Log Conductivity Research Articles

Experimental study on transient electromagnetic conductivity logging in cased well

Experimental study on transient electromagnetic conductivity logging in cased well

Integrated workflow incorporating the Hurst exponent and interval inversion for evaluating groundwater formations

A novel well-log-analysis approach is presented for an improved prediction of petrophysical properties in groundwater formations. Geophysical well logs are simultaneously processed for quantifying the lithology, storage capacity, and water flow parameters. A fully automated data processing workflow is proposed, the feasibility of which is assured by an appropriate starting model set by the joint application of factor analysis and the Hurst exponent, and a solution of a highly overdetermined inverse problem. The Hurst exponent is used for zone boundary detection, which assists the series expansion-based interval inversion method applied for estimation of the petrophysical parameters of clastic formations. The hydraulic conductivity as a well log is directly derived from the inversion results. The workflow is tested using both synthetic data contaminated with 5% Gaussian distributed noise and real data collected from a thermal water well in Baktalórántháza, eastern Hungary. At the test site, the Hurst exponent extracted from the wireline logs allows one to divide the processed interval into subzones around the Pleistocene-Miocene boundary. The observed wireline logs are inverted to estimate the volumetric parameters (porosity, shale content, water saturation, etc.) of the same zones. The predicted parameters, including hydraulic conductivity, reveal that Pleistocene sediments contain good aquifers with formation quality varying with depth. The shale volume and hydraulic conductivity logs show a proper match with the core data, which confirms the results of the comprehensive analysis. The suggested workflow is recommended for the evaluation of groundwater formations located in different depth domains, from unsaturated sediments to geothermal reservoirs.

Quantification of mixed hydrate and free gas concentrations by the joint integration of velocity and conductivity information

Quantification of gas hydrates in marine sediments is crucial for understanding gas hydrate systems. By empirical relationships or effective medium modelling, gas hydrate concentrations can be derived from velocity and/or conductivity logs. However, these approaches do not take the co-occurrence of free gas and gas hydrate into account leading to large uncertainties in the calculated free gas and gas hydrate concentrations. To overcome this issue we adopt a joint elastic and electric self-consistent/differential effective medium model as the basis for a new joint inversion scheme that distinguishes between both phases. We apply this scheme to p-wave velocity and electric induction data measured by downhole-logging of boreholes at Formosa Ridge off Taiwan - a known hydrate province with an active gas conduit. Gaussian Mixture Modeling separates the background signal of the host medium from anomalies and allows to determine a background porosity as a probability density function of depth. We use this derived porosity to jointly invert electrical conductivity and velocity data for hydrate and free gas concentrations. At Formosa Ridge, we find two resistive anomalies, one in the shallow and another in the deep part of the borehole. Only the deep anomaly in conductivity coincides with a high-velocity anomaly. This is consistent with ∼30% hydrate with ∼1% free gas concentration. For the shallow anomaly, increased velocities due to hydrate concentrations of ∼15% are compensated by a decrease in velocity due to ∼1% of free gas. The method reconciles the different sensitivities of the two data types and yields hydrate and free gas concentrations that are largely consistent with geochemically derived values.

Revised models for evaluating hydrocarbon saturation of tight sandstone formations based on dielectric dispersion logs

AbstractAccurate estimation of hydrocarbon saturation is significant for log interpreters to evaluate tight sandstone formations. It is difficult to use conventional wireline logs to calculate hydrocarbon saturation in complex reservoirs. Dielectric dispersion logs are processed using dielectric models to obtain accurate saturation assessment, especially in high salinity shaly sand formations. However, the dielectric models consist of complex refractive index method model and shaly sand model ignore the impact of clay effects on complex refractive index method model, and the dielectric dispersion logs generated by them appear several unphysical phenomena in the clay‐bearing formations, such as the permittivity data at the highest frequency are greater than those at the second highest frequency and the conductivity data at the highest frequency are lower than those at the second highest frequency. This paper modifies the dielectric models by introducing a combined conductive phase in complex refractive index method model to correct the unphysical behaviours. Revised models are combined with four permittivity and four conductivity logs acquired by dielectric scanner at 24, 102, 360 and 960 MHz to inverse the water saturation, water salinity, textural index for water‐bearing pore and fraction of clay‐related phase. The complex refractive index method model interprets the logs measured at 960 MHz and shaly‐sand model interprets other dielectric dispersion logs. The particle swarm optimization algorithm is used to search inversion parameters. The results of forward simulation show that the revised models can correct unphysical behaviours of dielectric dispersion logs generated by the original models. Moreover, we apply original models and revised models to laboratory core data. The results of experiments show that the mean relative error values of the original models are 19.38% and 23.60% and of the revised models are 5.54% and 6.28% in two cases. It shows that the revised models are more accurate than the original models to interpret dielectric dispersion logs of tight sandstone reservoirs.

Terrestrial heat flow measurement and numerical simulation of lithospheric thermal structure in western Sichuan, China

The western Sichuan in the eastern Qinghai-Tibet plateau has significant geothermal potential. Heat flow is one of the most important parameters in geothermic, its measurement can help obtain a better understanding of the regional lithospheric thermal structure. In this study, we reported 4 heat flow data based on the continuous steady-state temperature logging and rock thermal conductivity test, including two class-A and two class-D data. Furthermore, we calculated the lithospheric thermal structure by a 2D steady-state thermal conduction equation in COMSOL, analyzing the lateral differences of lithospheric thermal structure in the eastern Qinghai-Tibet plateau. Our study has determined that the heat flow values in the western Sichuan range from 94.7 to 116.2 mW/m2, with a corresponding geothermal gradient of 32.1–37.3 °C/km. Moreover, numerical simulation results indicate significant differences in lithospheric thermal structure between western Sichuan and Sichuan Basin, where the Longmen Shan fault zone is a crucial regional tectonic boundary and a significant temperature gradient zone. Specifically, the Moho temperature in the western Sichuan region ranges from 1000 to 1200 °C with an average temperature of 1060 °C, while the Sichuan Basin ranges from 600 to 700 °C. Besides, the thermal lithosphere thickness in the western Sichuan and the Sichuan Basin is 88–97 km and 105–110 km, respectively. These observations suggest that the western Sichuan region is characterized by high thermal anomaly and provide theoretical evidence for the geodynamic and geothermal development in this area. Finally, we suggest that the high thermal anomaly in western Sichuan is the result of a combination of factors, such as thickened crust, high radioactive heat production, and shear frictional heating from deep fault and so on.

Aquifer Storage and Recovery Feasibility Study With Flowing Fluid Electrical Conductivity Logging in Shallow Aquifers of South Bihar, India

Growing dependence on groundwater to fulfill the water demands has led to continuous depletion of groundwater levels and, consequently, poses the maintenance of optimum groundwater and management challenge. The region of South Bihar faces regular drought and flood situations, and due to the excessive pumping, the groundwater resources are declining. Rainwater harvesting has been recommended for the region; however, there are no hydrogeological studies concerning groundwater recharge. Aquifer storage and recovery (ASR) is a managed aquifer recharge technique to store excess water in the aquifer through borewells to meet the high-water demand in the dry season. Therefore, this paper presents the hydrogeological feasibility for possible ASR installations in shallow aquifers of South Bihar with the help of flowing fluid electrical conductivity (FFEC) logging. For modeling, the well logging data of two shallow borewells (16- and 47-m depth) at Rajgir, Nalanda, were used to obtain the transmissivity and thickness of the aquifers. The estimated transmissivities were 804 m2/day with an aquifer thickness of 5 m (in between 11 and 16 m) at Ajatshatru Residential Hall (ARH) well. They were 353 and 1,154 m2/day with the aquifer thicknesses of 6 m (in between 16 and 22 m) and 2 m (in between 45 and 47 m), respectively, at Nalanda University Campus (NUC) well. Despite the acceptable transmissivities at these sites, those aquifers may not be fruitful for the medium- to large-scale (more than 100-m3/day injection rate) ASR as the thickness of the aquifers is relatively small and may not efficiently store and withdraw a large amount of water. However, these aquifers can be adequate for small (up to 20-m3/day injection rate) ASR, for example, groundwater recharge using rooftop water. For medium- to large-scale ASR, deeper aquifers need to be further explored on these sites or aquifers with similar characteristics.

A revised mid-Pliocene composite section centered on the M2 glacial event for ODP Site 846

Abstract. The composite section from ODP Site 846 has provided key data sets for Pliocene stable isotope and paleoclimatic time series. We document here apparent outliers in previously published data sets for stable isotopes and alkenone-derived sea surface temperature (SST) estimates in the Pliocene interval containing the M2 glaciation (ca. 3.290–3.3 Ma) by tying high-resolution core measurements to a continuous downhole conductivity log. We generate a revised sequence of new stable isotopic and alkenone measurements across the M2 event that correlate well to the revised splices of color reflectance and gamma ray attenuation porosity evaluator data from Site 846, and to a new composite section produced at equatorial Pacific ODP Site 850. A new composite splice for Site 846 is proposed, along with composite isotope and alkenone time series that should be integrated into revised Pliocene paleoclimatic stacks.

Gradient Self-Potential Logging in the Rio Grande to Identify Gaining and Losing Reaches across the Mesilla Valley

The Rio Grande/Río Bravo del Norte (hereinafter referred to as the “Rio Grande”) is the primary source of recharge to the Mesilla Basin/Conejos-Médanos aquifer system in the Mesilla Valley of New Mexico and Texas. The Mesilla Basin aquifer system is the U.S. part of the Mesilla Basin/Conejos-Médanos aquifer system and is the primary source of water supply to several communities along the United States–Mexico border in and near the Mesilla Valley. Identifying the gaining and losing reaches of the Rio Grande in the Mesilla Valley is therefore critical for managing the quality and quantity of surface and groundwater resources available to stakeholders in the Mesilla Valley and downstream. A gradient self-potential (SP) logging survey was completed in the Rio Grande across the Mesilla Valley between 26 June and 2 July 2020, to identify reaches where surface-water gains and losses were occurring by interpreting an estimate of the streaming-potential component of the electrostatic field in the river, measured during bankfull flow. The survey, completed as part of the Transboundary Aquifer Assessment Program, began at Leasburg Dam in New Mexico near the northern terminus of the Mesilla Valley and ended ~72 kilometers (km) downstream at Canutillo, Texas. Electric potential data indicated a net losing condition for ~32 km between the Leasburg Dam and Mesilla Diversion Dam in New Mexico, with one ~200-m long reach showing an isolated saline-groundwater gaining condition. Downstream from the Mesilla Diversion Dam, electric-potential data indicated a neutral-to-mild gaining condition for 12 km that transitioned to a mild-to-moderate gaining condition between 12 and ~22 km downstream from the dam, before transitioning back to a losing condition along the remaining 18 km of the survey reach. The interpreted gaining and losing reaches are substantiated by potentiometric surface mapping completed in hydrostratigraphic units of the Mesilla Basin aquifer system between 2010 and 2011, and corroborated by surface-water temperature and conductivity logging and relative median streamflow gains and losses, quantified from streamflow measurements made annually at 16 seepage-measurement stations along the survey reach between 1988 and 1998 and between 2004 and 2013. The gaining and losing reaches of the Rio Grande in the Mesilla Valley, interpreted from electric potential data, compare well with relative median streamflow gains and losses along the 72-km long survey reach.

Developing Pseudo Continuous Pedotransfer Functions for International Soils Measured with the Evaporation Method and the HYPROP System: II. The Soil Hydraulic Conductivity Curve

Direct measurement of unsaturated hydraulic parameters is costly and time-consuming. Pedotransfer functions (PTFs) are typically developed to estimate soil hydraulic properties from readily available soil attributes. For the first time, in this study, we developed PTFs to estimate the soil hydraulic conductivity (log(K)) directly from measured data. We adopted the pseudo continuous neural network PTF (PCNN-PTF) approach and assessed its accuracy and reliability using two independent data sets with hydraulic conductivity measured via the evaporation method. The primary data set contained 150 international soils (6963 measured data pairs), and the second dataset consisted of 79 repacked Turkish soil samples (1340 measured data pairs). Four models with different combinations of the input attributes, including soil texture (sand, silt, clay), bulk density (BD), and organic matter content (SOM), were developed. The best performing international (root mean square error, RMSE = 0.520) and local (RMSE = 0.317) PTFs only had soil texture information as inputs when developed and tested using the same data set to estimate log(K). However, adding BD and SOM as input parameters increased the reliability of the international PCNN-PTFs when the Turkish data set was used as the test data set. We observed an overall improvement in the performance of PTFs with the increasing number of data points per soil textural class. The PCNN-PTFs consistently performed high across tension ranges when developed and tested using the international data set. Incorporating the Turkish data set into PTF development substantially improved the accuracy of the PTFs (on average close to 60% reduction in RMSE). Consequently, we recommend integrating local HYPROPTM (Hydraulic Property Analyzer, Meter Group Inc., USA) data sets into the international data set used in this study and retraining the PCNN-PTFs to enhance their performance for that specific region.

Numerically enhanced conceptual modelling (NECoM) applied to the Malta Mean Sea Level Aquifer

Conventional hydrogeological practice is to formulate a conceptual model, which is often the basis of a numerical model. The numerical model is then used to test groundwater management strategies. A workflow is proposed, employing the numerically enhanced conceptual model (NECoM) of the Mean Sea Level Aquifer (MSLA) on the island of Malta. The Malta MSLA is overexploited and under threat of salinization. Data (heads, chloride concentrations, electrical conductivity logs, tidal tests and qualitative analyses) were assimilated into a fast-running numerical model. Simultaneously, strategies for optimal acquisition of further data were examined through the modelling process. The model was delivered through the Energy and Water Agency, with suggestions for flexible model deployment. These workflows will, hopefully, spawn model improvements through further revision of the base concepts. The model allows the agency to make predictions, which have uncertainties that are quantified and reduced through data assimilation as new data become available. Contemplated management plans can therefore be properly assessed before implementation. The proposed NECoM approach can be generalized since it bases model usage on the premise that modelling should make maximum use of existing data by assimilating its information content, thereby highlighting the uncertainties of decision-critical predictions that remain because of data insufficiency. Thus, the presently disjointed process of modelling on the one hand, and data acquisition on the other, can be better aligned. Conceptual and numerical model development become parallel, rather than sequential, activities. Together, they enable predictions of future system behaviour for which bias is reduced and uncertainties quantified.

Evaluating the potential of carbonate sub-facies classification using NMR longitudinal over transverse relaxation time ratio

While the well log-based lithology classification has been extensively utilized in reservoir characterization, the classification of carbonate sub-facies remains challenging due to the subtle nuances in conventional well-logs. The nuclear magnetic resonance (NMR) log provides extra information of pore size and pore geometry features, improving differentiating carbonate sub-facies. Here we explore the feasibility of using the ratio between NMR longitudinal relaxation time and transverse relaxation time as a potential lithology indicator to determine carbonate sub-facies. We analyzed a series of logging data and corresponding core samples of Arbuckle Group carbonate containing mudstone, packstone, grainstone, incipient breccia, and breccia in northern Kansas for the characteristics of longitudinal relaxation times, transverse relaxation times, and longitudinal over transverse relaxation time ratios. The results show that mudstone, packstone, and grainstone exhibit high, intermediate, and low longitudinal over transverse relaxation time ratios, respectively, while incipient breccia and breccia have a wide range of longitudinal over transverse relaxation time ratios. Furthermore, we evaluated the potential of using longitudinal over transverse relaxation time ratios to classify carbonate sub-facies using multivariate analysis. By adding longitudinal over transverse relaxation time ratios to neutron porosity, total gamma-ray, and conductivity logs as inputs of automated facies classification, the prediction error decreased, especially for incipient breccia. On the contrary, when photoelectric log and computed gamma-ray are also available, adding longitudinal over transverse relaxation time ratios does not improve the accuracy of sub-facies classification. Our results suggest that longitudinal over transverse relaxation time ratio is an independent lithology indicator. However, it cannot replace other logs like gamma-ray and photoelectric logs in classifying carbonate sub-facies. Our study provided valuable evidence and credible elucidation of the importance and physicochemical mechanism of longitudinal over transverse relaxation time ratios, which is essential for deciphering NMR logging data in carbonate reservoirs. Cited as : Zhang, F., Zhang, C. Evaluating the potential of carbonate sub-facies classification using NMR longitudinal over transverse relaxation time ratio. Advances in Geo-Energy Research, 2021, 5(1): 87-103, doi: 10.46690/ager.2021.01.09

Synthesis, physical and photo-electrochemical characterizations of a new hybrid host-guest complex [Cu12(C2N3H2)8Cl][(PW12O40)

Through careful choice of reduction conductions, a new hybrid host-guest compound [Cu12(C2N3H2)8Cl][(PW12O40)] was synthesized hydrothermally in the presence of 1, 2, 4 triazole as structure-directing agent. The material has been characterized by single-crystal X-ray diffraction, chemical analysis, FT-IR spectroscopy, thermal analysis and UV–Vis diffuse reflectance. The compound based on a two-dimensional (2D) supramolecular porous coordination polymer [Cu12 (C2N3H2)8Cl]3+ can accommodate in its cavities the Keggin polyoxotungstate anions, with host-guest interactions crystallizing in the monoclinic system (Space Group: C2/m). The metal organic species and Keggin anions are connected via hydrogen bonds and Cu…O short contacts giving rise to a three-dimensional architecture. The optical study shows a direct transition (1.60 eV) assigned to the O2−: 2p → Cu+: 4 s transition. The transport properties revealed a semiconductor comportment; the thermal variation of log (conductivity) versus 1000/T was fitted by a least square method to a straight line whose slope gave an activation energy of 54 meV. The chrono-amperometry and photo-electrochemistry, carried out in Na2SO4 (0.5 M) electrolyte, indicate n-type conduction with a flat band potential of +0.10 VSCE, making [Cu12(C2N3H2)8Cl][(PW12O40)] a promising solar material.

Direct push, in situ video imaging of buried prehistoric landscapes in soft soils: First results in the polders, coversands, and loess belt of Belgium

Since the introduction of direct push sensing, and more specifically, cone penetration testing, in prehistoric paleolandscape mapping, applications have been limited to mapping relatively thick and lithologically contrasting sedimentary units in fluvial and estuarine floodplains. However, this study investigates techniques to map thinner and less contrasting sediments, and soil horizons in soft soils outside these floodplains as well. Therefore, cone penetration testing and electrical conductivity logging are assessed in combination with the first paleolandscape mapping application of direct push, in situ video imaging in test cases situated in the polders, coversands, and loess belt of Belgium. The results reveal that the discrimination potential of archaeologically relevant, litho- and pedostratigraphic units through direct push sensing is increased in the respective regions. Despite the necessity of hardware updates and further developments in video data processing, a combination of cone penetration testing, electrical conductivity logging, and in situ video imaging is readily applicable to extensive mapping of deeply buried prehistoric paleolandscapes.

Relationship Between Aquifer Pumping Response and Quality of Water Extracted from Wells in an Active Hydrothermal System: The Case of the Island of Ischia (Southern Italy)

The thermal waters of the Island of Ischia, an active volcano located in Southern Italy, are widely used for supplying numerous spas. Groundwater withdrawals occur mainly through wells in the coastal strip. This study explores the impact of withdrawals on the quality of the waters used in thermal facilities, which is required to be constant in terms of composition and temperature by law. For this purpose, specific investigations were conducted including 155 pumping tests, 124 water temperature measurements during pumping tests, 31 temperature and electrical conductivity logs and periodic chemical analysis of the waters of 21 selected wells. By comparing the response to pumping of the aquifer and the quality of the water extracted from the wells, it turned out that the quality of groundwater supplying spas depends not only on natural phenomena (meteoric recharge, seawater intrusion, and rising of deep hydrothermal fluids) but also relies on the island sector where groundwater is pumped and on the pumping method. The distance of the wells from the coast, the type of aquifer formation intersected by the wells, and the field of groundwater temperature of the hydrothermal system strongly affect the aquifer pumping response, determining the quality of water extracted from wells and its variation over time. In Ischia, techniques and regimes of groundwater withdrawals should adapt to the local aquifer pumping response, more than in another hydrogeological context. The concomitant analysis of drawdown, water temperature, and salinity during pumping turned out to be a valuable tool to define the sustainable yield of the single well.

Estimation of Geothermal Gradient, Geothermal Heat Flux and Thermal Conductivity of Rocks in Western Niger Delta Using Well Log Data

This study presents the result of the estimation of heat flow from six (6) wells (Well X:001 to 006) in South-Western Niger Delta using values of Geothermal gradient (GG), Geothermal heat flux (Q) and thermal conductivity (K) computed from Sonic and continuous temperature log data for each well. Geothermal gradient was computed from continuous temperature logs using the simple gradient method while geothermal heat flux and thermal conductivity of the rocks in the wells were computed from the sonic log data, using the Relative Heat Flow Model and Fourier One-dimensional Heat Flow Law respectively. The results were analysed and interpreted to investigate the thermal structure and pattern of heat flow distribution of the basin. Results showed that geothermal gradient ranges from 1.45 0 C/100m to a value of 1.61 0 C/100m, with a simple average of 1.55 0 C/100m. Geothermal gradient contour map computed from this result, showed a low thermal gradient at the northern part of the study area where we have Well X-006 and increases outwards in all direction as we move further offshore. These differences reflect changes in thermal conductivity of rocks, ground water movement and endothermic reaction during diagenesis, since geothermal gradient is influenced by lithology or differential rate of sedimentation. Therefore, it was inferred that sediments with a relatively high geothermal gradient (1.55 to 1.61 0 C/100m) will mature earlier (low oil window) than those with low thermal gradient values. By implication, a high geothermal gradient enhances the early formation of oil at relatively shallow burial depths, but causes the depth range of the oil window to be narrow, while low geothermal gradient causes the first formation of oil to begin at fairly deep subsurface levels, but makes the oil window broad. Geothermal heat flux estimated from subsurface temperature and one-way sound travel time, shows heat flux varying between 33.16 mWm -2 to 72.73 mWm -2 with a simple average of 48.43 mWm -2 . Low heat flux was observed at the central part of the study area which increases towards the western and eastern parts of the area with Well X-005 characterized by a higher geothermal heat flux. Therefore, it was inferred that the western and eastern parts of the study area with higher heat flux values may be characterized as zones with maximum sediment thickness and are characterized as having depressions (gravity low) on the geoid which is characteristics of a basin, while the central part of the study area with low heat flux values correspond with zones of minimum sediment thickness. Also, thermal conductivity of rocks in the study area computed directly from heat flux and geothermal gradient results, ranges from 2.28W/m 0 C to 4.76 W/m 0 C with an average of 3.19 W/m 0 C. Thermal conductivity contour map computed from this result, showed low thermal conductivity values observed at the central part of the study area, and increases outwards towards the west and eastern parts. This pattern of thermal conductivity variation suggests probably there exists heavy crude oil at the central part of the study area and lighter crude oil as we move outward in all direction. It was also observed that within each well, thermal conductivity increased with depth and decreased with porosity which may be caused by difference in lithology and fluid content, due to the fact that all pore fillers (i:e gases and liquids) are poor conductors. The estimated values of geothermal gradient, heat flux and thermal conductivity obtained in this study are similar to the results obtained from previous studies in the region and with other passive continental margins of the world. Keywords: Heat flow, Geothermal Gradient, Geothermal Heat Flux, Thermal Conductivity, Continuous Temperature and Sonic log. DOI: 10.7176/JETP/10-2-04 Publication date: April 30 th 2020

Blocking borehole conductivity logs at the resolution of above-ground electromagnetic systems

Borehole conductivity logs provide an in situ measurement of the electrical conductivity of the subsurface. Despite the measurements being a proxy for the true earth structure, they are often used as ground truth when inferring subsurface electrical conductivity boundaries between lithologies. Borehole conductivity measurements are therefore commonly used to plan and benchmark electromagnetic (EM) surveys and to establish the credibility of a given inversion technique. A consequence of the diffusion physics of EM prospecting is that not all subsurface features present in a conductivity log can be resolved by an EM system, nor can they be recovered by a subsequent inversion. Quantification of the ability of an EM system to determine layer boundaries in the subsurface is therefore an issue meriting investigation. We have developed a reversible-jump Markov chain Monte Carlo (RJMCMC) method to segment borehole conductivity logs at the scale recoverable by a given EM system as the foundation for an objective comparison between the inversion results and conductivity logs. A common consequence of RJMCMC inversions for EM problems is that few layers are required to fit the data. Similarly, we find that a borehole log blocked at the scale sensed by an EM system consists of a limited number of segments. Segmentation of borehole conductivity logs is determined by the physics of EM prospecting and by factors such as base frequency, number of gates, system geometry, and noise levels. For a survey line intersecting a borehole near Carnarvon, Western Australia, we see that different inversion schemes result in images of the subsurface that are consistent with a borehole conductivity log segmented according to the mechanics of the EM system and accounting for the physics of EM prospecting.

Hydrocarbon saturation in shale oil reservoirs by inversion of dielectric dispersion logs

Hydrocarbon saturation is an important petrophysical parameter in reservoir evaluation and reserve calculation. Dielectric dispersion logs have been widely used to estimate the hydrocarbon saturation, especially in high salinity shale formations. However, there is still room to improve the accuracy of interpretation of dielectric dispersion logs. In this paper, we used two interpretation models combined four dielectric permittivity and four conductivity logs measured by Array Dielectric Tool (ADT) at four frequencies to predict the hydrocarbon saturation in shale oil reservoirs, Triassic Yanchang Formation, Ordos Basin, China. The logs measured at the highest frequency are interpreted by the Complex Refractive Index (CRIM) model. And the other three frequencies measured logs are processed by the shaly sandstone (SHSD) model. Based on the two models, simulated annealing algorithm is selected to calculate water saturation and rock textual parameter, the dispersive phase fraction, and water salinity. Besides, accurate porosity, dielectric permittivity of rock matrix, and temperature are input information to the proposed method. The proposed method is applied to shale oil reservoirs of Triassic Yanchang Formation in two wells. The effectiveness and reliability of proposed model is verified by synthetic log responses. The mean relative error between synthetic and field logs is small. The predicted hydrocarbon saturation is consistent with core data, and its variation is consistent with characteristics of NMR T2 distributions, verifying the accuracy and reliability of proposed method and inversion results. Our estimated hydrocarbon saturation of the two wells is about 30%, showing a good oil generation potential of the studied shale oil reservoirs.

Probabilistic Forecast of Single‐Phase Flow in Porous Media With Uncertain Properties

AbstractUncertainty about geologic makeup and properties of the subsurface renders inadequate a unique quantitative prediction of flow and transport. Instead, multiple alternative scenarios have to be explored within the probabilistic framework, typically by means of Monte Carlo simulations (MCS). These can be computationally expensive, and often prohibitively so, especially when the goal is to compute the tails of a distribution, that is, probabilities of rare events, which are necessary for risk assessment and decision making under uncertainty. We deploy the method of distributions to derive a deterministic equation for the cumulative distribution function (CDF) of hydraulic head in an aquifer with uncertain (random) hydraulic conductivity. The CDF equation relies on a self‐consistent closure approximation, which ensures that the resulting CDF of hydraulic head has the same mean and variance as those computed with statistical moment equations. We conduct a series of numerical experiments dealing with steady‐state two‐dimensional flow driven by either a natural hydraulic head gradient or a pumping well. These experiments reveal that the CDF method remains accurate and robust for highly heterogeneous formations with the variance of log conductivity as large as five. For the same accuracy, it is also up to four orders of magnitude faster than MCS in computing hydraulic head with a required degree of confidence (probability).

Electrical Properties of AgSb(SxSe1-x)2 Thin Films

Alloys from AgSb(SxSe1-x)2 with different compositions were prepared using quenching from the melt. This was done by put the appropriate amount of Ag, Sb, S and Se in an evaluated quartz ampoule, sealed and left at oven in temperature 1273 for 5 hours. Thin films with different composition were deposited by pulsed deposition technique PLD onto glass substrates at ambient temperature. This paper concerned on the investigate effect of composition on structural morphology, and electrical properties. The structure and morphology of the prepoared thin films were checked using X–ray diffraction and atomic force microscope. The D.C conductivity of the AgSb(SxSe1-x)2 thin films with various x content was measured in the temperature range (298-473)K. It was found the electrical conductivity decreased two order of magnitude with the increase of x content. Two activations energies Ea1, and Ea2 estimated from the plot of log conductivity with reciprocal temperature for AgSb(SxSe1-x)2 with different compositions which increased with increasing of x content. The data obtained from Hall effect which are concentration of charge carriers decreased while mobility increased with the increase of x content.

Generation of synthetic dielectric dispersion logs in organic-rich shale formations using neural-network models

Dielectric dispersion (DD) logs acquired in subsurface geologic formations generally are composed of conductivity ([Formula: see text]) and relative permittivity ([Formula: see text]) measurements at four discrete frequencies in the range of 10 MHz to 1 GHz. Acquisition of DD logs in subsurface formations is operationally challenging, and it requires a hard-to-deploy infrastructure. We developed three supervised neural-network-based predictive methods to process conventional, easy-to-acquire subsurface logs for generating the eight DD logs acquired at four frequencies. These predictive methods will improve reservoir characterization in the absence of a DD logging tool. The predictive methods are tested in three wells intersecting organic-rich shale formations of the Permian Basin and the Bakken Shale. The first method predicts the eight dispersion logs simultaneously using a single artificial neural network (ANN) model, whereas the second method simultaneously predicts the four conductivity dispersion logs using one ANN model, followed by simultaneous prediction of four permittivity dispersion logs using a second ANN model. The third method sequentially predicts the eight dispersion logs, one at a time using eight sequential ANN models, based on a predetermined ranking of the prediction accuracy for each of the eight DD logs when simultaneously generated. Considering that the conventional and DD logs are recorded more than 10,000 ft deep in the subsurface using logging tools that are run at different times in rugose boreholes for sensing the near-wellbore geologic formation, the data used in this predictive work is prone to noise and biases that tend to adversely affect the prediction performances of the proposed methods. In terms of normalized root-mean square error (Nrms error), the prediction performances of the second predictive method are 8.5% worse and 6.2% better for the conductivity and permittivity dispersion logs, respectively, as compared with those of the first predictive method. The third method has best prediction performance for permittivity dispersion logs, which is 0.089 in terms of the Nrms error.