guidance document to assist the implementation of a new approach and an associated Utility Coordination Training Program. This guidance document includes suggestions for identifying, managing, and mitigating utility-related risks using utility conflict management, provides information on the strategic use of subsurface utility engineering, and offers recommendations for managing consultant-led utility coordination.

Editor’s Choice: Advances in Carbon Capture Subsurface Storage and Utilization

This “Editor’s Choice” article summarizes nine recent articles in Energies focusing on carbon capture, subsurface storage, and utilization [...]

POTENTIAL OF CONSUMER-GRADE CAMERAS AND PHOTOGRAMMETRIC GUIDELINES FOR SUBSURFACE UTILITY MAPPING

Abstract. The poor documentation of subsurface utility data is a common problem in many cities, exposing field engineers to risks of utility strike. This paper investigates the use of consumer-grade cameras to improve operational efficiency on construction sites and explores different imaging networks to optimize photogrammetric processing for low-cost subsurface utility surveys. Results from the first part of the study demonstrated the potential of consumer-grade cameras as a photogrammetric utility data acquisition tool. However, statistical insights from the photogrammetric calibration show that caution needs to be taken about the camera types particularly for lens calibration. Results from the second part of the study were recommended as easy-to-understand guidelines for image acquisition at trenches and supported the planning of photogrammetric measurements in the field.

Diffusion of CO2 in single-step silica nanofluid for subsurface utilization: an experimental study.

This study investigates the role of single-step silica nanofluids as additives to increase CO2 absorption in polymeric solutions for proposed oilfield applications. Using pressure decay approach, the study investigates the applicability of single-step silica nanofluids for CO2 absorption in a high pressure-high temperature (HPHT) cell. Various parameters like nanoparticle size (30-120nm) and concentration (0.1-1 wt%) were investigated to ascertain the absorption performance of the nanofluids and optimization their application in subsurface applications as carrier fluids for CO2. The solutions under observation (deionized water and silica nanofluids) were pressurized under the desired pressure and temperature inside a stirring pot and the decline in pressure was continuously noted. To comprehensively cover the near-reservoir field conditions, the CO2 absorption was investigated in the pressure range of 5-10MPa and at temperatures of 30-90°C. While increasing the nanoparticle concentration (from 0.1 to 1 wt%) increased the CO2 absorption (evident by the sharper decline in pressure), increasing the nanoparticle size reduced the absorption capacity of the nanofluids as a lesser volume of decline in pressure was noted. Furthermore, increasing the temperature of the experimental investigation caused a major reduction (12-19%) in the pressure decay. However, it was also observed that higher pressure (> 7.5MPa) was detrimental for CO2 absorption (due to its supercritical nature). Adding salt (sodium chloride, NaCl) was found to massively lower (up to 33%) while adding surfactant (sodium dodecyl sulfate, SDS) slightly increased the amount of CO2 absorption (in presence of salinity). Based on the observations of this study, the use of single-step silica nanofluids as CO2 carrier fluids is recommended for oilfield conditions where salinity is less than 4 wt%.

Locating underground utilities in the United States: A comparative analysis of services provided by private locators

The ability to locate underground utilities is imperative for the protection of these facilities and for the coordination of these facilities with transportation projects. The proliferation of underground facilities in the United States has led to an increase in dig-in strikes resulting in loss of services, project delivery delays, injuries, and even deaths. In fact, the Federal Highway Administration found utility-related issues to be one of the top causes of delays for transportation projects. These delays are often attributed to unknown or inaccurate utility location information. This scenario has led to a vast industry of utility location service providers. Additionally, national and state damage prevention laws led to the creation of one-call systems for the purpose of providing a communication conduit between designers or constructors and utility owners and operators. The importance of accurate utility locates and the risk and liability of providing utility location services also led to the American Society of Civil Engineers (ASCE) standardizing the practice of Subsurface Utility Engineering (SUE) into a professional service. Even with this standard, there remains misinformation and misunderstandings regarding SUE and non-SUE services provided by private utility location firms. The differences between the services provided by SUE investigations and non-SUE private locating services that do not meet SUE standards has largely been anecdotal. This study serves as an advancement in understanding the distinction of SUE services versus non-SUE services and provides evidence of industry misunderstanding of differences in these service types.

Hydrodynamics of gas-liquid displacement in porous media: Fingering pattern evolution at the breakthrough moment and the stable state

Gas-liquid displacement in porous media widely exists in many terrestrial/extraterrestrial subsurface resource extraction and utilization applications. The typical fingering displacement during gas invading has been well identified through extensive research efforts. Yet, the evolution of fingering structures after invading breakthrough is rarely reported. Herein, through a joint approach of experimental flow imaging and digital image processing, we investigated the gas-liquid fingering displacement in a porous-patterned microfluidic chip from the breakthrough moment until reaching the steady state. With a wide range of capillary number Ca and viscosity ratio M, we visualized the evolution of finger morphologies in different flow regimes including capillary fingering (CF), viscous fingering (VF), and crossover zone (CZ). Interestingly, we found that finger structures of CF regime remain the same after the breakthrough, whereas fingers of VF regime keep expanding until almost all the pore space is invaded and eventually reaches to steady state. Followed with experimental observations, a comparative quantification of fingering patterns was also conducted in terms of invasion velocity, phase saturation and fractal dimension. A dramatic increase of gas saturation, from 0.15 to 0.60 at the case of Log10Ca=-5.17 and Log10M=-2.78, is obtained in the VF regime when the steady state is reached, so is the fractal dimension (from 0.14 to 0.16, even higher than one of CF). The underlying mechanism of such fingering expansion in VF is further revealed from the time evolution of fingering after breakthrough. A previously unobserved fingering cycle, consisting of new finger forming, cap invading, breakthrough and finger vanishing, keeps repeating until the saturation reaches the maximum. We believe that these findings are of significance in evaluating extraction effectiveness, economic benefits and storage safety for subsurface applications.

An enhanced GPR-based data processing approach for detecting subsurface utilities in urban distribution networks

Ground-penetrating radar (GPR) is a non-destructive technique that helps find subsurface utilities. In geophysical investigations, the availability of noise sources, and the complexity of utility networks mean that performing a routine field operation and processing may not reveal the wanted anomalies. Thus, we use data acquisition and processing strategy to detect every single hyperbolic event (which means a probable anomaly) more accurately. In this approach, we first acquire data in parallel lines that cross the predetermined utility line path, use pre-processing techniques (zero-time correction, dewowing, etc.), and then use compensated time reversal (CTR) processing technique. Moreover, we group detected events depending on how frequently they occur through all traverses, where repeated events are probably caused by a utility line. For a better understanding, we compared CTR outputs with conventional processing (using filtering and Kirchhoff migration). This approach was used in a field that comprises buried utilities, such as pipelines and cables. Data were acquired along 4 parallel traverses with a GPR MALA tool and an antenna frequency of 250 MHz. Results indicate that the CTR generates better resolution/higher signal-to-noise ratio, and precise utility location as confirmed by drillings.