Core Sample Measurements Research Articles

Carbonate Rock Physics Model Using Different Approaches to Estimate Rock Frame Stiffness

Deepwater carbonate reservoirs in the Brazilian pre-salt have emerged as significant hydrocarbon plays in the region and globally. Seismic monitoring of these reservoirs is crucial to provide information for well placement assessments, to reduce uncertainty in reservoir models, and to enhance model-based decision making. To integrate seismic data quantitatively, a petroelastic model (PEM) is required to estimate elastic properties. The modeling of the rock frame stiffness is an essential part in the study of PEM. However, this becomes more complex for carbonate rocks given their diverse pore-types. One way for estimating stiffness is to model each distinct pore-type and include them into the overall rock frame (different inclusion models). In this research, an alternative approach is explored to estimate the rock frame stiffness. A proxy model is employed, and its coefficients are subsequently calibrated with well-log information. Two PEMs were developed using different approaches for rock frame stiffness modeling. The first was inspired by inclusion models and incorporated two pore types (compliant and stiff pores) for the modeling process. The second considered a mathematical regression model as a proxy to relate reservoir porosity to the rock frame stiffness. These two PEMs were tested on the Brazilian pre-salt carbonate rocks of the Barra Velha (BVE) formation using well-log data from three wells and core sample measurements for one well. The accuracy of the PEMs’ performances was assessed by measures (such as, mean absolute error and root mean square error) and visual comparisons of their predictions. The results showed that both PEMs predicted velocities (compressional and shear) within an acceptable match with the actual well-log data. Similarly, when tested on the core samples, the PEMs produced comparable results, which indicates the validity of the proxy, not only at the well-log scale but at the core scale. The visual comparison and the accuracy analyses of the results for all three wells confirmed that the two PEMs had comparable predictions. This is significant given that the proxy simplifies the modeling process and facilitates the representation of various pore-types in the prediction of elastic properties in carbonate rocks. Overall, the proxy for the rock frame stiffness modeling is a computationally less expensive model compared to the inclusion models which involve modeling of various pore-types. It also offers a straightforward model which enables the quantitative integration of seismic data in a multidisciplinary team of geosciences and petroleum engineers (for instance, early engagement of petroleum engineers in 3D/4D seismic history matching).

New evidence from the Paleoproterozoic Gunflint Iron Formation for microbially-driven, early diagenetic precipitation of siderite

Petrographic, geochemical, C-, O-, and clumped isotope measurements of drill core samples from the Paleoproterozoic (1.88 Ga) Gunflint Iron Formation containing siderite, ankerite, Fe-silicate clays (dominantly greenalite) and silica, reveal variable but light carbonate δ13C values (-21.3 to -7.87‰, VPDB), with heavy and less variable carbonate δ18O values (20.6 to 24.9‰, VSMOW). These measurements are consistent with a model in which siderite is formed during early diagenesis as a by-product of the metabolism of dissimilatory iron reducing (DIR) microbes that consume Fe(III)-oxide and organic carbon delivered from the water column to the sediment-water interface. This model indicates that the oxygen isotope compositions of reactant Fe-oxide, organic matter and dissolved inorganic carbon were set in equilibrium with seawater at T = 5–35 °C and δ18O = -1.0 to -6.5‰, prior to being metabolized to form siderite. Clumped isotope measurements on Fe-bearing carbonates yield temperatures (T(Δ47)) between 40 °C-132 °C, which constrain δ18Ofluid to values between -6.22 to 7.32‰. These measurements record the onset temperature of DIR followed by low water-to-rock ratio diagenetic recrystallization at elevated temperature. Combined petrographic, chemical, and isotopic measurements reveal that the major phases delivered to the shallow seafloor were a disequilibrium assemblage of Fe-oxide, greenalite, silica, and organic matter that underwent microbially mediated modification to form an assemblage of siderite, greenalite, silica, and later diagenetic ankerite. We contend that observed differences between carbonate derived from Gunflint core and outcrop may be reconciled by removal of siderite during exposure and weathering, leaving outcrop enriched in late diagenetic ankerite.

Level of thermal maturity estimation in unconventional reservoirs using interval inversion and simulating annealing method

AbstractThis study presents a novel geophysical approach for estimating the level of thermal maturity (LOM) in unconventional hydrocarbon reservoirs using well log data. LOM is a crucial parameter for assessing the hydrocarbon generation potential of source rocks, but it traditionally relies on laboratory measurements of core samples, which can be time-consuming and costly. The proposed method combines two techniques: interval inversion for estimating total organic carbon (TOC) content from well logs and simulated annealing (SA) optimization for deriving LOM from the estimated TOC. The interval inversion method enables accurate TOC estimation by jointly interpreting multiple well logs over depth intervals, overcoming limitations of conventional point-by-point inversion. Using the estimated TOC, the SA algorithm optimizes an energy function related to Passey's empirical TOC-LOM relationship, iteratively finding the optimal LOM value that best fits the well log data. This approach provides a continuous in situ LOM profile along the borehole without requiring core measurements. The effectiveness of the method is demonstrated through case studies on datasets from the North Sea (Norway), the Pannonian Basin (Hungary), and the Kingak Formation (Alaska). The LOM estimates show good agreement with reported maturity levels and allow reliable reservoir characterization. Statistical analysis confirms the robustness and accuracy of the results. By reducing dependence on core data, this integrated inversion-optimization workflow streamlines the reservoir prospecting phase, enhancing operational efficiency. The method holds promising applications across diverse geological settings for cost-effective evaluation of unconventional hydrocarbon plays.

Hyperparameter inversion of well logs for the simultaneous estimation of volumetric and zone parameters

We develop a new alternative for the joint inversion of well logs to predict the volumetric and zone parameters in hydrocarbon reservoirs. Porosity, water saturation, shale content, kerogen, and matrix volumes are simultaneously estimated with the tool response function constants with a hyperparameter estimation assisted inversion of the total and spectral natural gamma-ray intensity, neutron porosity, and resistivity logs. We treat the zone parameters, i.e., the physical properties of rock matrix constituents, shale, kerogen, and porefluids, as well as some textural parameters, as hyperparameters and estimate them in a metaheuristic inversion procedure for the entire processing interval. The selection of inversion unknowns is based on parameter sensitivity tests, which indicate that the automated estimation of several zone parameters is favorable, and their possible range can also be specified in advance. In the outer loop of the inversion procedure, we use a real-coded genetic algorithm for the prediction of zone parameters, and we update the volumetric parameters in the inner loop in addition to the fixed values of the zone parameters estimated in the previous step. We apply a linearized inversion process in the inner loop, which allows for the quick prediction of volumetric parameters along with their estimation errors from point to point along a borehole. The derived parameters, such as hydrocarbon saturation and total organic content, indicate good agreement with core laboratory data. The significance of the inversion method is that the zone parameters are extracted directly from the wireline logs, which improves the solution of the forward problem and reduces the cost of core sampling and laboratory measurements. In a field study, we demonstrate the feasibility of the inversion method using real well logs collected from a Miocene tight gas formation situated in the Derecske Trough, Pannonian Basin, East Hungary.

Trap Prevention in Machine Learning in Prediction of Petrophysical Parameters: A Case Study in The Field X

Petrophysical parameters such as porosity and water saturation are vital in the petroleum industry for reservoir characterization. These aspects are typically assessed through laboratorium measurements of core samples or intricate petrophysical calculations. Machine Learning (ML) offers a cost-effective and efficient approach as an alternative to conventional methods of predicting those parameters. However, developing ML models can be prone to the invisible traps such as overfitting, underfitting, feature selection, and feature importance. This study is intended to share how to identify the traps and its mitigation by establishing a synergistic workflow between ML and petrophysical theory. A model was developed based on data from several wells in X field, where they are randomized and split into test and train data. Well-log normalization preceded data splitting, and input features were normalized with outlier removal. A feature selection function was then employed to choose a specific amount of log data. Finally, the model selection function identified the highest-scoring model. Without a proper workflow, overfitting, irrelevant feature selection, and imprecise ranking issues emerged. However, with the proper workflow, these invisible traps were mitigated, even with a relatively small dataset. The final model could accurately predict porosity and water saturation

Classification of shale lithofacies with minimal data: Application to the early Permian shales in the Ordos Basin, China

Shale lithofacies classification is one of the key components of shale reservoir evaluation. Typically, a significant amount of laboratory X-ray diffraction (XRD) data acquired on many shale samples collected in a large number of boreholes is required to constrain the mineral composition that enables classifying shale lithofacies at the basin scale. This procedure is costly and time consuming. Here, we propose a supervised machine learning method to predict the mineral composition of shale samples, including the clay and silicate content. The main advantage of our approach is that it only uses conventional logging data and a small number of XRD measurements of core samples, combined with XGBoost algorithm, to predict shale lithofacies, which can reduce the cost and improve the efficiency of reservoir evaluation. We apply our method on the early Permian shales in the Ordos Basin, China, because these shale rocks have a high potential of gas production. However, these formations are also highly heterogeneous, making them challenging to explore and exploit. Therefore, it is critical to perform detailed lithofacies classification analysis at the basin scale before gas production. Our result show that the gamma ray, neutron porosity, and density measurements are the critical logging data that control the model predictions. These parameters are known to be sensitive to clay content, thereby supporting the robustness of model predictions. Applying the model to different wells to classify shale lithofacies, results that these shale formations are dominated by three types of lithofacies. We characterize the different shale lithofacies by microscopy images and gas adsorption measurements, and demonstrate that our results are consistent with previous studies, verifying the accuracy and applicability of our machine learning method to classify shale lithofacies.

Numerical Simulations of Carbon Dioxide Storage Efficiency in Heterogeneous Reservoir Models

The U.S. Department of Energy’s National Energy Technology Laboratory (DOE-NETL) has been developing methods and tools (the online Carbon Dioxide Storage prospeCtive Resource Estimation Excel aNalysis (CO2-SCREEN) tool) to estimate carbon dioxide (CO2) storage potential in subsurface reservoirs. The CO2 storage efficiency terms are input in the tool to calculate storage potential in targeted reservoirs. In this effort, two CO2 storage efficiency terms were evaluated: volumetric displacement ( E V ) and microscopic displacement ( E d ). The first term deals with efficiency of CO2 propagation into an accessible reservoir volume, while the second term evaluates effectiveness of native fluid displacement with CO2. The interpreted well logs and core sample measurements were applied to create the heterogeneous reservoir models including geostatistical realizations of porosity and intrinsic permeability fields. Supercritical CO2 was injected over the course of 30 years into brine-saturated reservoir models for clastics, limestone, and dolomite lithologies and deltaic fluvial, aeolian, shallow marine, and reef depositional environments by means of varying reservoir parameters and injection scenarios. The reservoir models providing vertically heterogeneous petrophysical properties and designated as “layered reservoir models” (with homogeneous parameters along each layer of the model) were not determined to be a transition between the homogeneous and heterogeneous models in respect to storage efficiency. Another finding shows that high-efficiency factors do not necessarily mean increased CO2 storage; they rather indicate that the available volume and pore space are more fully utilized. The CO2 storage efficiency factors were evaluated dynamically at the select time points using P 10 ‐ P 50 ‐ P 90 percentiles. The results of this study show that the P 10 ‐ P 90 distribution for volumetric efficiency is wider when compared to the microscopic efficiency. It was found that where dominant buoyancy forces drive the plume to the top of a target formation, the volumetric efficiency is low. Tighter sandstone and carbonate formations show prevalence of capillary forces and better utilization of reservoir volume.

Quality assessment and quality control of deep soil mixing columns based on a cement-content controlled method

This paper presents a cement-content controlled method for quality assessment and quality control of the deep soil mixing (DSM) columns in slope reinforcement. The ethylene diamine tetraacetic acid (EDTA) titration method was modified and used for the cement content measurement of core samples, and the effects of curing conditions and curing period on the titration results were investigated. 35 DSM columns with different construction parameters were installed in the test section, and cement content and unconfined compression tests of field core samples were conducted. The relationship between the unconfined compressive strength (UCS) and cement content of DSM columns was formulated, and the quality of DSM columns with different construction parameters was assessed. The test results suggested that the failure strength of the field cores was approximately 15–55% lower than that of laboratory samples with the same cement content. In single columns, the coefficient of variation (CV) of cement content had a negative correlation with the average failure strength and a positive correlation with the coefficient of variation of failure strength. Bidirectional mixing method, lower penetration and withdrawal velocity, more mixing blades and larger number of mixings could improve the uniformity of the DSM columns.

The development of methods and instruments for thermal conductivity measurement of standard core samples for petrophysical studies

The problem of obtaining qualitative data on the thermal conductivity of standard rock samples for petrophysical studies is considered. It is shown that the existing instruments for thermal conductivity measurement do not allow one to obtain reliable and accurate values of the thermal conductivity of small-sized rock samples. A laboratory installation for thermal conductivity measurement of standard rock samples with a diameter not less than 30 mm has been created. The installation was assembled and tested on small samples. Possible problems in the development, design and exploitation of the laboratory installation were analyzed. A software that allows automated collection and processing of the data has been developed. The key factors, negatively affecting the accuracy and reliability of thermal conductivity measurement results, are identified and excluded. There were unshielded thermocouples, potential changes between the hot and cold junctions (due to uneven melting of the water-ice mixture in the Dewar vessel, where the cold junction is immersed), incorrectly selected dimensions and shape of the object of study and the nonequilibrium ratio of the heat input and dissipation. The installation was tested on samples of pure tin standard and brass LS59 with known thermal conductivity. The thermal conductivity of a small-sized rock sample was measured with an error within 5.6 %.

In-situ assessment of soil shrinkage and swelling behavior and hydro-thermal regimes with a thermo-time domain reflectometry technique

The shrinkage and swelling behaviors of clayey soils could lead to cracks and erosions inducing severe damages to agricultural lands and engineering projects. Thus, improving the understanding of shrink-swell characteristics is crucial to nonrigid soils. However, it remains difficult for in-situ monitoring of soil shrink-swell processes continuously and nondestructively. The objective of this study was to present a thermo-time domain reflectometry (thermo-TDR) technique for determination of soil shrinkage and swelling dynamics and hydro-thermal regimes in-situ during wet-dry cycles. A field experiment on two clayey soils (a paddy soil and an alluvial soil) was conducted to evaluate the performance of the thermo-TDR method for in-situ determination of soil volume changes and associated hydraulic and thermal properties during wet-dry cycles. The results showed that both soils experienced considerable shrinking and swelling processes with maximum vertical deformations of 2.4 and 1.8 cm for the paddy soil and alluvial soil, respectively, and with maximum horizontal deformations of 370 and 280 cm2 for the paddy soil and alluvial soil, respectively, during a 36-day period. The thermo-TDR method provided volume change values (shown as the bulk density) agreed well with independent core-sampling measurements with an average RMSE of 0.15 Mg m−3 and a R2 of 0.46. A better agreement was observed between thermo-TDR measured bulk densities and values from the ruler-image processing method with an average RMSE of 0.07 Mg m−3 and a R2 of 0.77. Besides, the thermo-TDR method gave consistent in-situ soil shrinkage curve and water retention surface measurements by combining with soil matric potential sensors. Unlike rigid soils, the paddy and alluvial soils showed complicated hydro-thermal regimes in response to the shrink-swell processes. We conclude that the thermo-TDR technique is a reliable tool for continuous in-situ determination of soil shrink-swell processes. Future studies should focus on development of comprehensive soil heat and water transport models accounting for both moisture content and volume changes.

Sensitivity and Uncertainty Analysis for Natural Gas Hydrate Production Tests in Alaska

The Japan Research and Development Consortium for Pore Filling Hydrate in Sand (MH21-S), the U.S. Department of Energy National Energy Technology Laboratory (DOE NETL), and the U.S. Geological Survey (USGS) are planning a long-term production test from gas hydrate (methane hydrate) bearing reservoirs in the Prudhoe Bay Unit in northern Alaska. Prediction of gas and water production using 2D reservoir simulation models can be very useful for decision-making for long-term production testing. However, the input parameters applied to the simulation model, which are essentially based on the most likely values obtained from the well-log interpretation and core sample measurements of the Hydrate-01 stratigraphic test well (STW), have some degrees of uncertainty. In this study, to evaluate the impact of uncertainties in the input model on the prediction results of gas and water production as well as to analyze how each input parameter contributes to the uncertainties of prediction results, we conducted uncertainty analysis and parameter sensitivity analysis based on two different methods (the regression-based method and the Sobol’ method). The sensitivity analyses reveal that the parameters regarding relative permeability (exponential of the gas relative permeability (Ng) and residual gas saturation (Sgcr)) and the intrinsic/effective permeability of the lower B1 sand significantly contribute to the uncertainties of the gas and water production predictions. In addition, the uncertainty analyses reveal that the P50 value of cumulative gas production can result in less than the reference case with the most likely values for the input parameters due to the uncertainty of Ng. These results indicate that reducing the uncertainties of gas relative permeability and residual gas saturation is essential for more reliable numerical simulations both for prediction of test well performance and subsequent history matching of field test results.

Abnormally low heat flow in Southeast China resulted from remnant slab subducted beneath the east Asian lithosphere

AbstractSubducted remnant slabs play an important role in the geodynamics and evolution of the Earth, but their behaviour in the mantle is not well understood. Terrestrial heat flow and thermal lithosphere structure provide crucial constraints on lithospheric dynamics. Based on whole‐well steady‐state temperature logs and conductivity measurements of core samples from a scientific borehole, we obtained a new high‐quality terrestrial heat flow values for East Asia. The heat flow was calculated at 60.6 ± 16.0 mW/m2 with a high crust/mantle heat flow ratio of 1.41, suggesting a hot‐crust‐cold‐mantle lithospheric structure. The thermal lithospheric thickness of eastern Fujian is estimated to be 152–166 km, indicating a thick and cold lithosphere. We demonstrate that the cooling of the lithosphere is caused by a remnant palaeo‐slab of the Palaeo‐Pacific plate subducted beneath SE China. The remnant slab blocked heat convection into the bottom of the lithosphere of the Eurasian Plate.

Synthesis of a novel cationic hydrophobic shale inhibitor with preferable wellbore stability

To solve the problems of wellbore instability and collapse caused by clay hydration during the horizontal drilling process of shale gas, a novel cationic hydrophobic shale inhibitor ADD was synthesized by emulsion polymerization using acrylamide (AM), dioctyl maleate (DOM), dimethyl diallyl ammonium chloride (DMDAAC), and KH570-SiO2. Fourier transform infrared spectroscopy (FTIR) and Thermo Gravimetric Analysis (TGA) were used to characterize the functional groups and thermostability of synthesized material. The inhibition performance of shale inhibitor ADD was evaluated by the rolling recovery rate, linear expansion rate, and core immersion test. After being treated with 1% ADD for 16 h, the linear expansion rate of the core sample was 18%, the debris rolling recovery rate was 96.3%. The inhibition performance was better than that of polyamine inhibitor YZ and KCl. The Zeta potentials and contact angles measurement of core samples before and after treatment were measured, it was found that the Zeta potentials of core samples decreased significantly with the increasing concentrations of ADD. The possible explanation could be that ADD molecules with the positive charge can neutralize with the negative charge on the clay surface, reducing the repulsion force of the double electric layer of the clay. And the ADD molecules can form a hydrophobic adsorption layer with high roughness and low surface energy on the rock surface, which can reverse the wettability of shale from liquid-wetting to strong hydrophobicity, then preventing the intrusion of drilling fluid and formation water, achieving the inhibition of the hydration and expansion of shale.

Geothermal Gradient And Heat Flow Maps Of Offshore Malaysia: Some Updates And Observations

An update of the geothermal gradient and heat flow maps for offshore Malaysia based on oil and gas industry data is long overdue. In this article we present an update based on available data and information compiled from PETRONAS and operator archives. More than 600 new datapoints calculated from bottom-hole temperature (BHT) data from oil and gas wells were added to the compilation, along with 165 datapoints from heat flow probe measurements at the seabed in the deep-water areas off Sarawak and Sabah. The heat flow probe surveys also provided direct measurements of seabed sediment thermal conductivity. For the calculation of heat flows from the BHT-based temperature gradients, empirical relationships between sediment thermal conductivity and burial depth were derived from thermal conductivity measurements of core samples in oil/gas wells (in the Malay Basin) and from ODP and IODP drillholes (as analogues for Sarawak and Sabah basins). The results of this study further enhanced our insights into the similarities and differences between the various basins and their relationships to tectonic settings. The Malay Basin has relatively high geothermal gradients (average ~47 °C/km). Higher gradients in the basin centre are attributed to crustal thinning due to extension. The Sarawak Basin has similar above-average geothermal gradients (~45 °C/km), whereas the Baram Delta area and the Sabah Shelf have considerably lower gradients (~29 to ~34 °C/km). These differences are attributed to the underlying tectonic settings; the Sarawak Shelf, like the Malay Basin, is underlain by an extensional terrane, whereas the Sabah Basin and Baram Delta east of the West Baram Line are underlain by a former collisional margin (between Dangerous Grounds rifted terrane and Sabah). The deep-water areas off Sarawak and Sabah (North Luconia and Sabah Platform) show relatively high geothermal gradients overall, averaging 80 °C/km in North Luconia and 87 °C/km in the Sabah Platform. The higher heat flows in the deep-water areas are consistent with the region being underlain by extended continental terrane of the South China Sea margin. From the thermal conductivity models established in this study, the average heat flows are: Malay Basin (92 mW/m2), Sarawak Shelf (95 mW/m2) and Sabah Shelf (79 mW/m2). In addition, the average heat flows for the deep-water areas are as follows: Sabah deep-water fold-thrust belt (66 mW/m2), Sabah Trough (42 mW/m2), Sabah Platform (63 mW/m2) and North Luconia (60 mW/m2).

A Green's function approach to the study of effective anisotropic properties of the Barnett Shale

ABSTRACTThe purpose of this paper is to derive the Green's function of an anisotropic elastic medium and validate it with the effective stiffness tensor of Barnett Shale. We have derived the frequency‐dependent Green's function by using the spectral theorem for matrices, thus simplifying the process of computing Green's function and obtaining analytical solutions. Evaluating the inverse of the Green–Christoffel tensor is an essential part of computing the Green's function. Based on the degeneracy of the eigenvalues of the Green–Christoffel tensor, the inverse of the Green–Christoffel tensor is expressed in the form of partial fractions. Consequently, the stiffness tensors from the measurement of core samples of Barnett Shale are used to validate the Green's function. We use the generalized singular approximation method of effective medium theory to model the effective stiffness of the core samples from microstructural properties. The generalized singular approximation method also allows us to compute the theoretical stiffness tensor of the Barnett Shale for porosity variations. The behaviour of the Green's function, which reflects the behaviour of the media, is studied in the static, low‐ and high‐frequency domains and under different physical parameters. It is observed that the variations of crack‐induced porosity produce different trends in Green's function for vertically transverse isotropic and horizontally transverse isotropic media. Thus, the variation of porosity is observed to be influential in differentiating between transverse isotropic media that have inclusions. The Green's function results presented in this paper have direct applications in the construction of synthetic seismograms for unbounded transversely isotropic media.

Skin factor and potential formation damage from chemical and mechanical processes in a naturally fractured carbonate aquifer with implications to CO2 sequestration

In this study, we investigate formation damage due to acidization and water injection tests into the naturally fractured carbonate Middle Duperow Formation at Kevin Dome, Montana, potentially diminishing the chance of a future successful Geological Carbon Sequestration (GCS) project. Multiple well-test analytical models, correlated with core description and lithology data, are used to determine flow behavior and communication between the water injection interval and surrounding formations. An improved three-dimensional (3D) geologic model with dual-continuum matrix and fracture properties is constructed based on most recent seismic, core, and water sample measurements. Brine injection is simulated to verify the interpretation from the analytical models, followed by CO2 injection simulation. Geochemical calculations are performed to understand the in-situ processes that led to formation damage. Our findings suggest: (1) there are two possible scenarios that could lead to a positive total effective skin factor and permeability decline: partial penetration and formation damage; (2) analytical models indicate a positive total skin factor, contradicting results of a previous study suggesting that the well was mildly stimulated; (3) numerical simulation supports the formation damage hypothesis by matching the pressure buildup observed during the latter two brine injection tests; (4) several mechanical and chemical processes may have occurred during injection to clog the matrix/fracture system: anhydrite fines migration and/or calcite precipitation. We then make preventative suggestions for future GCS projects into carbonate reservoirs and remediation recommendations for GCS operation at the Kevin Dome.

The Rocklea Dome 3D Mineral Mapping Test Data Set

Abstract. The integration of surface and subsurface geoscience data is critical for efficient and effective mineral exploration and mining. Publicly accessible data sets to evaluate the various geoscience analytical tools and their effectiveness for characterisation of mineral assemblages and lithologies or discrimination of ore from waste are however scarce. The open-access Rocklea Dome 3D Mineral Mapping Test Data Set (Laukamp, 2020; https://doi.org/10.25919/5ed83bf55be6a) provides an opportunity for evaluating proximal and remote sensing data, validated and calibrated by independent geochemical and mineralogical analyses, for exploration of channel iron deposits (CIDs) through cover. We present hyperspectral airborne, surface, and drill core reflectance spectra collected in the visible–near-infrared and shortwave infrared wavelength ranges (VNIR–SWIR; 350 to 2500 nm), as well as whole-rock geochemistry obtained by means of X-ray fluorescence analysis and loss-on-ignition measurements of drill core samples. The integration of surface with subsurface hyperspectral data collected in the frame of previously published Rocklea Dome 3D Mineral Mapping case studies demonstrated that about 30 % of exploration drill holes were sunk into barren ground and could have been of better use, located elsewhere, if airborne hyperspectral imagery had been consulted for drill hole planning. The remote mapping of transported Tertiary detritals (i.e. potential hosts of channel iron ore resources) versus weathered in situ Archaean bedrock (i.e. barren ground) has significant implications for other areas where “cover” (i.e. regolith and/or sediments covering bedrock hosting mineral deposits) hinders mineral exploration. Hyperspectral remote sensing represents a cost-effective method for regolith landform mapping required for planning drilling programmes. In the Rocklea Dome area, vegetation unmixing methods applied to airborne hyperspectral data, integrated with subsurface data, resulted in seamless mapping of ore zones from the weathered surface to the base of the CID – a concept that can be applied to other mineral exploration and mineral deposit studies. Furthermore, the associated, independent calibration data allowed the quantification of iron oxide phases and associated mineralogy from hyperspectral data. Using the Rocklea Dome data set, novel geostatistical clustering methods were applied to the drill core data sets for ore body domaining that introduced scientific rigour to a traditionally subjective procedure, resulting in reproducible objective domains that are critical for the mining process. Beyond the previously published case studies, the Rocklea Dome 3D Mineral Mapping Test Data Set has the potential to develop new methods for advanced resource characterisation and develop new applications that aid exploration for mineral deposits through cover. The white mica and chlorite abundance maps derived from airborne hyperspectral, presented here for the first time, highlight the additional applications of remote sensing for geological mapping and could help to evaluate newly launched hyper- and multispectral spaceborne systems for geoscience and mineral exploration.

Investigation the relationship between nuclear magnetic resonance and acoustic velocity for improving the evaluation of tight gas reservoirs

ABSTRACT Nuclear magnetic resonance (NMR) and acoustic logging play different roles in formation evaluation. Establishing a relationship model between the two is helpful for joint inversion or evaluation of the physical properties of the formation content. The rock pore structure is used as a link to analyze the theoretical relationship between the transverse relaxation time (T2) spectrum of NMR and acoustic velocity. In this paper, the relationship between NMR T2 and shear-wave velocity is determined by using NMR-acoustic velocity joint experiment. Considering that both NMR T2 spectrum and Shear-wave velocity (Vs) are highly related to porosity and pore structure, a formula based on the relationship between Vs and T2gm (NMR T2 geometric mean) was established. It is found that the T2gm is a power function of the shear-wave velocity. The respective coefficients in this formula for different lithologies were derived through petrophysical measurements of core samples (both NMR and ultrasonic experiments). The relationship model displays the same power-law relations as fitting expression from the experimental data.After that, there is a relation-model application for field data further validated effectiveness and reliability by contrasting the Shear-wave velocity determined by NMR logging with the direct measurements. This model establishment also helps to predict the mutual prediction of NMR and acoustic information of rocks. Based on the sensitivity of the vertical and transverse wave ratios of the formation to the gas-bearing properties of the reservoir, a NMR-acoustic velocity joint gas-bearing identification map was established. An extended case study demonstrated that the cross-plot between NMR logging and acoustic logging is also applicable to natural gas-bearing reservoir identification. As an important supplement and perfection of the existing methods, the relation model proposed in this paper offers a new thought for the petrophysical and in-situ field studies.

Permeability inversion using induced microseismicity: A case study for the Longmaxi shale gas reservoir

We have predicted the flow permeability and its spatial distribution for the Longmaxi shale gas reservoir using microseismicity induced during hydraulic-fracturing stimulation. In the time-of-occurrence versus distance-from-injector plot, we find that microseismic points exhibit a parabolic envelope, which we interpret as a triggering front. This reveals that fluid pressure diffusion is at least one of the underlying mechanisms of microseismicity generation. We derive the large-scale equivalent diffusivity from the triggering front plot and thereafter obtain a 3D diffusivity map of the heterogeneous reservoir by solving an eikonal-like equation suggested previously. During this process, we apply kriging interpolation to increase the density of sparsely distributed microseismic points. The resulting diffusivity ranges between 1.0 and [Formula: see text] with the peak probability attained at [Formula: see text], which is consistent with the estimate we obtain from the triggering front analysis. We transform the diffusivity map into a permeability map using three different theories of fluid pressure diffusion in porous media: the seismicity-based reservoir characterization method (SBRC) based on Biot’s theory of poroelasticity, the quasirigid medium approximation (QRMA), and the deformable medium approximation (DMA) based on the de la Cruz-Spanos theory. The permeability according to QRMA is slightly higher than that from SBRC, yet we observe no significant difference. However, these estimates are by one order of magnitude higher compared with the permeability estimate from DMA. Furthermore, the permeability from all three theories is much higher than that from previously reported core sample measurements. We interpret this as the difference between large-scale equivalent and matrix permeability and therefore lend weight to the hypothesis that there exist highly conducting fluid pathways, such as natural fractures.

Characterization of Uranium Ore Samples by HPGe Gamma-Ray Spectroscopy

Gamma logging for uranium exploration is currently based on total counting with the Geiger–Muller gas detectors or NaI(Tl) scintillators. However, the total count rate interpretation in terms of uranium concentration may be impaired in case of roll fronts when the radioactive equilibrium of the natural 238U radioactive chain is modified by the differential leaching of uranium and its daughter radioisotopes radium, radon, and so on. Indeed, in the case of secular equilibrium, more than 95% of gamma rays emitted by uranium ores come from 214Pb and 214Bi isotopes that are in the back end of the 238U decay chain. These two isotopes might produce an intense gamma signal even when uranium is not present, or with a much smaller activity, in the ore. Therefore, gamma spectroscopy measurements of core samples are performed on the surface with HPGe detectors to directly characterize uranium activity from the 1001-keV gamma ray of 234mPa that is at the beginning of the 238U chain. However, due to the low intensity of this gamma ray, acquisitions of several hours are needed. In view to characterize uranium concentration within a few minutes, we propose a method using both the 92 keV gamma rays of 234Th and 235U and the 98.4-keV uranium X-ray. This last is due to uranium self-induced fluorescence caused by gamma rays of the uranium chain, mainly 214Pb and 214 Bi. The gamma rays of 214Pb and 214Bi undergo scatterings in the sample leading to photons with energy in the 100-keV range that favor photoelectric interactions and, thus, fluorescence. The comparison of the uranium activity obtained with the 92- and 98.4-keV lines allows detecting a uranium heterogeneity in the ore. Indeed, in the case of uranium nugget, the 92-keV peak leads to underestimated uranium concentration due to the gamma self-absorption, but on the contrary, the 98.4-keV peak leads to an overestimation because of increased fluorescence. In order to test this new approach, tens of uranium ore samples have been measured with a handheld HPGe FALCON 5000 detector.