Geotechnical Parameters Research Articles

Advancing Geotechnical Evaluation of Wellbores: A Robust and Precise Model for Predicting Uniaxial Compressive Strength (UCS) of Rocks in Oil and Gas Wells

This study examines the efficacy of various machine learning models for predicting the uniaxial compressive strength (UCS) of rocks in oil and gas wells, which are essential for ensuring wellbore stability and optimizing drilling operations. The investigation encompasses Linear Regression, ensemble methods (including Random Forest, Gradient Boosting, XGBoost, and LightGBM), support vector machine-based regression (SVM-SVR), and multilayer perceptron artificial neural network (MLP-ANN) models. The results demonstrate that XGBoost and Gradient Boosting offer superior predictive accuracy for UCS in drillability, as indicated by low Mean Absolute Percentage Error (MAPE) values of 3.87% and 4.18%, respectively, and high R2 scores (0.8542 for XGBoost). These models emerge as optimal choices for UCS prediction focused on drillability, offering increased accuracy and reliability in practical engineering scenarios. Ensemble methods and MLP-ANN emerge as frontrunners, providing valuable tools for improving wellbore stability assessments, optimizing drilling parameter selection, and facilitating informed decision-making processes in oil and gas drilling operations. Moreover, this study lays a foundation for further research in drillability-centred predictive modelling for geotechnical parameters, advancing our understanding of rock behaviour under drilling conditions.

Refinement of the volcanic slope rating approach for determining slope stability in volcanic rocks of the Canary Islands

AbstractDue to their genesis, volcanic rocks present some singularities that make their geotechnical characteristics significantly different from other, more common types of rock masses, such as sedimentary and metamorphic rocks. The formation mechanisms of volcanic rocks are varied, rapid and generally high energy. These processes give this type of rock geotechnical behaviour and geomechanical properties that are completely different from those of nonvolcanic materials, due to their high heterogeneity and anisotropy. In volcanic rock slopes, applying widely used geomechanical classifications to assess the quality of any rock mass present several challenges due to their distinctive and singular characteristics, which detract from their validity. For this reason, the Center for Studies and Experimentation of Public Works (CEDEX) of the Ministry of Public Works, under the agreement signed with the Ministry of Public Works and Transport of the Government of the Canary Islands, carried out during 2017 and 2018 an exhaustive analysis and reviews of existing geomechanical classifications and their applications to volcanic terrains. They developed a new geomechanical classification called VSR (volcanic slope rating), based on data obtained from 85 slopes across the Canary Islands, which allowed for the estimation of the stability of volcanic rock slopes by evaluating seven geotechnical parameters. This article presents the work conducted to review and calibrate this tool, based on the study of 94 slopes of different lithotypes throughout the Canary Islands (lavas, pyroclasts, heterogeneous), culminating in the proposal of a new classification for pyroclastic massifs (with new parameters and different weightings) and the adjustment of the current classification for the other slopes (regarding the Surface Regularity parameter). Therefore, the VSR geomechanical classification was applied to assess the stability of these 94 slopes, revealing a strong fit for Types A and C (R2 > 0.97), while the tool overestimated stability in Type B slopes, prompting a new classification proposal for this category.

Large-scale geohazards risk of submarine landslides considering the subsea cables vulnerability: A case study from the northern continental slopes of South China Sea

Submarine landslides pose significant threats to subsea cables distributed on the global seabed. However, regional scale risk assessment of landslide geohazards is rarely reported. This study introduces a methodology for regional-scale geohazard risk prediction of submarine landslides, focusing on the northern continental slopes of the South China Sea. Initially, the study employed the infinite-slope method to calculate safety factors for typical submarine slopes. Addressing uncertainties in geotechnical and seismic parameters, Monte Carlo simulations determine slope failure probabilities. Using kriging interpolation, localized failure probabilities are extrapolated to regional scales, establishing a spatiotemporal distribution method for large-scale geohazard susceptibility. Hazard levels are subsequently determined considering the volumes of potential landslides. The density of subsea cables is used as a vulnerability factor to guide the regional-scale assessment of cable vulnerability. Finally, integrating vulnerability with hazard levels provides a comprehensive assessment of landslide-induced large-scale geohazard risks. The findings highlight elevated geohazard risks in the Taiwan Bank slope segment, moderate risks in the Zhujiang Valley and Shenhu slope segments, with lower risks in other areas.

Innovative geological–geotechnical zoning framework for urban planning: Wuhan’s experience

Traditional methods for understanding geological conditions, such as borehole drilling and on-site tests, are often costly and impractical for extensive urban areas like Wuhan’s Main Urban Area. This study introduces an innovative geological–geotechnical zoning framework that utilizes limited data to overcome these challenges, essential for urban planning, underground space development, and construction design. We began by dividing the study area into four primary geological units based on geomorphological characteristics, using a novel method validated at four metro stations. Our approach incorporated data from 1544 geological boreholes to compile a comprehensive database, from which six typical stratigraphic profiles for each unit were identified. These profiles facilitated the estimation of potential layers and their corresponding geotechnical parameters, and the identification of subsurface hazards. The study resulted in a detailed engineering geological zoning divided into nine secondary units. Our analysis not only demonstrates the effectiveness of the proposed criteria for geomorphological units in achieving more accurate and quantifiable outcomes but also shows the framework’s suitability for regions with complex sedimentary conditions. The resultant engineering geological zoning enhances understanding of geological risks, providing a foundation for safer and more sustainable urban development.

Estimation of the displacement of soil nailing vertical face structures intended for building undergrounds

ABSTRACT This study proposes a methodology for estimating horizontal displacements in vertical face soil-nailing structures in urban areas, analyzing 20 projects in São Paulo, Brazil. To minimize displacements, post-grouting sectorized injections through polyethylene tubes was used, a methodology routinely adopted in Brazil which gives the soil mass a significant increase in strength and stiffness.To study the effect of the sectorized injections on soil treatment, a three-dimensional computational model using Plaxis 3D software and calibrated through back-analysis according to the displacements of the structures. Additionally, 11 models were tested with variations in nail length, mesh configuration, and geotechnical parameters, considering injection effects. The study provides design and execution guidelines to optimize this technique. Equations derived from the study predict horizontal displacements, which will be used to assess the technical feasibility of the projects in advance and, when they are being executed, to provide performance control within a more precise and realistic margin.

A smarter approach to liquefaction risk: harnessing dynamic cone penetration test data and machine learning for safer infrastructure

This paper presents a novel approach for assessing liquefaction potential by integrating Dynamic Cone Penetration Test (DCPT) data with advanced machine learning (ML) techniques. DCPT offers a cost-effective, rapid, and adaptable method for evaluating soil resistance, making it suitable for liquefaction assessment across diverse soil conditions. This study establishes a threshold criterion based on the ratio of the penetration rate to the dynamic resistance (e/qd), where values exceeding four indicate high liquefaction susceptibility. ML models, including Support Vector Machine (SVM) optimized with Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Genetic Algorithm (GA), and Firefly Algorithm (FA), were employed to predict the e/qd ratio using key geotechnical parameters, such as fine content, peak ground acceleration, reduction factor, and penetration rate. The SVM-PSO model demonstrated superior performance, with high R2 values of 0.999 and 0.989 in the training and testing phases, respectively. The proposed methodology offers a sustainable and accurate approach for liquefaction assessment, reducing the environmental impact of geotechnical investigations, while ensuring reliable predictions. This study bridges the gap between field testing and advanced computational techniques, providing a powerful tool for geotechnical engineers to assess liquefaction risks and design resilient infrastructures.

A novel algorithm for identifying arrival times of P and S Waves in seismic borehole surveys

The arrival times of P and S waves, originating from earthquakes, diverse seismic tests, and events, are crucial geotechnical parameters. Derived from the inversion of these travel times, VP (P-wave velocity) and VS (S-wave velocity) are pivotal in geotechnical engineering, correlating directly with dynamic soil properties and enabling calculations of Poisson's Ratio (ν), Young's modulus (E), Shear modulus (μ), and Bulk modulus (B). Both VP and VS are crucial for evaluating soil behaviour under various conditions, aiding in modelling soil for settlement, wave propagation, seismic wave interaction, liquefaction potential analysis, seismic response analysis, and many more. The selection of arrival times for seismic tests, including Crosshole, Downhole, and Uphole tests, is done manually, which is time-consuming and potentially erroneous. To address this issue, various algorithms have been developed to automate the picking process. Some of these algorithms use wavelet transforms and Bayesian information criteria, while others use machine learning techniques such as artificial neural networks. These methods vary in terms of their accuracy, yet each one possesses inherent limitations when it comes to processing data with different levels of signal-to-noise ratio. The advancement of automated algorithms for determining arrival times is an ongoing and dynamic field of research. Apart from the existing research focused on determining the arrival time of P waves, there is a dearth of studies investigating the detection of S wave arrival times. To fill this gap, this study proposes new approaches for detecting both P and S wave arrival time(s). One approach entails the utilization of an iterative optimization algorithm to accurately fit a curve to the leading edge of the P waveform. The arrival time is determined by calculating a fraction relative to the highest point obtained from the fitted peak. The second approach entails identifying the exact moment of the S wave's arrival by determining the points of intersection between the oppositely polarized S waveforms. These methods provide a promising approach for automatically detecting both P and S wave arrival time(s), which has the potential to improve the precision and efficiency in picking up arrival time(s).

Seismic site conditions of RESNOM network

The Northwest Seismic Network of Mexico (RESNOM) is operated by personnel from the Center for Scientific Research and Higher Education of Ensenada, Baja California (CICESE), which supervises station installation, improvement, and maintenance. We employed seismic noise and the Horizontal to Vertical Spectral Ratio (HVSR) method to determine, for each station, the following site condition parameters: the depth of the rock layer (Heng_bed), and the geotechnical parameter VS30, obtained from 1D shear wave velocity models. Other parameters as the fundamental frequency (f0) and the average amplitude at the fundamental frequency (A0) were also estimated. Our results show clear differences between the values obtained for the Mexicali Valley and the Peninsular ranges regions. The VS30 obtained for stations of the Mexicali Valley region falls in the range from 173 m/s to 535 m/s, while for the Peninsular Ranges region is between 213 m/s and 958 m/s. Regarding the Heng_bed parameter, the values are similar between both regions, from 23 m to 850 m for the Peninsular and from 42 m to 926 m for the Mexicali Valley. Additionally, from the VS30 values, we propose the site classification according to the U.S. National Earthquake Hazards Reduction Program (NEHRP).

Micro–Macro-Analysis and Model Derivation of Electrical Resistivity of Ningxia Cement–Loess

In recent years, highway infrastructure in the Ningxia region of China has rapidly advanced. Cement–loess is extensively utilized in the roadbed and foundation reinforcement. It is necessary to conduct micro–macro-analysis and model derivation of the electrical resistivity on Ningxia cement–loess, which are beneficial for both the practical application of electrical resistivity and the evaluation of the geotechnical properties of cement–loess. Therefore, a series of electrical resistivity measurements, microstructural observations (scanning electron microscopy), mineral analyses (thermogravimetric analysis), and theoretical analyses were adopted on the cement–loess. The following conclusions can be drawn: The electrical resistivity is negatively related to dry density and water content, while it is positively related to cement dosage and curing age. A cement dosage of 6% exhibits a lower hydration reaction potential compared to 12%, causing a slower increase in electrical resistivity. The formation of calcium silicate gel around particles results in particle clustering and pore filling, reducing the pore area and increasing electrical resistivity. Increased hydration also decreases microscopic orientation, contributing to a higher electrical resistivity of cement–loess. Finally, a new three-dimensional electrical resistivity model was created, finding that the electrical resistivity of Ningxia cement–loess was determined by the dry density, water content (ρd·w), cement dosage, and curing age (aw·T) in an exponential function form. The new three-dimensional electrical resistivity model could be used in the high-efficiency evaluation of the cement–loess geotechnical parameter, offering valuable insights for the monitoring and maintenance of road infrastructure.

Analysis and monitoring of the behavior of a rock fill dam ten years after construction: a case study of the Iran-Madani Dam

AbstractIn this study we compared dam monitoring results with those of numerical analysis to propose a plan for the first reservoir impounding of the Iran-Madani Rock fill dam, ten years after the completion of its construction. The stability of the dam body has been assessed using numerical analysis and data obtained from sensors installed in the dam. The correctness and accuracy of the geotechnical parameters of the dam body materials were confirmed by comparing the results of numerical analysis and monitoring through back analysis. The linear correlation coefficients between the experimental data and the numerical results for settlement, pore water pressure, and total stress are 84%, 67%, and 99%, respectively. In addition, the agreement between the design assumptions with both the numerical analysis results and instrumentation data was examined. The arching ratio values obtained from instrumentation and numerical analysis in the core of the dam are 0.47 and 0.35, respectively, indicating the safety of the dam. Finally, a numerical sensitivity analysis was conducted to present a special impounding program for the dam, with a focus on controlling simultaneous changes in pore water pressure and effective stress in the clay core, ten years after the completion of the dam body construction.

A consistent terminology to communicate ground-related uncertainty

Engineering geology is highly affected by uncertainty related to geology, geotechnical parameters, models and methods. While the technical aspects of ground-related uncertainty are increasingly well investigated, the terminology to communicate uncertainty - e.g., “It is likely that X will happen.” - has not yet been unified and experts use it however they see fit. Due to varying experience, personal biases and societal backgrounds, people may understand uncertainty statements very differently, which is misleading and can even result in legal disputes. This contribution investigates the usage of uncertainty communicating terminology in ground-related disciplines and finds that there is a pronounced prevalence of uncertainty terminology in them. Furthermore, there is a special need to express uncertainty related to quantities (e.g. “most of the project area consists of…”). In response, we propose a framework to consistently communicate ground-related uncertainty encompassing three steps: 1. When you are certain about a statement, do not use uncertainty communicating language. 2. Assess and state the degree of confidence in a statement based on the quantity and quality of the available evidence vs. the agreement of the evidence. 3. If you have high or very high confidence in the statement, communicate the uncertainty in a consistent manner, otherwise elaborate how higher confidence can be achieved. The proposed approach feeds into new uncertainty-aware standards, such as Eurocode 7, and goes beyond them by addressing uncertainty in text and speech. This paper provides the premises for increased awareness of uncertainty communication and encourages further works on the topic.

Analysis of the possibility of description the pile load-settlement curve based on the CPTu results

One of the field soil tests commonly used for pile design is CPTu static sounding. The load-bearing capacity of pile foundations is commonly verified in field experiments through static load tests. The result of this test is the load-settlement relationship of the pile which can be approximated by a curve named M-K. The main aim of the work is to check the possibility of determining the parameters of the M-K curve based on the results of field tests with the CPTu sounding. Experimental research leads to relationships between the parameters of the M-K curve and geotechnical parameters, including CPTu static sounding. The paper presents the possibilities of using the CPTu sounding to estimate the pile settlement curve. Knowledge of this relationship at the foundation design stage allows you to confirm whether the pile meets the load-bearing conditions and to determine the safety margin, which gives designers greater opportunities to correctly design the foundation

Prediction of Undrained Shear Strength Utilizing a Hybrid Stacking Model Enhanced by Bayesian Optimization Algorithm

Undrained shear strength serves as one of the crucial indicators for analyzing the strength and assessing the stability of clay. To enhance the predictive capability of undrained shear strength, we introduced a hybrid stacking model, the KSMRX, which leverages the Bayesian optimization algorithm. Comparative analyses against base models revealed that the KSMRX model significantly enhanced prediction accuracy, elevating it from 51.3% to 72.5%. This substantial improvement underscored the efficacy of our approach in predicting drained shear strength. Moreover, when compared with the prediction accuracies of 15 other hybrid models, the KSMRX hybrid stacking model consistently demonstrated superior performance. Therefore, this study not only presents a novel and more convenient computational approach, facilitating the acquisition of highly accurate geotechnical parameters, but also serves as a reference for the implementation of geotechnical engineering projects.

Research on parameter selection criteria and design method for leachate pumping using vertical shafts

High leachate levels in landfills not only threaten the environment but also seriously affect the stability of piles. Therefore, it is crucial to pump leachate from piles, and vertical pumping wells have demonstrated their effectiveness in practical engineering. This paper establishes a model of vertical pumping wells, taking into account the non-homogeneous distribution of geotechnical parameters of the pile. The accuracy of this model is then validated through existing test results and numerical models. The main findings of the study are as follows: the radius of influence R is primarily influenced by the pumping time T, pumping pressure P, and anisotropy coefficient A. On the other hand, the depth of influence h is mainly determined by the burial depth h1 of the pumping section. The optimal pumping time Tb coincides with the time at which the well reaches its maximum radius of influence Rm. Similarly, the optimal pumping pressure Pb corresponds to the inflection point in the relationship between the radius of influence R and the pumping pressure P. The optimal pumping section burial depth is h1b = 20 m, and the optimal setback distance db is equal to the maximum setback distance dm. Additionally, this paper provides the criteria for parameter selection under each working condition at the optimal burial depth of the pumping section, as well as the design process for the vertical pumping system. The parameter design diagram and design method presented in this paper serve as valuable references for the design of real guide drainage projects.

Effect of Uncertainty in Geotechnical and Flow Parameters on Landslide-induced Force for Building Response Analysis Under Flow-type Landslides Using Uncoupled Approach

Effect of Uncertainty in Geotechnical and Flow Parameters on Landslide-induced Force for Building Response Analysis Under Flow-type Landslides Using Uncoupled Approach

Automated geotechnical logging of core box images using machine learning

ABSTRACT Geotechnical characterization is contingent on reliable data to reduce uncertainty in the conditions of slope walls or underground workings. However, geotechnical data for greenfield and brownfield sites are often limited. The data that are available are often inconsistent and difficult to reliably use to inform the geotechnical domain model. SRK has developed machine learning workflows using deep learning for geotechnical classification of existing core box photographs to provide a reliable and objective data set that can be used to inform rock mass characterization and structural modeling. Conventional geotechnical parameters are often unsuitable for automation due to the reliance on subjective decisions by the logger for interval lengths or defining naturally open versus closed breaks. Three classification systems have been developed: the Core Damage Index (CDI), the Pseudo-RQD, and the Break Frequency. The CDI classifies discrete intervals within the photographs according to the average clast sizes relative to the core diameter to provide a high-resolution view of the variability of damage down a drill hole. Pseudo-RQD and Break Frequency are calculated by mapping the breaks and rubble zones observed on drill core images.

Seismic site characterization baseline data for microzonation and site response analysis of Otuasega Town, Bayelsa State, Niger Delta region of Nigeria

This study presents the findings of a comprehensive geotechnical and seismic site investigation conducted at Otuasega Town located in Bayelsa State within the Niger Delta region of Nigeria. Subsurface exploration involved advancing 10 boreholes to 30 m depth using hollow stem auger drilling. Continuous disturbed and undisturbed soil sampling was performed at 1.5 m intervals for detailed geotechnical testing. Laboratory tests on the recovered soil samples established the index properties, classification, densities and consistency limits of the stratified deposits. The subsurface profile comprised alternating layers of clay, silt and sand typical of deltaic sediments, with the clay fractions exhibiting medium to high plasticity. Shear wave velocity (Vs) profiling using Multichannel Analysis of Surface Waves (WASW) techniques categorised the site predominantly as Site Class C and D based on international standards. The Standard Penetration Test (SPT) N-values ranged from 5 to 10, indicating soft normally consolidated clay conditions typical of the Niger Delta region. Predictive empirical models developed from the field and lab data showed strong correlations for estimating key geotechnical parameters such as SPT blow count, Vs and liquefaction resistance. Ground response analyses using the Vs and SPT data indicated significant site amplification potential, with peak ground accelerations up to 1.5 times the bedrock motion. Liquefaction analysis based on the empirical SPT-based methods revealed a high potential for liquefaction in the sandy layers, especially under strong earthquake shaking. The study characterized the complex sedimentology and provided baseline information for seismic microzonation and site-specific ground response analyses to advance understanding of geohazards in this delta environment.

Shear-Wave Velocity Data Assists Modeling for Offshore Windfarm Development

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 35354, “Pseudo-3D Underwater Multichannel Analysis of Surface Waves for Offshore Windfarm Development,” by Stephan Unterseh and Luis McArthur, TotalEnergies, and Edouard Mouton, SismOcean. The paper has not been peer reviewed. Copyright 2024 Offshore Technology Conference. _ In the course of a research and development (R&D) project dedicated to quantitative ground modeling, underwater multichannel analysis surface-wave (UMASW) data were acquired within an offshore windfarm area currently in development in the North Sea. The goal of the project described in the complete paper was to test the added value of the shear wave velocity (Vs) interpreted from the UMASW, particularly as a propagation tool of geotechnical information. While UMASW, together with seismic refraction, is regularly used to characterize the ground for burial or trenching purposes, it appears also to bring valuable design parameters for offshore wind turbine foundations. Introduction To investigate the value of Vs in the performance of quantitative ground modeling studies, an internal R&D initiative was launched aimed at acquiring Vs data and the associated uncertainties of foundation depth of an offshore windfarm currently in development. These data will be tested at a later stage for the propagation of geotechnical parameters used in foundation design. The acquisition consisted of obtaining Vs data through UMASW methodologies around two distinct geotechnical boreholes and along a corridor tying the two areas. The UMASW commonly is used in combination with seismic refraction to perform burial assessment analysis of cable or pipeline or to characterize ground conditions before performance of horizontal deviated drilling. Thus, the data acquisition did not require extensive hardware development. A unique pseudo-3D processing technique nevertheless was implemented to allow for 3D data visualization and ground characterization. Site Conditions The selected site lies in the North Sea in water depths ranging from 20 to 30 m. The area was first investigated with standard geophysical techniques. Preliminary geotechnical investigation included 6-m-deep vibrocores and 60-m-deep drilled boreholes, with alternating cone penetration tests and push sampling and coring. P-S logging also was performed at key geotechnical locations to gather 1D primary wave velocities (Vp) and Vs. The seabed generally consists of a thin cover of Holocene dense sand, occasionally with boulders, overlying quaternary subglacial formation deposits, including moraine, gravelly sand, and clays of variable thicknesses. The bedrock is generally Jurassic and includes dense sand; hard clay; weak claystone; and, locally, strong limestone bands. The test locations were selected within the coverage of the geophysical data set in areas where variable lithologies occur and where the seabed was found free of boulders and outcrops because these are detrimental to UMASW acquisition. The lithology of the two boreholes performed within the test area is indicated in Table 1 of the complete paper.

An approach to risk of rockfalls on roads. Case study of the Rafael Caldera Highway

In recent times, significant advancements have been made in the development of road safety, making it a key focus for Highway Engineers. To ensure the safety of road users, various methodologies have been established for assessing vulnerability, threat, and risk in both road infrastructure and vehicles. This article proposes an evaluation of the risk associated with rockfall on roads, incorporating the analysis of geotechnical and road parameters, verification of risk and vulnerability criteria, statistical analysis of vehicle vulnerability, and the assessment of kinematic slope stability. Additionally, the classification of rock masses in terms of threat is considered, leading to the development of a novel methodology for risk assessment. The evaluation of threat, vulnerability, and risk utilizes conventional methods such as assessing rock mass quality, kinematic stability analysis, and statistical parameters. This methodology has been implemented on the Mérida-El Vigía Highway, giving results consistent with those observed on the ground, unlike the others implemented in the area.

Development of a site-screening method for hydrogen storage purposes and its application to an industrial dataset of Italian hydrocarbon reservoirs

A methodology is presented for the objective and transparent screening of hydrocarbon reservoirs for underground hydrogen storage (UHS), with subsequent testing on a large confidential dataset provided by the energy company Eni. The procedure uses the Analytic Hierarchy Process and the Delphi technique to gather expert opinions and weight 27 screening parameters in terms of: health, safety, and environment; geotechnical performance; and economic performance. A set of scores is produced that characterizes each site in terms of these three categories, as well as a comprehensive site ranking based on their overall suitability for UHS. The results highlight the importance of geotechnical parameters, while the characterization of faults and hydrocarbon type, the onshore or offshore location, the number of wells, and the reservoir architecture yielded the highest individual weights. Potential scores are also estimated for sites with incomplete datasets. Two blind tests evaluated the method's effectiveness against preexisting industrial assessments.