Rock Thin Sections Research Articles

Deformation Bands and Associated FIP Characteristics From High-Porous Triassic Reservoirs in the Tarim Basin, NW China: A Multiscale Analysis

Deformation bands are widely formed and distributed in Triassic high-porous rocks as a result of multistage tectonic movement. In this research, core observation, the rock thin section (fluorescence and casting thin section), FIB-SEM, X-ray diffraction, Raman laser, and thermometry of fluid inclusions were employed to describe the macro- and micro characteristics of deformation bands and their associated relationship with microfractures. Results indicate that the main types of deformation bands formed in the Lunnan Triassic high-porosity sandstone during the Yanshanian and Himalayan periods under different temperature and pressure conditions are compaction shear bands, and their quantity increases evidently with the distance of thrust faults. The density of deformation bands near the fault is about 15/m; porosity and permeability decrease sharply compared with those of the host rock. Microscopically, two obtained fluid-inclusion planes (FIPs) can be distinguished as 51 samples collected from 12 wells by the cutting relationship and mechanical characteristics. The homogenization temperature of associated aqueous inclusion is generally characterized by two peaks, mainly 70–80°C and 110–120°C, which were formed in the Late Yanshanian and Late Himalayan periods. The formation period of deformation bands induced by the intragranular microfractures improved the reservoir seepage capacity. In the later stage, as the interlayer and barrier with low porosity and low permeability affects the distribution of oil and gas, which is an important factor in this study of the local fluid dynamic field and high-quality reservoir evolution distribution.

Effects of surface roughness and mineralogy on the sorption of Cm(III) on crystalline rock

Crystalline rock is one of the host rocks considered for a future deep geological repository for highly active radiotoxic nuclear waste. The safety assessment requires reliable information on the retention behavior of minor actinides. In this work, we applied various spatially resolved techniques to investigate the sorption of Curium onto crystalline rock (granite, gneiss) thin sections from Eibenstock, Germany and Bukov, Czech Republic. We combined Raman-microscopy, calibrated autoradiography and µTRLFS (micro-focus time-resolved fluorescence spectroscopy) with vertical scanning interferometry to study in situ the impact of mineralogy and surface roughness on Cm(III) uptake and molecular speciation on the surface. Heterogeneous sorption of Cm(III) on the surface depends primarily on the mineralogy. However, for the same mineral class sorption uptake and strength of Cm(III) increases with growing surface roughness around surface holes or grain boundaries. When competitive sorption between multiple mineral phases occurs, surface roughness becomes the major retention parameter on low sorption uptake minerals. In high surface roughness areas primarily Cm(III) inner-sphere sorption complexation and surface incorporation are prominent and in selected sites formation of stable Cm(III) ternary complexes is observed. Our molecular findings confirm that predictive radionuclide modelling should implement surface roughness as a key parameter in simulations.

SMART mineral mapping: Synchrotron-based machine learning approach for 2D characterization with coupled micro XRF-XRD

A Synchrotron-based Machine learning Approach for RasTer (SMART) mineral mapping was developed for the purpose of training a mineral classifier for characterization of millimeter-sized areas of rock thin sections with micron-scale resolution. An Artificial Neural Network (ANN) was used to extract relationships between coupled micro x-ray fluorescence (μXRF) data for element abundances and micro x-ray diffraction (μXRD) data for mineral identity. Once trained, the resulting classifier, i.e., the SMART mineral mapper, can identify minerals using only μXRF data. This is the real value of this machine learning approach because μXRF data are relatively fast to collect and interpret whereas μXRD data take longer to collect and interpret. Training and testing of an initial mapper were done with 192 coupled μXRF-μXRD data points sampled from a 0.25 mm2 area of a shale from the Eagle Ford formation, which was scanned with 2 μm resolution. All data used in this work were obtained from the Advanced Photon Source synchrotron beamline 13-ID-E at Argonne National Laboratory. Three minerals were mapped in the Eagle Ford rock sample, for which there were 8 elements characterized. In the testing phase, the minerals were correctly classified with accuracy of 97 % and higher. The trained SMART mapper was applied for self-similar upscaling by mapping a 14 mm2 scan of the Eagle Ford sample. Generated maps captured micro-scale features characteristic of the stratified texture of the rock, and the identified minerals agreed well with bulk XRD analysis of the powdered rock. The SMART mapper was also applied to a scan of a 6-mineral mixture of known composition to demonstrate ability to distinguish minerals of similar chemistry. The trained SMART mapper is transferable to scans from other x-ray microprobes because of the μXRF data normalization that accounts for sample- and beamline-specific properties like thickness, detector configuration, and incident energy.

Characteristics of Tight Sandstone Cement in Panke Area

In order to improve the success rate of oil and gas exploration and further study the impact of tight sandstone cements on reservoirs, this paper uses a large number of rock thin sections, scanning electron microscopy, and physical property analysis to analyze the cements of the Chang 6 reservoir in the Panke area, southern Ordos Basin. Features have been studied in depth. The results show that the cements in the study area mainly include: authigenic cements such as illite and chlorite, carbonate cements such as iron calcite and iron dolomite, and siliceous cements. As the depth of the stratum increases and the temperature rises, the content of illite gradually increases; the main distribution area of chlorite cement is shallower than that of illite; with the increase of buried depth, the content of carbonate cement has a increase trend ; The content of siliceous cement in the deeper stratum is higher than that in the shallow layer.

Characteristics of Hydration Damage and Its Influence on Permeability of Lamellar Shale Oil Reservoirs in Ordos Basin

The continental shale oil reservoir has low permeability, high clay content, rich lamellar structure, and strong heterogeneity, which makes the reservoir vulnerable to hydration damage. In order to study characteristics of hydration damage and its influence on permeability of lamellar shale oil reservoirs, a series of experiments such as high-pressure mercury injection, steady gas permeability, rock thin section identification, and scanning electron microscope were carried out with the downhole core in Ordos Basin as the experimental object. The effects of water and water-based drilling fluid on pore size distribution, permeability, and rock microstructure were analyzed. Results show that the pore size of the reservoir is mainly nanoscale, and the pore size of shale changes most dramatically in the stage of hydration for 12-24 hours, while that of tuff changes most dramatically in 24-48 hours. The permeability increases rapidly with hydration time and then tends to be stable, among which the permeability of samples with lamellar structure in the direction parallel to the lamellar structure is most easily affected by hydration and changes fastest. Hydration leads to the formation of new pores, new fractures, and the expansion of existing fractures in rocks, especially in the strata containing large amounts of terrigenous clastic, lamellar structure, and pyrite. The new seepage channel increases the permeability of rock, and the soil powder and plugging particles in drilling fluid are easy to form protective mud cake in these places. These protective mud cakes not only change the microstructure of rock but also inhibit the influence of hydration on the pore space and permeability of rock, which play an effective role in preventing the mineral shedding on the rock surface, reducing the increase of micropores and delaying hydration.

Rock thin sections identification based on improved squeeze-and-Excitation Networks model

Rock thin section recognition provides geological information, which is crucial in petroleum geology, exploration, and mining research as a kind of fundamental work. Although many machine learning methods solve this research, there are still problems of data hierarchy and model pertinence. We use the hierarchical classification method to divide the dataset into sedimentary, metamorphic, and igneous rock as first-level, and to subdivide a total of 105 s-level further from the three categories. We propose the MaSE-ResNeXt model based on the fundamental work in the SeNet that can enhance the feature connection between different channels. The MaSE-ResNeXt adopted hierarchical filter groups, bottleneck stacking, and other strategies to enhance the representational capability of the model which advances the solving ability in rock recognition. Six data enhancement methods and other techniques are used to improve the robustness and effectiveness. The accuracy in the test set was 90.89% and 81.97% for the first and second level, respectively, with the inference duration is only 0.0357s. This study also designs a degeneration experiment and model comparison to demonstrate the model's effectiveness. Future research can employ this model as the fundamental base of transfer learning in geology to save time in the training of study.

The Application of Ethyl A-Cyanoacrylate in the Early Stage of Geological Experiment

In recent years, the oil field chemical A-cyanoacrylate mixed adhesive has been used in rock preparation and preparation to a certain extent, and its role has been paid more and more attention due to the solidification of the rock surface in the rock thin section, the early embedding of the rock, and the adhesion of the thin side of the rock to the slide surface, etc. This paper introduces the preparation and application development of a-cyanoacrylate mixed adhesive in geological experiment, and the development of a-cyanoacrylate mixed adhesive in oilfield geological experiment.

The influence of magmatic-hydrothermal activities on porosity and permeability of sandstone reservoirs in the Linxing area, Ordos Basin, Northern China

The eastern margin of the Ordos Basin in the Linxing area has great potential for exploration of natural gas. However, the intrusion of the Zijinshan igneous pluton and associated hydrothermal activities have affected the sandstone reservoirs. Through the data analyses of rock thin sections, cathodoluminescence, X-ray diffraction, vitrinite reflectance, fluid inclusions, and reservoir physical property, this paper aims to clarify the influences of magmatic-hydrothermal activity and to explore the response characteristics of reservoir porosity and permeability. From the outer zone to the inner zone, the closer to the pluton, the closer the contact between the reservoir clastic particles, which confirms the compression caused by magma intrusion. The differences in feldspar dissolution and alteration, siliceous cementation, clay mineral content, vitrinite reflectivity, homogenization temperature and salinity of fluid inclusions, confirmed that magmatic-hydrothermal activity affected fluid properties and evolution of strata temperature. Combined with the vertical distribution characteristics of feldspar dissolution-alteration and the abnormal conversion of clay minerals, it is considered that the influence of hydrothermal fluid was limited to the reservoir under the thick mudstone of the Xiashihezi Formation. Magma intrusion causes the development of reservoir fractures, thus the permeability of the reservoir decreases from the inner zone to the outer zone, and the porosity presents the distribution pattern of “high-low-slightly high”. The reservoir porosity and permeability genetic model was established to provide references about favorable areas for oil and gas exploration and development in the Linxing area and areas with similar geological history.

VAN BÖLGESİNDEKİ URARTU MERKEZLERİNDE KULLANILAN KAYAÇLARA İLİŞKİN PETROGRAFİK GÖZLEMLER

Van and its vicinity have been a prominent region with settlements recording many civilizations since the earliest periods in history. The most stunning remains of civilizations in this region belong to the Urartian Kingdom, which was established in the centre of Van from the middle of the 9th century BC. The capital city of the Urartian Kingdom was Tushpa (Van Castle), which was established on the Van Castle rock cliffs rising on the eastern shore of Lake Van. In addition to Tushpa, the capital of the Kingdom of Urartu, the architectural remains of many castles, urban settlements, and other architectural structures, including dams and water canals, are extensively observed in the eastern part of Lake Van. Considering the geological structure of this central region, it appears that the Kingdom’s settlements and architectural structures were founded on the Van formation, which consists of Bitlis Metamorphics, Upper Cretaceous Ophiolites and Tertiary deep-sea sediments that form the basement rocks in the region. This study was carried out to determine petrographic characteristics and classify rock types of natural stones used as building materials in Van Castle, Çavuştepe, Ayanis, Toprakkale, Zivistan, Keçikıran Castle, Körzüt Castle and Menua Canal belonging to the Urartian Kingdom. A secondary purpose was to use a geological approach to determine the quarries from which they were extracted. For this purpose, representative natural stone samples were taken from the architectural structures and their remains in the settlement centres of Urartian Kingdom in order to prepare rock thin sections of natural stone samples. The thin sections were examined under polarising petrographic microscope to determine petrographic features and classify the rock types. When the architectural building groups in Urartian settlements are examined, different natural stones were mostly used as building materials. The rock types of these natural stones used in construction of these structures are generally classified under two main groups as igneous and sedimentary origin. Sedimentary rock types such as limestone, travertine and sandstone were preferred as the main building material in settlement centres around the Lake Van Basin. Additionally, igneous rocks types such as gabbro, basalt, andesite and serpentinite were preferred more intensely in centres which are located around the north and western part of Lake Van. At the point of determining the sources of rock types used as natural stone building materials in the Urartian centres, it was concluded that Urartu primarily supplied those materials from the nearest quarry sites. The use of this material is also possible especially from rocky or other nearby areas on which the structure was built. However, in line with the materials used in cuneiform inscriptions and monumental architectural structures such as temples, etc, the supply of building materials was also provided by distant sources. Considering the geology of the region, it is suggested that essential findings were obtained showing that igneous rocks were brought from the areas north and west of Lake Van, while sedimentary rocks are represented by limestones from the southern part of Lake Erçek, and travertine rocks from quarries in the Edremit region.

Research on Application of Image Enhancement Technology in Automatic Recognition of Rock Thin Section

Artificial intelligence technology has rapidly emerged in various new industries due to its high efficiency and has been successfully used in many fields. However, it has been slow to start in the field of petroleum exploration, under the background of the need for more efficient exploration and development in the petroleum field. In this paper we used the ResNet-18 convolutional neural network to make an attempt to automatically identify rock thin section, and finds that this method can efficiently identify rock thin section and has a higher accuracy rate. In addition, we adopted appropriate image enhancement technology, which can significantly improve the recognition accuracy of the model. It proves that related machine learning technology has broad application prospects in the fields of petroleum exploration and petroleum geology.

Polarized light micrograph dataset of Late Cretaceous-Eocene rock thin sections from western Tarim Basin, Xinjiang

Polarized light micrograph dataset of Late Cretaceous-Eocene rock thin sections from western Tarim Basin, Xinjiang

Successful complete digestion of well lithified shale and extraction of microfossils from Devonian beds in western New York

ABSTRACT: Researchers in paleontological and paleoecological sciences often need complete disaggregation of rock materials for certain lines of investigation. However, complete disaggregation of more lithified sedimentary rock is known to be problematic. A complete shale disaggregation method implementing quaternary ammonium surfactants,widely used in paleontological sciences for poorly lithified shale and mudstone, was successfully used on well lithified Devonian shale in the Appalachian Basin ofWestern New York. Over 50 Devonian gray and black shale samples were collected from multiple localities in western New York (Cashaqua, Rhinestreet, Skaneateles, Windom, and Ludlowville), coarsely crushed, and fully immersed in a quaternary ammonium surfactant until complete disaggregation was achieved (5–14 days); aliquots were run through a series of nested sieves. The sieved sediments contained hundreds of well-preserved microfossils released from the shale: ostracods, dacryoconarids, and previously unreported palymorphs, charophytes, agglutinated foraminifera, miospores, and other microspherules. These microfossils were easily found within disaggregated and sieved samples but were unrecognizable on the shale surface and destroyed in prior investigations of whole rock thin sections. In addition to more traditional approaches, inclusion of this complete rock disaggregation method may assist in a more complete analysis of material, increase our understandings of ancient basin systems and have important implications on our understanding of the paleoecology during the Late Devonian marine biotic crises.

Sedimentary cycles of evaporites and their application in sequence division in the upper member of the Xiaganchaigou Formation in Yingxi Area, Southwestern Qaidam Basin, China

The upper member of the Xiaganchaigou Formation in the Yingxi Area of the Southwestern Qaidam Basin is a set of evaporite-bearing lacustrine series. In this study, petrographic analyses of rock thin sections, cores, drillings, logging as well as geochemistry were used to study the characteristics of the sedimentary cycles of the series. Concurrently, this study adopts a transgressive–regressive (T–R) cycle sequence theory, based on lithology, logging curves, the stacking pattern of the subsequences, and unconformity and seismic reflection terminal relations. This approach uses evaporites as the primary marker layer for identifying the initial lake flood surface and dividing the sequence of the evaporite-bearing series in the upper member of the Xiaganchaigou Formation. Results show a zonal distribution of evaporites transitioning laterally from the center to the margin of the basin to mixed carbonate rocks and then to clastic rocks. Vertically, there are two third-order sedimentary cycles and six fourth-order sedimentary cycles. Five types of evaporite lithofacies combinations were identified. Evaporites were formed by evaporative crystallization at a particular depth beneath lake water during a lacustrine regression during an arid paleo-climate and rapid subsidence of the basin basement. It has been established based on the asymmetric sedimentary cycle development model that during the lacustrine transgression stage, the mixed carbonate rocks were transformed into mudstone upward, and during the lacustrine regression stage, the mixed carbonate rocks transformed into gypsum rocks, glauberite, and halite, upward, while a delta and reef flat limestones developed at the edge of the basin. There is a one-to-one correspondence between the T–R cycle sequence division and the sedimentary cycle division.

Petrographic microfacies classification with deep convolutional neural networks

Petrographic analysis is based on the microscopic description and classification of rocks and is a crucial technique for sedimentary and diagenetic studies. When compared to hand specimens, thin sections provide better and more accurate means for analysis of mineral proportion, distribution, texture, pore space analysis, and cement composition. Most petrographic analysis relies on visual inspection of rock thin sections under a microscope, a task that is laborious even for experienced geologists. Large projects with a tight time frame requiring the analysis of a large amount of thin sections may require multiple petrographers, thereby risking the introduction of inconsistency in the analysis. To address this challenge, we explore the use of deep convolutional neural networks (CNN) as a tool for acceleration and automatization of microfacies classification. We make use of transfer learning based on robust and reliable CNN models trained with a large amount of non-geological images. With a relatively small number of labeled thin sections used in “fine-tuning” training we are able to adapt CNN models that achieve low error levels (<5%) for the classification of microfacies from the same dataset, and moderate results (<40%) for the classification of microfacies of thin sections from different datasets. These alternate datasets differ from the training data on two independent factors: the thin sections are from different formations and are prepared by different laboratories. While becoming widely accepted as a useful tool in the biological and manufacturing disciplines, CNN is currently underutilized in the geoscience community; we foresee an increase of use of such techniques to help accelerate and quantify a wide variety of geological tasks.

Computing the permeability and Forchheimer tensor of porous rocks via closure problems and digital images

Current computing capabilities, in combination with available theoretical frameworks, allow for the petrophysical evaluation of porous rocks from simple images. This procedure represents a less expensive alternative and it complements, generally expensive, laboratory measurements. A porosity, permeability and Forchheimer tensors estimation is reported here through a numerical solution of associated closure problems within digital images of porous rock thin sections. The solution of these steady-state boundary-value problems allows direct computation of all permeability elements and Forchheimer tensors. The digital images were obtained from a computer procedure that identifies the network of pores in thin sections. The results of the numerical estimation of permeability and porosity and its scopes were compared with those obtained via experimental measurements in four samples representing three distinct lithologies (travertine, sandstone and limestone), and were found to be in acceptable agreement. Once the permeability was computed, the Forchheimer tensor was calculated as function of the pore-scale Reynolds number. The Forchheimer coefficient varied with fluid velocity at an exponent close to 2 (range from 1.7 up to 4.2) depending on the lithology and local microstructure. The critical Reynolds number at which the Forchheimer coefficient became relevant was approximately 0.25. We found that the Forchheimer tensor exhibited anisotropy not only according to the local microstructure but also according to the flow path.

A Deep Learning Model for Quick and Accurate Rock Recognition with Smartphones

In the geological survey, the recognition and classification of rock lithology are an important content. The recognition method based on rock thin section leads to long recognition period and high recognition cost, and the recognition accuracy cannot be guaranteed. Moreover, the above method cannot provide an effective solution in the field. As a communication device with multiple sensors, smartphones are carried by most geological survey workers. In this paper, a smartphone application based on the convolutional neural network is developed. In this application, the phone’s camera can be used to take photos of rocks. And the types and lithology of rocks can be quickly and accurately identified in a very short time. This paper proposed a method for quickly and accurately recognizing rock lithology in the field. Based on ShuffleNet, a lightweight convolutional neural network used in deep learning, combined with the transfer learning method, the recognition model of the rock image was established. The trained model was then deployed to the smartphone. A smartphone application for identifying rock lithology was designed and developed to verify its usability and accuracy. The research results showed that the accuracy of the recognition model in this paper was 97.65% on the verification data set of the PC. The accuracy of recognition on the test data set of the smartphone was 95.30%, among which the average recognition time of the single sheet was 786 milliseconds, the maximum value was 1,045 milliseconds, and the minimum value was 452 milliseconds. And the single-image accuracy above 96% accounted for 95% of the test data set. This paper presented a new solution for the rapid and accurate recognition of rock lithology in field geological surveys, which met the needs of geological survey personnel to quickly and accurately identify rock lithology in field operations.

Pore structure characterization through path-finding and Lattice Boltzmann simulation

Characterization of underground porous media parameters at the micro and macro scales is fundamental in geosciences. A thorough comprehension of flow phenomena requires analyses and observations at the micro scale through adoption of micromodels as representative as possible of real geological formations. In this paper we focus on the analysis of 2D binary images of real rock thin sections to characterize pore network geometry and to estimate effective porosity, pore size distribution and tortuosity with the aim of providing suitable information for designing micromodels. To this end, a geometrical analysis of the pore structure, based on the identification and characterization of the set of the shortest geometrical pathways between inlets and outlets pairs, was implemented. The geometrical analysis is based on a path-finding algorithm derived from graph theory. Results provided by geometrical analysis were validated against hydrodynamic numerical simulation via the Lattice Boltzmann Method (LBM). Results show that the path-finding approach provides reasonable and reliable estimates of tortuosity and can be successfully applied for analyzing the distribution of effective pore radius, as well as for estimating the effective porosity.

SEM-EBSD Analysis of Broad Ion Beam Polished Rock Thin Sections – The MFAL Protocol

Abstract A protocol is presented to perform Broad Ion Beam Polishing (BIBP) of rock thin sections to obtain a surface that can yield high quality crystallographic preferred orientation data using SEM-EBSD. The modus operandi, referred to as Mamtani’s Fabric Analysis Lab (MFAL) protocol, involves flat milling of a rotating rock thin section using a triple ion beam milling system (Leica EM TIC 3X) in which tilt angle of sample (degree) with reference to ion beam (Argon), acceleration voltage (kV) and source current (mA) can be controlled along with lateral and rotary movements. The protocol has been developed after &amp;gt;90 hours of BIBP experiments on various rock samples under different experimental settings (tilt angle/kV/mA) followed by SEM-EBSD analysis. Each experiment was performed at medium rotation speed (7 rpm) with a lateral movement of upto ±7 mm on rectangular rock thin sections (long dimension &amp;lt;25 mm). The best surface for SEM-EBSD analysis of rock thin sections is obtained in two steps of BIBP. In step-1, cleaning of thin section is done for 5 minutes (1.5°/4 kV/1.5 mA). In step-2, polishing is done for 30 minutes (1.5°/4 kV/3 mA). BIBP following MFAL protocol yields very good SEM-EBSD data from hard and soft mineral phases in rocks that enable (a) determination of mineral slip systems, (b) kinematics and (c) EBSD data-based mapping of grain boundaries of soft mineral phases (like hornblende) for petrofabric analysis in a polymineralic rock, which has always remained a challenge from mechanically polished samples. It is concluded that the MFAL protocol saves more than 5 hours of sample preparation time over other sample preparation methods for SEM-EBSD studies.

Generating a pixel-wise annotated training dataset to train ML algorithms for mineral identification in rock thin sections

Generating a pixel-wise annotated training dataset to train ML algorithms for mineral identification in rock thin sections

Effect of Amending Acid Oxisols Using Basalt Dust, Tithonia diversifolia Powder and NPK 20-10-10 on Garlic (Allium sativum) Production in Bafut (Cameroon Volcanic Line)

Aims: To compare the effects of basalt dust, Tithonia diversifolia (T. diversifolia) powder and NPK 20-10-10 on the growth and production of Garlic (Allium sativum, softneck variety) in Bafut (Cameroon Volcanic Line).&#x0D; Study Design: A randomized complete block design (RCBD) with three replications in the field was used. The treatments were T0 (control), T1 (0.7 tons ha-1 NPK 20-10-10), T2 (0.4 tons ha-1 basalt), T3 (0.6 tons ha-1 basalt) and T4 (0.5 tons ha-1 T. diversifolia powder).&#x0D; Place and Duration of Study: The study conducted in Bafut (Cameroon) from 2nd August 2017 to 24th February 2018.&#x0D; Methodology: Fieldwork involved land preparation, planting and collection of growth and yield parameters as well as rocks and soil sampling. Laboratory work involved soil physicochemical analysis and cutting of rock thin sections for microscopic observations. The plant data were subjected to statistical and economic analyses.&#x0D; Results: The control soil (T0) showed a sandy clayey loamy texture, acidic pH (5.1), very high organic carbon (6.4%), low total nitrogen (0.2%) and moderate available phosphorus (19.42 mg kg-1). The exchangeable complex revealed high K+ (0.88 cmol (+).kg-1), very low Ca2+ (0.63 cmol (+).kg-1) and Mg2+ (0.21 cmol (+).kg-1), low Na+ (0.07 cmol (+). kg-1), very low sum of exchangeable bases (1.79 cmol (+).kg-1), moderate cation exchange capacity (CEC) (22.7 cmol (+). kg-1) and a very low base saturation (7.88%). C/N ratio was very high (35&gt;17) indicating very poor quality organic matter and a potentially very slow mineralization rate. Growth and yield parameters, except fruit number, were such that T2&gt;T3&gt;T4&gt;T1&gt;T0. T2, T3 and T4 plants gave high yields while T1 recorded the lowest yields below the control. The net yield showed that T3&gt;T4&gt;T2&gt;T0&gt;T1 suggesting that basalt dust and T. diversifolia powder improved soil fertility that in turn boosted yields. Economically, T1 had a BCR (benefit-to-cost ratio)&lt;1 indicative of no profit, while T2, T3 and T4 showed a BCR&gt;2 indicating more than 100% profit of the investment and a possibility of popularization of these treatments.&#x0D; Conclusion: Natural basalt dust and T. diversifolia powder treatments gave better garlic yields indicating a better soil fertilizing capacity compared to synthetic NPK 20-10-10. Basalt dust and T. diversifolia can be popularized to local inhabitants.