A probabilistic approach to establishing the resistivity-lithology relationship using co-located tTEM data and lithological logs

Reliable delineation of shallow weak zones is essential for infrastructure design in carbonate-alluvial environments where thin soils overlie fractured or karstified limestone. In this study, 15 closely spaced multichannel analysis of surface waves (MASW) profiles were acquired along urban corridors in Riyadh, Saudi Arabia, and integrated with six geotechnical boreholes (SPT and RQD) to characterize subsurface conditions to depths of approximately 20m. Dispersion curves were inverted to produce two-dimensional shear-wave velocity (Vs) sections, which were calibrated using lithologic logs and penetration resistance data. The integrated results define a consistent three-layer structure comprising: (1) near-surface silty sand with gravel (Vs ≈ 360-760m/s), (2) highly weathered to fractured limestone (Vs ≈ 760-1500m/s), and (3) compact limestone bedrock with Vs locally exceeding 3000m/s. Soil thickness above limestone varies laterally from approximately 2 to 11m. Shallow low-Vs anomalies (30-60% velocity reduction relative to surrounding materials) are detected between 2 and 10m depth and correspond to intervals of poor RQD and reduced SPT resistance, indicating fractured or cavity-prone zones. Vs30 estimates classify most of the area as NEHRP Site Class C, with localized tendencies toward Class D where soils are thickest and weak zones cluster. The principal contribution of this work lies in the high-resolution, corridor-scale integration of MASW and borehole data to map laterally discontinuous weak zones and generate engineering-ready spatial products (soil thickness, average Vs, and site class) suitable for foundation planning and infrastructure alignment in heterogeneous carbonate terrains.

A hydrogeophysical investigation of groundwater potential was conducted in the Ugbowo area of Edo State, Nigeria, using Electrical Resistivity Method to characterize the subsurface lithology and evaluate groundwater potential. A Global Positioning System (GPS) receiver was used to obtain the geodetic coordinates of the VES station, which is located at latitude 6° 28′ 48.36″ N and longitude 5° 35′ 17.16″ E. The geology of the study area is predominantly composed of the Benin Formation, which underlies approximately 95% of the region. Vertical Electrical Sounding (VES) was performed at one station using the SAS 300C ABEM Terrameter with the Schlumberger array configuration and a maximum electrode spacing of 147 m. The acquired data were processed and interpreted using the IPI2WIN software. The resulting geoelectric model revealed six subsurface layers with apparent resistivity values ranging from 391.51 Ωm to 5836.9 Ωm and depths extending from 1.41 m to 85.23 m. The lithologic units identified include lateritic topsoil, clay, gravel, cemented sandstones, and fine- to coarse-grained sands of varying thicknesses. The aquifer units were predominantly confined and showed good correspondence with lithologic logs from existing boreholes within the study area. A high resistivity lateritic layer was found to dominate the upper subsurface. The Vertical Electrical Sounding (VES) results indicate the presence of an aquifer with a resistivity of 783.37 Ωm, located directly below the fifth layer in the study area. This potential aquifer suggests that the area may be suitable for groundwater development. Based on these findings, it is recommended that drilling contractors consider this information before borehole construction to enhance the efficiency and success of groundwater exploration.

Kaolin clay has long served as a vital raw material for ceramics, refractories, and construction products due to its plasticity, heat resistance, and abundance. Despite Nigeria’s rich clay resources, the country continues to rely heavily on imports of refractory-grade materials. This study employed the Vertical Electrical Sounding (VES) technique to characterise and assess the economic potential of clay deposits in Ire-Ekiti, Southwestern Nigeria. Eighteen (18) VES stations were established within an area of about 200 m² using the Schlumberger array configuration with current electrode spacing (AB/2) ranging from 1 to 100 m. Apparent resistivity data were acquired using a SYSCAL Junior resistivity meter and processed with IPI2Win and RESIST software to generate one-dimensional resistivity–depth models. The inverted results, correlated with lithologic logs and field observations, delineated three major subsurface units: a thin resistive overburden, a conductive clay-bearing horizon (18–100 Ω-m), and a highly resistive basement or sandy formation. The clay layer exhibited variable thickness, ranging from 10 m to 14 m across the area, with the thickest and most laterally continuous zones identified around VES 4, 5, 6, 7, 10, and 17. These “sweet zones” represent the most promising targets for economic extraction. The deposit’s volume, overburden characteristics, and accessibility indicate favourable conditions for industrial exploitation. Comparative assessment with similar Nigerian clay deposits suggests that the Ire-Ekiti kaolin clay is suitable for refractory and ceramic applications.

Identifying lithologies within the volcanic reservoirs of the Huoshiling Formation (Wangfu Fault Depression, Songliao Basin) remains challenging due to extreme heterogeneity, limited core control, and ambiguous responses on conventional logs. We introduce an enhanced machine-learning framework for high-precision classification of these complex volcanic sequences, leveraging detailed core descriptions and five conventional well logs—gamma ray (GR), compensated neutron (CNL), bulk density (DEN), acoustic travel-time/sonic (AC), and deep array laterolog resistivity (RLA5)—from 12,388 depth-matched samples across 20 wells, encompassing 18 lithologies. The core innovation is an enhanced Random Forest (eRF) specifically engineered for geological and data-centric challenges. The eRF synergistically integrates: (1) Borderline-SMOTE to counteract severe class imbalance by selectively augmenting minority instances near decision boundaries, critical for rare but geologically significant facies; (2) C4.5 decision trees with gain-ratio splitting to optimize node-level feature selection from correlated continuous logs; and (3) Kendall’s coefficient of concordance (Kendall’s W) to stabilize feature-importance ranking across trees, prioritizing robust predictors. Against standard RF, back-propagation neural network (BPNN), k-nearest neighbors (kNN), and support-vector machine (SVM), the eRF attains 96.34% overall accuracy. Per-class accuracies exceed 0.88 for all 18 lithologies, with the largest improvement (+43 percentage points) for trachytic tuff. Sensitivity analysis indicates GR and AC dominate, together accounting for >60% of model decisions. This geologically attuned, optimized ensemble provides a transferable route to high-resolution lithology logs in uncored intervals, substantially aiding hydrocarbon sweet-spot prediction in complex volcanic settings.

Identifying lithologies within the volcanic reservoirs of the Huoshiling Formation (Wangfu Fault Depression, Songliao Basin) remains challenging due to extreme heterogeneity, limited core control, and ambiguous responses on conventional logs. We introduce an enhanced machine-learning framework for high-precision classification of these complex volcanic sequences, leveraging detailed core descriptions and five conventional well logs-gamma ray (GR), compensated neutron (CNL), bulk density (DEN), acoustic travel-time/sonic (AC), and deep array laterolog resistivity (RLA5)-from 12,388 depth-matched samples across 20 wells, encompassing 18 lithologies. The core innovation is an enhanced Random Forest (eRF) specifically engineered for geological and data-centric challenges. The eRF synergistically integrates: (1) Borderline-SMOTE to counteract severe class imbalance by selectively augmenting minority instances near decision boundaries, critical for rare but geologically significant facies; (2) C4.5 decision trees with gain-ratio splitting to optimize node-level feature selection from correlated continuous logs; and (3) Kendall's coefficient of concordance (Kendall's W) to stabilize feature-importance ranking across trees, prioritizing robust predictors. Against standard RF, back-propagation neural network (BPNN), k-nearest neighbors (kNN), and support-vector machine (SVM), the eRF attains 96.34% overall accuracy. Per-class accuracies exceed 0.88 for all 18 lithologies, with the largest improvement (+43 percentage points) for trachytic tuff. Sensitivity analysis indicates GR and AC dominate, together accounting for >60% of model decisions. This geologically attuned, optimized ensemble provides a transferable route to high-resolution lithology logs in uncored intervals, substantially aiding hydrocarbon sweet-spot prediction in complex volcanic settings.

Abstract Groundwater occurrences, movements and interactions are governed by hydrogeological features, whose spatial variability in thickness and continuity introduces uncertainties in models derived from limited discrete data points. Integrating geophysical methods with borehole data is essential for accurately characterizing these features. However, conventional deterministic geophysical inversion approaches often suffer from trapping in local minima and strong dependence on initial models potentially resulting in inaccurate hydrogeological interpretations. This study applies a Particle Swarm Optimization (PSO)-based inversion algorithm to interpret 20 vertical electrical sounding (VES) datasets acquired using the Schlumberger configuration in the Lake Tana Sub-Basin, Ethiopia. Results reveal an 8–40 m thick low-resistivity sedimentary layer (4–12 ohm·m), underlain by a higher-resistivity unit (9–15 ohm·m) of variable thickness. At approximately 40 m depth, another low-resistivity layer appears, followed by a very high-resistivity zone (>20 ohm·m) beginning around 70 m depth. To enhance structural interpretation, cubic interpolation was employed to construct 2D resistivity cross-sections along selected transects. The resulting models show strong correlation with borehole lithological logs, validating the inversion results. Through cooperative interpretation, hydrogeological units such as aquitard, leaky aquifer, aquitard and leaky aquifer from top to bottom were identified. The surface low-resistivity layer is interpreted as an aquitard that thickens toward Lake Tana. Beneath it lies a leaky aquifer, which extends upland but not toward the lake. This is underlain by a regional aquitard that confines the main leaky aquifer at ~70 m depth.This study provides valuable insights into hydrostratigraphic characterization in the Sub-Basin. The successful application of PSO-based inversion also highlights its potential as a robust alternative to conventional techniques, paving the way for future hydrogeophysical investigations in the Lake Tana Sub-Basin.

The Dalazi Formation in the Yanji Basin is primarily composed of fan delta and lacustrine facies, with local development of alluvial fan deposits. The second member of the Dalazi Formation (Da₂) serves as the key oil-bearing interval for exploration and development. Based on logging data, lithological observations, and maximum entropy spectral analysis (MESA), Da₂ is interpreted to mainly represent a continental fan delta system. Due to the complex depositional environment, significant variations exist in sedimentary types, resulting in notable differences in both lithology and logging curves, which hinders regional correlation using conventional logging marker bed pairings. In order to solve this problem, based on the theory of high resolution sequence stratigraphy and astronomical cycle theory, this paper uses the maximum entropy spectrum analysis, spectrum analysis and wavelet time–frequency analysis technology to process and analyze the natural gamma curve (GR) data, and combines the logging lithology information to identify the sequence interface. According to the prediction error trend (INPEFA) curve in MESA, it is identified that Da2 contains 1 long-term base level rise half-cycle and 1 long-term base level fall half-cycle. On this basis, the mid-term base level cycle and short-term base level cycle are identified by combining spectrum analysis technology and wavelet time–frequency technology. Finally, The Da2 sequence is subdivided into 1 long-term, 6 mid-term, and 16 short-term base level cycles, based on which a sequence stratigraphic division scheme is proposed. Based on this, a high-resolution stratigraphic framework is established, which provides accurate geological basis for subsequent comprehensive reservoir evaluation and sand body prediction.

A comparative machine learning study for lithology classification in volcano-fluvial deposits from La Vega de La Laguna (Tenerife, Canary Islands): application to core lithology log using all-elements and major elements approach

Palynostratigraphic, Paleoclimatic and Sequence Stratigraphic analyses were conducted in a section of Emi-4 well, Offshore Niger Delta to establish palynozones, relative age, paleodepositional setting and reconstruct paleoclimatic changes overtime within the section of the well. The intercalation of the sandy and shaly intervals of the section evidenced from lithologic, textural, and wire line log data suggested that the entire studied interval belong to the Agbada Formation. Thirty-six (36) ditch cuttings within 6,158 ft - 10,452 ft were subjected to standard palynological analysis involving sample maceration with 10% HCl and 40% HF acids to remove carbonates and siliceous components, neutralization with distilled water and sieving through 5-micron sieve, followed by separation of palynomorphs from residue and mounting on glass slides for microscopic analysis. Recovered palynomorphs are marked by dominance of pollen and spores over dinoflagellate cysts. The occurrences of age diagnostic palynomorphs such as Echiperiporites estelae, Belskipollis elegans, Verrutricolporites rotundiporus, Retribrevitricolpites protrudens, Pachydermites diederixi, Peregrinipollis nigericus, Cassoretitriletes vanraadshooveni, Magnastriatites howardii, Retistephanocolpites gracilis, Racemonocolpites hians, Praedapollis flexibilis, Elaeis guineensis, and Zonocostites ramonae at some intervals of the studied wells suggest early Miocene to late Miocene age. Three distinct interval palynostratigraphic zones were delineated using the international stratigraphic guide for the establishments of biozones, they are Racemonocolpites hians - Cyperaceaepollis sp. Zone (early Miocene); Gemmemonoporites sp. - Magnastriatites howardi Zone (middle Miocene) and Pachydemites diederixi - Retibrevitricolporites protrudens Zone (late Miocene). The sequence stratigraphic study identified Maximum Flooding Surfaces (MFS) within the well intervals along with the identification of Highstand Systems Tract (HST) and Transgressive Systems Tract (TST). Paleoclimatic interpretations based on palynological evidence suggest the presence of wet climatic conditions throughout the studied intervals, characterized by abundant mangrove, freshwater, and rainforest taxa.

Abstract Canals have been important structure for transporting water from one place to another for irrigation purposes across the globe. In the present scenario of increasing water scarcity, the significance of canals has increased manifold. Canals also suffer water leakages, which in turn contributes to the groundwater recharge. Thus, there is a strong need to study how the long‐term canal flow impacts groundwater recharge and improves its quality, especially in saline environments. The paper presents a detailed analysis of airborne electromagnetics (AEM) data acquired from a highly saline groundwater zone in the semi‐arid region of northwest India, where most of the irrigation has been met from the canal network for the past several decades. The study focuses on using AEM data, supported by borewell lithology and borehole electrical logs, to analyse the subsurface recharge induced by the canals and its impact on groundwater quality. Over the dense and sparse canal networks, AEM has identified different resistivity signatures. It shows high resistivity over the dunes and low resistivity in the clay‐dominated areas. A crescent‐shaped, 20–100 m thick zone with moderate to high resistivity has been observed below the canals within the low resistivity background, which indicates seepage and discharge from the canal. Moreover, changes in water quality (1994–2019) from borewells near the canal recharge zones show significant improvement in the groundwater quality, evidenced by a lowering of the electrical conductivity of groundwater. This recharge affects approximately 20% of the total study area. The total volume of canal‐induced recharge inferred from AEM resistivity is estimated to be ∼12,000 to ∼18,000 MCM.

ABSTRACT Groundwater resources across the country are swiftly heading towards depletion and quality deterioration. This study extensively examines the geological and hydrostratigraphic complexities in Thal Doab area, Punjab, Pakistan offering valuable insights into its subsurface lithology and groundwater quality. Data from twenty five (25) Vertical Electrical Soundings (VES) using Schlumberger electrode configuration were carefully analyzed, and calibration of resistivity models was performed by comparing them to lithological borehole logs to ensure their accuracy. The study establishes a fundamental connection between subsurface lithology and resistivity values, revealing four to six geo-electric sub-layers comprising the intermixing of clay, silt, sand, gravel, and kankar inclusions. These layers exhibit resistivity ranging from very low (<20 Ω-m) to very high (>230 Ω-m) at various depths. 2D/3D aquifer models identify the higher resistivity areas with promising good-quality groundwater primarily within sand, gravel, and kankar layers, while lower resistivity values indicate marginally suitable or saline/brackish groundwater within fine sediments like clays/silts. Groundwater quality improves significantly at depths below 75 m, suggesting sustainable water extraction potential. However, caution is advised while drawing water from depths below 50 m due to the presence of saline or brackish water, posing challenges due to limited recharge potential. The study emphasizes the importance of Indus and Chenab rivers, canal systems, and precipitation in the processes that recharge groundwater.

ABSTRACT Comprehensive mapping of the stratigraphy and structures is essential when exploring basaltic reservoirs for CO 2 storage. A major task in analysing the storage potential of the reservoir is to bring all relevant geological data within a single framework for integration and joint interpretation. In this study, we illustrate how data integration facilitates an improved understanding of the geological evolution of the Faroe Islands, the North Atlantic Igneous Province, and how the data integration forms a foundation for future carbon capture and storage campaigns. We have integrated new and existing data including geological field observations, digital elevation models, digital outcrop models, lithological logs, seismic profiles, and bathymetry in a single, consistent, and quality‐controlled toolbox. Two key findings are that (a) we have mapped stratigraphic markers in the central Faroe Islands across the islands, and there is no indication of large‐scale strike‐slip faults that offset the volcanic stratigraphy; (b) our analysis provides no clear onshore evidence of transfer zones in the Faroe Islands. We show that a high density of data and integration of data types across different vertical and horizontal scales is crucial for mapping the highly heterogeneous basaltic reservoir.

This paper presents a case study on the application of simultaneous inversion (SI) technique and well log analysis to accurately seismic-geomechanical characterization of Asmari formation in an Iranian oil field. To achieve this goal, a one-dimensional (1D) prediction of geomechanical properties such as Young’s modulus (E), bulk modulus (K), shear modulus (), Poisson’s ratio (PR), Vp/Vs ratio and brittleness (BRI) was first generated from the analyzing the well log data. In the next step, the spatial distribution of the geomechanical parameters in the reservoir area was predicted on the basis of the results of the simultaneous inversion. Lithological facies discrimination and fluid detection of the Asmari formation were performed using simultaneous inversion of pre-stack seismic data and conventional cross-plotting analysis of well data. To accomplish this objective, elastic and geomechanical parameters were cross-plotted against conventional petrophysical logs along with BRI, water saturation (Sw), gamma ray (GR), acoustic impedance (Zp), , and lithology logs such as quartz and calcite volumes. As a result of this work, two reservoirs were identified in the Asmari formation: sandstone and carbonate. The carbonate reservoir consists predominantly of calcite and dolomite, with minimal shale content, while the sandstone reservoir is mainly composed of shale and contains less quartz. In addition, the carbonate section within the Asmari formation exhibits better reservoir quality due to lower water saturation and higher porosity compared to the sandstone zone. To determine the type of fluid in the Asmari formation of the studied oil field, LMR (lambda-mu-rho) scatterplots were employed in both well and seismic domains. The findings reveal that the sandstone reservoir in the Asmari formation is water-saturated, while the carbonate reservoir is oil-saturated. Furthermore, a gas cap is present at the top of the Asmari formation.

The Middle Miocene-aged Jeribe Formation is an important reservoir in many of Iraq's oilfields. This study identifies the Jeribe Formation in several drilled wells at the Khurmala Dome Field using gamma-ray log and lithology analyses, comparing gamma-ray log analysis for the Jeribe Formation of a subset of wells at Khurmala Dome Field and two wells from Jari Pika Field and Taza Field. The lithology analyses of selected wells at Khurmala Field, along with the formation’s lithology, were studied at local types and other locations, which indicates the presence of the Jeribe Formation. The analysis results denoted its lateral continuity, lithology similarity, and thickness variations over location differences for the formation at selected wells of the Khurmala Dome Field. Both gamma-ray log and lithology analyses determined the interval's top, bottom, and thickness. Future studies should include biostratigraphy, correlation with wells drilled in the north part of the Khurmala Dome, gas and hydrocarbon analyses, and reservoir modeling to evaluate the amount of hydrocarbons within the formation.

Lithology identification plays a crucial role in reservoir characteristics, as it directly influences petrophysical evaluations and informs decisions on permeable zone detection, hydrocarbon reserve estimation, and production optimization. This paper aims to identify lithology and minerals composition within the Mishrif Formation of the Ratawi Oilfield using well log data from five open hole logs of wells RT-2, RT-4, RT-5, RT-6, and RT-42. At this step, the logging lithology identification tasks often involve constructing a lithology identification model based on the assumption that the log data are interconnected. Lithology and minerals were identified using three empirical methods: Neutron-Density cross plots for lithology identification, M-N cross plots (also known as Litho-porosity cross plots) for mineral identification, and Matrix identification (MID) plots. Neutron-density cross plots show that the Mishrif formation consists of limestone with some data points tending to the dolomite line east of the field and to the sandstone line west of the field. The M-N and MID plots indicate that calcite is the major mineral for the Mishrif formation; however, quartz grows to the west of the area while dolomite increases to the east. These findings underscore the importance of integrating multiple well-log interpretation techniques to capture lithologic and mineralogical complexity, providing critical insights for reservoir management and targeted exploitation strategies in heterogeneous carbonate systems.

ABSTRACT This study evaluates the effectiveness of four geophysical techniques—2D electrical resistivity tomography (ERT), 2D induced polarization (IP), 2D multi-channel analysis of surface waves (MASW), and downhole seismic tests—for determining the thickness of collapsible soils at two test sites. The 2D ERT survey is the most effective in accurately delineating vertical and lateral soil boundaries. This conclusion is validated by lithologic logs from boreholes and an excavated pit. The 2D MASW survey is the second most effective, followed by shear wave results from downhole seismic tests. In contrast, the 2D IP survey and compressional wave data from downhole seismic tomograms yield less distinct and more ambiguous soil boundaries. However, the 2D IP survey is useful for mapping clay content distribution within the subsurface. The non-destructive 2D ERT, 2D IP, and 2D MASW techniques provide high-resolution vertical and lateral subsurface coverage, potentially reducing the need for extensive borehole drilling.

Abstract. Caves are well-known archives that preserve valuable information about the past, relevant for reconstructing past climates and environments. We sampled sediments from a 480 cm deep profile, and 16S ribosomal ribonucleic acid (rRNA) gene-based metabarcoding analyses were undertaken that complemented lithological logging, sedimentology, and optically stimulated luminescence (OSL) dating. These analyses revealed different sedimentation conditions along the profile with various water inputs. The OSL age of the sediments places the profile between 74.7 ± 12.3 to 56 ± 8 ka (base to top). However, the more recent Last Glacial Maximum (LGM) paleofloods might have occurred in the upper and lower passages of the cave. Bacterial compositions changed with depth, from soil bacteria (present in the upper part of the sediment profile) to thermophilic/sulfurous bacteria (abundant in the deeper samples of the profile). Considering the thermophilic bacteria, we could only assume their origin from a surface of hot sulfurous springs, old thermal springs, or sapropel sediments.

Towed transient electromagnetics (tTEM) is applied in the Plateau Region of Togo for rapid and high-resolution characterization of groundwater systems surrounding six villages. Past drilling efforts in the region often resulted in unsuccessful or low-yielding boreholes, due in large part to sparse hydrogeologic data at the scale relevant for borehole siting surrounding each village. Towed transient electromagnetics systems are shown to be well suited to addressing this data sparsity issue, enabling the mapping of large regions surrounding each village in relatively short field times (two days per village in this work). Comparison with borehole lithology logs reveals that a towed electromagnetic system can accurately characterize the thickness of the weathered zone in gneissic settings, as well as delineate elevated saturation fractured zones within the gneissic bedrock in several cases. Boreholes drilled based on tTEM surveys were able to intercept fresh groundwater resources in each of the investigated villages.

Abstract The exposure of highly weathered rocks at the research location will affect the strength of the rock so a geological and geophysics approaches to creating subsurface lithology will make it easier to analyze the bearing capacity of soil in Suppa, Pinrang regency. The research aims to analyze subsurface lithology and soil bearing capacity based on correlations between soil mechanics and geophysics data. Data used in this research are the measurement of vertical electrical sounding (VES) Schlumberger configuration with one track, drilling, laboratory tests (test of shear strength, volume weight, specific gravity, and sieve analysis), and megascopic description of rocks. Terzaghi’s theory on the foundation (continuous, square, and circular) is used for the analysis of soil bearing capacity. Correlation of drill data with geoelectrical data and electrical logging lithology of the study area interpreted at a depth of 0-2.1 m silt sand, 2.1-7.2 m depth of clay, and 7.2-70 m depth of volcanic breccia. The results of the ultimate soil bearing capacity analysis on the first sample of silt sand (continuous, square, and circular foundations, 50-400 m wide) is 147.48 – 427.11 kg/cm2 are classified as very good condition. The second sample with the value of ultimate soil bearing capacity of 72.63 - 109.07 kg / cm2 is classified as a medium - good condition. Based on these results, the first sample has a higher soil bearing capacity than the second sample. Circular foundations have the greatest soil bearing capacity, so a circular foundation is recommended at that location.