Resistivity Log Data Research Articles

Assessing the application of ultradeep azimuthal electromagnetic resistivity tools in detecting igneous formations ahead of the transmitter

The Faroe–Shetland basin (FSB) is considered challenging for oil and gas exploration due to its complex geological structure and limited exploration drilling activity. The costs of drilling in the basin are the most expensive within the United Kingdom Continental Shelf (UKCS) due to varying geological and engineering challenges. The prevalence of igneous sill complexes within the basin present drilling hazards that contribute to drilling nonproductive time (NPT) and are documented in multiple studies. Recent advancements in ultradeep azimuthal resistivity (UDAR) technology which utilizes the look-ahead portion of the electromagnetic (EM) signal presents an opportunity to assess its suitability as a derisking tool to ‘look-ahead’ and detect igneous intrusions in volcanic basins. This paper utilizes resistivity log data from Well 214/28-1, which encountered multiple igneous intrusions and is used to validate the ability of these tools to detect the intrusions. The EM look-ahead technology detected with good confidence the top of an igneous intrusion 72 ft (22 m) true vertical depth (TVD) ahead of the transmitter and once drilled, detect the base of the intrusion 54 ft (16 m) TVD ahead of transmitter. The detection of the intrusions prior to drilling and information on intrusion thickness can enable proactive drilling decisions to reduce nonproductive time.

Evaluating methods for logging the pore structure of tight sandstone reservoir in Chang 6 member of the Yanchang Formation, Ordos Basin

Pore structure is a key parameter used to evaluate reservoir quality. At present, experimental method is the most important method to analyze reservoir pore structure. However, coring data may be limited, and it is not possible to perform experimental analyses on all cores. Therefore, the researchers explored the use of logging techniques to study the pore structure of reservoirs. The relationship between pore geometry index (PGI), pore permeability and mercury injection parameters was analyzed based on mercury injection experiment, thin slice analysis, production test data and well logging data. These results can then determine the response characteristics of the logging parameters that correspond to different pore structures and establish a method of modeling the PGI through a multiple parameter regression and neural network method. This research shows that: (1) PGI can quantitatively characterize pore structure, and the maximum pore throat radius, displacement pressure and flow unit index have the highest correlation with PGI, which can be accurately characterized by practical formulas; (2) Natural gamma ray, natural potential amplitude difference, acoustic transit time, density, compensated neutron, deep and shallow resistivity logging data can reflect the quality of the reservoir pore structure. However, there are limitations in evaluating reservoir pore structure with a single logging parameter. Multi-parameter regression method and neural network method realize the quantitative calculation of pore structure from the perspective of multi-parameter and nonlinear. (3) The neural network method and multiple parameter regression method are used to study the pore structure of reservoir and realize the continuous quantitative calculation of pore structure index in a single well. It can be used in uncored analysis Wells and as one of the parameters to evaluate reservoir pore structure.

A new insight for geophysical and geospatial mapping quaternary alluvium of Indo-Gangetic plains for exploration and assessment of groundwater in Haryana, India

A comprehensive study on groundwater exploration and assessment was conducted, integrating geophysical, geological, lithological, and resistivity logging techniques for a holistic evaluation of groundwater resources in Haryana, India. The primary research objective was to gain insight into the geological composition of alluvial sand and its implications for groundwater occurrence in Haryana's semi-arid region. The study showcases high-resolution electrical resistivity tomography results alongside conceptual cross-sectional models and 3D lithological models, revealing buried channels that serve as groundwater sources and saturated sand as well as recharge conduits within the alluvial region of Haryana. Moreover, borehole drilling at two sites and resistivity logging data demonstrate a strong correlation between various lithologies and resistivity logs. Overall, groundwater prospect zones are delineated at depths ranging from 18 m to over 100 m based on resistivity values of aquifer zones inferred from electrical resistivity tomography models, as well as mapped thick sand layers with significant hydrogeological importance in the study area. This emphasizes the stress on the aquifer system, where groundwater is being extracted from deeper depths. The conceptual litho-sectional model reveals a thick sand signature at intermediate depths, indicating the presence of buried paleochannels extending from Galedwa (Kurukshetra) to Jubbal (Yamunanagar). Additionally, the 3D lithological models, along with the electrical resistivity tomography results, facilitate strategic planning for shallow and deep boreholes for groundwater exploration and prospecting, aiming at sustainable groundwater development and management of resources in both the present and future.

Geosteering based on resistivity data and evolutionary optimization algorithm

Currently, the oil and gas industry faces numerous challenges in addressing geosteering issues in horizontal drilling. To optimize the extraction of hydrocarbon resources and to avoid penetration in aquifers, industry experts frequently modify the drilling trajectory using real-time measurements. This approach involves quantifying subsurface uncertainties in real-time, enhancing operational decision-making with more informed insights but also adding to its complexity. This paper demonstrates an approach to decision making for trajectory correction based on real-time formation evaluation data and the differential evolution algorithm. The approach uses volumetric resistivity log data and data from reservoir models, such as porosity. The provided methodology suggests corrections for planned well trajectories by maximization of the objective function. The objective function operates with a calculated hydrocarbon saturation environment as the decision-making system in a virtual sequential drilling process. To demonstrate the accuracy and reliability of our approach, we compared the simulations of the corrected trajectory with the preliminary trajectory drilled in the same area. In addition, we conducted several experiments to tune the hyper-parameters of the differential evolution algorithm to select the optimal parameter set for our case study and compared proposed differential evolution algorithm with particle swarm optimization and pattern search algorithms. The results of our experiments showed that the real-time formation evaluation data combined with the differential evolution algorithm outperformed a trajectory provided by the drilling engineers. Differential evolution algorithm demonstrated strong performance compared to others optimization algorithms. We have implemented a complete pipeline from generating resistivity and porosity cubes, using the Archie equation to estimate oil saturation, and consequently generating a corrected trajectory in this cube based on near-well data, angle constraints and predefined hyper-parameters set prior to well trajectory planning. The methods developed were validated on synthetic and real datasets. Our decision-making system shows better cumulative oil saturation values than the preliminary provided horizontal well.

Optimization of gas saturation calculation model for deep clastic reservoirs under strong compression stress

The interpretation model for gas saturation in deep clastic reservoirs subject to intensive extrusion stress relies predominantly on experimental petrophysical data and the expanded Archie equation. Nonetheless, these methodologies may not consistently yield optimum results. Specifically, when subsurface pressure impacts formation resistivity, the resulting curve values exhibit substantial elevations, leading to significant inaccuracies in the precise estimation of gas saturation from resistivity logging data. Consequently, the evaluation of logging interpretations becomes a complex undertaking. This paper aims to comprehensively assess gas saturation in deep clastic reservoirs from both electrical and mechanical perspectives. To achieve this goal, we employ a multifaceted approach encompassing the Archie formula, the stress-corrected variable cementation index saturation model, and the resistivity-corrected saturation model. Through rigorous theoretical analysis and the utilization of simulated experimental data, a quantitative relationship equation between resistivity and stress difference has been established. Building upon this fundamental groundwork, an innovative resistivity-corrected saturation calculation model has been proposed. In comparison to the two alternative models, the new model exhibits enhanced accuracy in calculating gas saturation, as it is less influenced by extrusion stress and gravitational compaction. Furthermore, it demonstrates better consistency with core mercury injection capillary pressure data in determining gas saturation. The findings of this research provide valuable insights for the effective evaluation of deep clastic reservoirs, offering a robust framework for advancing the understanding of gas saturation in the face of complex geological and geophysical challenges.

EVALUATION OF THE EFFICIENCY OF ELECTRIC LOGGING METHODS WHEN STUDYING TIGHTNESS OF CASING STRINGS IN WELLS OF URANIUM DEPOSITS

Link for citation: Sharapatov A., Assirbek N., Samanbetov N. Evaluation of the efficiency of electric logging methods when studying tightness of casing strings in wells of uranium deposits. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 10, рр. 7-15. In Rus. The relevance. When exploiting uranium deposits using the method of in-situ leaching, many problematic issues arise. Among them, it is possible to distinguish a violation of the integrity and tightness of the polymer casing, which leads to leakage of solutions due to defects and threaded connections, colmatation, etc. With the help of geophysical wells surveys, namely current logging and resistivity logging, there is a technological possibility of obtaining actual data on the leakage of solutions into the near-wellbore space (their location, size). The distribution of solutions in the annulus lead to technological and environmental violations during the development of deposits. The main aim: comparative evaluation of the effectiveness of current logging and resistivity logging in solving technological problems – assessment of the integrity of polymer pipes and tightness of threaded connections in the casing of uranium wells and determination of the parameters of liquidation of wells with damaged columns based on the data of current logging or resistivity logging in the casing. Objects: artificial defects in the casing for experimental work: holes in pipes with different diameters and locations, leaky connections of casing pipes. Methods. The work was carried out at one of the sites of the Shu-Sarysu province uranium deposit and includes the following activities: preparation of polymer casing strings for the experiment; physical and technical justification of using geophysical wells surveys methods to study the problem; performing measurement work by current logging and resistivity logging methods; performing computational work using current logging, resistivity logging readings and obtaining values of a probabilistic parameter for evaluation of the state of the casing strings and the decision on the operation of wells; comparative analysis and drawing conclusions on the informativeness of borehole geophysical (electrical) methods. Results. Research results showed that to solve the problem of monitoring the technical condition of casing strings, the use of the resistivity logging method is optimal. The conclusions of the research are based on the analysis of the nature of changes in the diagrams of the electrical methods of current logging and resistivity logging, the sensitivity of the measured values of the electric field to defects in the casing. The quantitative values of the parameter % ANO – the amount of current leakage (anomalies) obtained by calculation according to current logging and resistivity logging data are probabilistic in nature. They made it possible to develop recommendations for making technological and/or managerial decisions on the condition of casing strings and the further use of production wells with various defects in them.

Real-Time Rock-Properties Estimation for Geosteering: Statistical Rock-Physics-Driven Inversion of Seismic Acoustic Impedance and LWD Ultradeep Azimuthal Resistivity

Summary This work describes a statistical rock-physics-driven inversion of seismic acoustic impedance (AI) and ultradeep azimuthal resistivity (UDAR) log data, acquired while drilling, to estimate porosity, water saturation, and facies classes around the wellbore. Despite their limited resolution, seismic data integrated with electromagnetic resistivity log measurements improve the description of rock properties by considering the coupled effects of pore space and fluid saturation in the joint acoustic and electrical domains. The proposed inversion does not explicitly use a forward model, rather the correlation between the petrophysical properties and the resulting geophysical responses is inferred probabilistically from a training data set. The training set is generated by combining available borehole information with a statistical rock-physics modeling approach. In the inversion process, given colocated measurements of seismic AI and logging-while-drilling (LWD) electromagnetic resistivity data, the pointwise probability distribution of rock properties is derived directly from the training data set by applying the kernel density estimation (KDE) algorithm. A nonparametric statistical approach is used to approximate nonsymmetric volumetric distributions of petrophysical properties and to consider the characteristic nonlinear relationship linking water saturation with resistivity. Given an a priori facies classification template for the samples in the training set, it is possible to model the multimodal, facies-dependent behavior of the petrophysical properties, together with their distinctive correlation patterns. A facies-dependent parameterization allows the effect of lithology on acoustic and resistivity responses to be implicitly considered, even though the target properties of inversion are only porosity and saturation. To provide a realistic uncertainty quantification of the estimated rock properties, a plain Bayesian framework is described to account for rock-physics modeling error and to propagate seismic and resistivity data uncertainties to the inversion results. In this respect, the uncertainty related to the scale difference among the well-log data and seismic is addressed by adopting a scale reconciliation strategy. The main feature of the described inversion lies in its fast implementation based on a look-up table that allows rock properties, with their associated uncertainty, to be estimated in real time following the acquisition and inversion of UDAR data. This gives a robust, straightforward, and fast approach that can be effortlessly integrated into existing workflows to support geosteering operations. The inversion is validated on a clastic oil-bearing reservoir, where geosteering was used to guide the placement of a horizontal appraisal well in a complex structural setting. The results show that the proposed methodology provides realistic estimates of the rock-property distributions around the wellbore to depths of investigation of 50 m. These constitute useful information to drive geosteering decisions and can also be used, post-drilling, to update or optimize existing reservoir models.

Estimation Pore and Fracture Pressure Based on Log Data; Case Study: Mishrif Formation/Buzurgan Oilfield at Iraq

Prediction of the formation of pore and fracture pressure before constructing a drilling wells program are a crucial since it helps to prevent several drilling operations issues including lost circulation, kick, pipe sticking, blowout, and other issues. IP (Interactive Petrophysics) software is used to calculate and measure pore and fracture pressure. Eaton method, Matthews and Kelly, Modified Eaton, and Barker and Wood equations are used to calculate fracture pressure, whereas only Eaton method is used to measure pore pressure. These approaches are based on log data obtained from six wells, three from the north dome; BUCN-52, BUCN-51, BUCN-43 and the other from the south dome; BUCS-49, BUCS-48, BUCS-47. Along with the overburden pressure gradient and clay volume, which were also established first, data such as gamma ray, density, resistivity, and sonic log data are also required. A key consideration in the design of certain wells is the forecasting of fracture pressure for wells drilled in the southern Iraqi oilfield of Buzurgan. The pressure abnormality is found in MA, MB21, MC1 and MC2 units by depending on pore pressures calculated from resistivity log. In these units, depths and its equivalent normal and abnormal pressure are detected for all sex selected wells; BUCS-47, BUCS-48, BUCS-49, BUCN-43, BUCN-51 and BBCN-52. For MA, MB21, MC1, and MC2 units, the highest difference in pore pressure values are 1698 psi @ 3750 m (BUCN-51), 3420 psi @ 3900 m (BUCN-51), 788 psi @ 3980 m (BUCS-49), and 5705 psi @ 4020 m (BUCN-52). On other hands, MB11 and MB12 units have normal pressure trend in all studied wells. Finally, the results show that the highest pore and fracture pressure values is existed in North dome, in comparison with that obtained in south dome of Mishrif reservoir at Buzurgan oilfield.

Corrections of logging-while-drilling electromagnetic resistivity logging data acquired from the horizontal well for the shale oil reservoir

Corrections of logging-while-drilling electromagnetic resistivity logging data acquired from the horizontal well for the shale oil reservoir

Saturation evaluation for fine-grained sediments

Accurate quantification of the gas hydrate content in the deep sea is useful for assessing the resource potential and understanding the role of gas hydrates in the global carbon cycle. Resistivity logging data combined with Archie's equation are often used to calculate gas hydrate saturation, but the reliability is dependent on the rationality of the empirical parameter cementation factor and saturation index. At present, an increasing number of fine-grained hydrate-rich sediment regions have been discovered worldwide through drilling efforts, and the reservoir types and hydrate distribution are diverse, which differs greatly from that of coarse-grained reservoirs of hydrate-bearing sediment. This results in vertical variations in m and n through stratigraphy. At present, the saturation evaluation effect of these reservoirs cannot be improved. In this work, a theory for the determination of the cementation factor and saturation index was first proposed to obtain reliable and variable values of the empirical parameters. Then, a hydrate saturation evaluation technique with variables m and n was formed based on the well logging data. This technique was used to evaluate complex fine-grained hydrate-bearing reservoirs in several regions worldwide. It was found that the highest n could be 16, and the log calculation results were more consistent with the core hydrate saturation. Additionally, the cause of the excessively high n values was explained from physical principles, and the result was verified with actually well log data. In future evaluations of the amount of hydrate resources in fine-grained sediment reservoirs worldwide, new saturation estimation methods should be taken into account to advance hydrate research.

Accounting for tilted electrical anisotropy in numerical simulation and interpretation of resistivity logging data (analytical review based on national and foreign literature)

Features and main conclusions of publications devoted to the study of medium transverse-isotropic geoelectric models which are characterized by inclination of the electrical anisotropy axis relative to a logging tool are reviewed in this article. Such models can be defined either by horizontal and vertical conductivities (or their reciprocals, called resistivities) with a non-zero dip of a logging tool or by the conductivity tensor with the tilt of the principal axes.

GSTAR (1,1) Modeling with Time-Correlated Errors for Geoelectric Resistivity Log Data in Pontianak City

Planting of concrete piles on the soil surface must reach a layer of rock/soil that is hard enough for the building to stand firmly. Rock/soil layers can be studied through geoelectric resistivity log data. We require tools with high prices and need a complicated process to obtain such data. Therefore, a mathematical model is developed to explore geological formations using a space-time model to overcome these problems. The generalized space-time autoregressive (GSTAR) model can be applied to the resistivity data. However, this data correlates with each rock layer. Therefore, we develop a GSTAR model for time-correlated errors. In our study, the parameter index, usually for a concrete time, is applied to the relative time in the form of rock layers. This research uses geoelectric resistivity log data at six locations in Pontianak City, namely Untan 1, Untan 2, Untan 3, Jl. Sawo, Jl KPM Permai, and Gg. Beringin. The GSTAR(1,1) model with time correlation error results in an average RMSE value of 9.51605 Ωm. In addition, we obtain that the most profound peat soil depth is 17.9 m from the surface and is located in the Untan 3.Keywords: GSTAR (1,1); martingale difference; peat soil; resistivity; time-correlated error. AbstrakPenanaman tiang pancang beton pada tanah gambut harus mencapai lapisan batuan/tanah yang cukup keras agar bangunan dapat berdiri kokoh. Lapisan batuan/tanah dapat dipelajari melalui data log resistivitas geolistrik yang memerlukan alat yang mahal dan proses yang rumit untuk mendapatkan datanya. Untuk mengatasi permasalahan tersebut, dibuatlah model matematika untuk mengeksplorasi formasi geologi menggunakan model ruang-waktu. Salah satu model yang dapat diaplikasikan adalah generalized space-time autoregressive (GSTAR). Pada umumnya, data ini memiliki korelasi antarlapisan batuan. Oleh karena itu, pada penelitian ini dikembangkan model GSTAR untuk galat yang berkorelasi waktu. Indeks parameter yang biasanya menggunakan waktu konkret, pada penelitian ini diterapkan pada waktu relatif berupa lapisan batuan. Model ini disebut GSTAR dengan galat berkorelasi waktu. Data yang digunakan adalah data resistivitas geolistrik pada enam lokasi di Kota Pontianak Indonesia yang dinamakan Untan 1, Untan 2, Untan 3, Jl. Sawo, Jl KPM Permai, dan Gg. Beringin. Hasil menunjukkan bahwa model GSTAR(1,1) dengan galat berkorelasi waktu berhasil mengestimasi nilai resistivitas geolistrik di keenam lokasi tersebut dengan nilai rata-rata geometri dari RMSE sebesar 9,51605 Ωm. Selain itu, model ini pun berhasil memperkirakan kedalaman tanah gambut terdalam (dari permukaan tanah) yang terletak di lokasi Untan 3 yaitu 17,9 m.Kata Kunci: GSTAR(1,1); pembeda martingale; tanah gambut; resistivitas; galat berkorelasi waktu. 2020MSC: 62P30

Joint numerical inversion of resistivity logging data in vertical wells of the Imilorskoye field

The paper considers an example of applying a joint 2D numerical inversion to the resistivity logs measured at complex sediments intervals of the Imilorskoye field. Complex structure of the sediments makes it difficult to use the traditional interpretation techniques for processing resistivity logs. This leads to the need to find new interpretation approaches, such as joint 2D inversion of resistivity logs obtained by different geophysical methods, which makes it possible to retrieve more reliable estimates of complex sediments electrophysical properties. Due to the lack of measurements taken by modern equipment in old wells, the proposed approach for improving the accuracy of the retrieved electrophysical parameters in this work is a joint 2D inversion of unfocused lateral logging sounding data, focused lateral and low-frequency induction logs.

A Method for the Inversion of Reservoir Effective Permeability Based on Time-Lapse Resistivity Logging Data and Its Application

Effective permeability is a key parameter for evaluating reservoirs and their productivity. With the wide application of resistivity logging tools in drilling, the advantages of resistivity logging in response to the dynamic invasion process of drilling fluids have become increasingly prominent. We analyzed the variation law of the measured resistivity data for different permeability formations at different times. In this study, we proposed an effective permeability modeling method based on the time-lapse resistivity logging data. First, based on the resistivity measurement data at different times, the dynamic resistivity profile of the reservoir was obtained through joint inversion; we then obtained the invasion depth and invasion zone resistivity of the drilling fluid at different times, along with the original formation resistivity. Subsequently, combined with parameters such as the soaking time, fluid viscosity, and saturation change of the drilling fluid, we obtained the phase permeability curve of the reservoir and dynamic effective permeability of the fluid near the wellbore. This study provides basic parameters for subsequent formation analyses and productivity prediction and substantially improves the reservoir evaluation technology from static to dynamic.

Estimation Of Water Saturation In Carbonate Reservoirs Without Resistivity Log Data. Part I: Theory And Existing Model

This paper presents an observation over a suggested approach for establishing water saturation model that is specifically designed without the need of resistivity log data. One of the main strength of the approach is that the resulting water saturation model can be specifically established for local or specific use only. This is true since the approach can be applied using carbonate rocks that are obtained locally or from specific areas. Another important conclusion is that this approach can also be applied for any carbonate rock classification as long as the classification can clearly group carbonate rocks into groups with distinctive petrophysical properties. This paper – first part of two – presents theory and rock classification that underlines the approach, as well as procedure and the existing models available.

ESTIMATION OF WATER SATURATION IN CARBONATE RESERVOIRS WITHOUT RESISTIVITY LOG DATA. PART I: THEORY AND EXISTING MODEL

This paper presents an observation over a suggested approach for establishing water saturation model that is specifically designed without the need of resistivity log data. One of the main strength of the approach is that the resulting water saturation model can be specifically established for local or specific use only. This is true since the approach can be applied using carbonate rocks that are obtained locally or from specific areas. Another important conclusion is that this approach can also be applied for any carbonate rock classification as long as the classification can clearly group carbonate rocks into groups with distinctive petrophysical properties. This paper – first part of two – presents theory and rock classification that underlines the approach, as well as procedure and the existing models available.

Pore-Scale Investigation of the Electrical Property and Saturation Exponent of Archie’s Law in Hydrate-Bearing Sediments

Characterizing the electrical property of hydrate-bearing sediments is essential for hydrate reservoir identification and saturation evaluation. As the major contributor to electrical conductivity, pore water is a key factor in characterizing the electrical properties of hydrate-bearing sediments. The objective of this study is to clarify the effect of hydrates on pore water and the relationship between pore water characteristics and the saturation exponent of Archie’s law in hydrate-bearing sediments. A combination of X-ray computed tomography and resistivity measurement technology is used to derive the three-dimensional spatial structure and resistivity of hydrate-bearing sediments simultaneously, which is helpful to characterize pore water and investigate the saturation exponent of Archie’s law at the micro-scale. The results show that the resistivity of hydrate-bearing sediments is controlled by changes in pore water distribution and connectivity caused by hydrate formation. With the increase of hydrate saturation, pore water connectivity decreases, but the average coordination number and tortuosity increase due to much smaller and more tortuous throats of pore water divided by hydrate particles. It is also found that the saturation exponent of Archie’s law is controlled by the distribution and connectivity of pore water. As the parameters of connected pore water (e.g., porosity, water saturation) decrease, the saturation exponent decreases. At a low hydrate-saturation stage, the saturation exponent of Archie’s law changes obviously due to the complicated pore structure of hydrate-bearing sediments. A new logarithmic relationship between the saturation exponent of Archie’s law and the tortuosity of pore water is proposed which helps to calculate field hydrate saturation using resistivity logging data.

Inversion based on deep learning of logging-while-drilling directional resistivity measurements

Because of the response complexity and real-time interpretation required by geosteering, an efficient and reliable inversion method for logging-while-drilling (LWD) directional resistivity measurement is important. A three-layer parametric inversion method based on deep learning has been developed. The inversion process includes two steps. The first step is the inversion of formation parameters, such as the resistivity and distance to boundary, and the second step is the uncertainty estimation of the inversed parameters, to remove the low-quality inversed boundaries. The input of the first part of the inversion is the directional resistivity logging data. The input of the second step is the output of the first step. The second step is based on the relationship between the output error and the value of each output parameter of the first step. A synthetic example shows the original results of the first step of the inversion have some low-quality false boundaries, such as some of the ones in thick layers. By estimating the uncertainty and distinguishing the low-quality boundary in the second step, these false boundaries can be effectively removed.

Designing Aquifer Model for the Banks of the Serayu River, Sokawera, Somagede, Banyumas, Indonesia by Means of 1D-Electrical Resistivity Data

A geoelectric survey using the 1D-electrical resistivity method was applied to design a groundwater aquifer model for the banks of the Serayu River in Sokawera Village, Somagede District, Banyumas Regency, Indonesia. The aim of this research was to identify the characteristics of aquifers in the research area based on resistivity log data. Acquisition, modeling, and interpretation of resistivity data were carried out and the results were lithological logs at seven sounding points. Correlation between the lithological logs resulted in a hydrostratigraphic model. This model is composed of several hydrological units, i.e. shallow aquifer, aquitard, and deep aquifer. The shallow aquifers are composed of sandy clay (10.81-18.21 Wm) and clayey sand (3.04-7.43 Wm) with a depth of groundwater from the water table to 27.51 m. The deep aquifers are composed of sandstone with variation of porosity (2.24-12.04 Wm) at a depth of more than 54.98 m. Based on this model, potential shallow aquifers were estimated to be at sounding points Sch-5, Sch-6, and Sch-7. This hydrostratigraphic model shows that the two types of aquifers are separated by an aquitard layer, allowing groundwater infiltration from the shallow aquifer to the deep aquifer and vice versa. Moreover, the Serayu riverbanks in this research area are estimated to be a groundwater discharge area.

Application of GSTAR(1,1) model for layer peat soil predicted based on resistivity log data

In this study, GSTAR modeling was carried out with the inverse of distance weight matrix obtained from Geoelectrical Resistivity data at several peatland locations around the Universitas Tanjungpura, Pontianak. This data can identify the subsurface layer of the soil through the electric current that binds into the soil. However, due to the limitation of the tool to measure the resistivity value, it can only measure 1/5 of the depth of the observation length. To overcome this problem, predictions are made at the next depth using the GSTAR model. The study began by measuring the resistivity value of the land using the geoelectric method and mapping it. Through this GSTAR modeling, predictions are made for the unobserved subsurface to determine the type of soil layer. Knowing the type of deeper soil layer can help contractors build plant concrete stakes to keep buildings safe on peatland. The results of the GSTAR(1.1) model are not accurate enough to estimate the resistivity value data. This is possible because the correlation between rock ages is not the same, so further analysis is required.