Rock Quality Index Research Articles

Contribution to the numerical modelling analysis of displacements caused by tunnel construction in discontinuous rock masses

This paper presents a comprehensive study of the stability conditions of a rock mass surrounding a tunnel, using numerical modelling analysis of displacements induced by the tunnel construction. The case study focuses on the Boukhadra iron ore mine in Algeria. This research employs empirical equations from literature based on geomechanical classifications to provide the most appropriate geotechnical input data for simulation. In addition to those equations, a novel correlation equation relating the rock mass ratio (RMR) and the rock quality index (Q) was developed. This equation gives a high regression coefficient, revealing a strong correlation (R2) of 0.878. It gives a better estimation of the rock mass characteristics: Young’s moduli (E), Poisson’s ratio (υ), cohesion (C), and friction angle (φ), compared to the existing literature-based correlation equations. The estimated parameters were used to pass from a discontinuous to a continuous equivalent medium, making the numerical modelling easier with the finite element method. Compared with intact rock and direct equations, the numerical simulation results based on the new equation fit well with the in-situ observations and provide a more reliable comprehension of rock mass behaviour. The new equation proposed in this paper provides a substantial evaluation of the rock mass parameters needed in the design process of underground structures once used with respect to their acceptable ranges.

Quality evaluation of surrounding rocks in a mine shaft based on the game gray target model

Accurate evaluation of surrounding rock quality grade can help guarantee the safety of tunnel design and construction; hence, it has great significance in the construction of mine shafts. Accordingly, the uniaxial saturated compressive strength of the rock block Rc, rock quality index RQD, rock softening coefficient kR, integrity coefficient of the rock mass kv, depth H, unit weight of the rock mass γ, coefficient of quantification of the angle between the principal structural plane and shaft axis k2, and weight of the groundwater k1 are first selected as the indexes of assessment to introduce the game gray target model. Then, the gray target model of the surrounding rocks in a mine shaft project is established. The weight coefficient of each index is next calculated using the combination weighting method based on game theory, and the synthetic target center distance of each sample is determined using the gray target model. Finally, the quality level of the asphalt pavement is determined. The suggested model can be used to mine a small data sample to the maximum extent possible, thereby minimizing the information shortage caused by the small sample to a certain extent, to evaluate the final quality grade of the surrounding rocks quantitatively. Thus, the proposed approach provides a new scheme for the future quality assessments of surrounding rocks.

Drilling Process Monitoring for Predicting Mechanical Properties of Jointed Rock Mass: A Review

Reliably assessing the quality and mechanical properties of rock masses is crucial in underground engineering. However, existing methods have significant limitations in terms of applicability and accuracy. Therefore, a field measurement method that meets the real-time monitoring and safety requirements for the quality of engineering rock masses is needed. Firstly, the research findings of domestic and international scholars on the application of drilling process monitoring technology are comprehensively analyzed. Rotary cutting penetration tests are conducted on tuff rock masses containing fractures and joints. Various rock mass classification and evaluation standards are integrated with rotary penetration tests. Rotary cutting penetration tests are used to determine the residual strength of rock, based on this review. The rationality of the calculated mi parameter values is validated. The peak strength, residual strength, and errors of the rock are obtained based on the penetration method. The rock quality index rock quality designation from drilling (RQDd) is redefined, based on the drilling process monitoring apparatus (DPMA). Rock mass classification is conducted, based on the correlation between the standard deviation of rotary drilling energy and the rock quality designation (RQD). Additionally, a new relational formula is introduced to determine the RQD from variations in drilling energy, based on discontinuity frequency. This field measurement method undoubtedly provides a crucial scientific basis for rock design and construction, ensuring long-term safety in engineering applications.

Permeability Prediction for Carbonate Rocks using a Modified Flow Zone Indicator Method

Carbonate reservoir rocks are usually heterogeneous, so it is not an easy task to establish a relation between porosity and permeability in these types of reservoir rocks. First, Kozney and Kozney-carmen formulas were used to establish these relations. Later, the flow zone indicator (FZI) method was introduced, which was widely used to find such a relation since it shows better results than the two former methods. In this work, the classical FZI method and a modified form of the FZI method are utilized to identify the hydraulic flow units and rock quality index to predict permeability. In this FZI method, the cementation factor (m) was introduced in calculating the value of FZI. The data collected from core analysis of the cored intervals in the Tanuma and Khasib formations were used as a database for this work. The classical and the modified FZI methods were applied using the database to predict core permeability. The value of the cementation factor was tuned to get a better match between the predicted permeability resulting from applying the modified method and the measured permeability values. Results show that the correlation coefficients resulting from applying the modified FZI method are closer to unity compared with that resulting from the classical FZI method. Cementation factor (m) of m = 3 for Tanuma formation and m = 3 for Khasib formation are the best values used with the modified FZI method. The modified FZI method shows a regression factor of 0.9986 for Tanuma and 0.9942 for Khasib formation.

Comparative Study of Rock Mass Classification Systems: A Case Study of Nagdhunga-Naubisea Road Tunnel

Ground classification systems have been widely used to characterize the soil or rock mass for the analysis and design of underground structures. Deformation characteristics of rock mass around the underground excavation boundary varies according to types of rock and their properties, in situ stress condition and types of support used. Broadly used classification systems for underground structures are Rock Mass Rating (RMR) and Rock Quality Index (Q- Systems) but in-case of the Nagdhunga-Naubisea road tunnel Nippon Expressway Company Limited used NEXCO-System. Literally, the NEXCO classification is based on the velocity of elastic wave, geological condition, boring core condition, competence factor, stability of tunnel face and convergence. However, in-case of Nagdhunga-Naubisea road tunnel, grade point is computed using the similar parameters that are used in RMR- System and Q-System. This research focuses about comparison between ground classification from RMR, Q-system and NEXCO system. The geological descriptions obtained from project office at chainages (0+497 to 0+502), (0+508 to 0+513), (0+581.8 to 0+587.8) and (0+584.2 to 0+590.2) were used to correlate the relationship between RMR, Q-system and NEXCO system of rock mass classification systems. Results showed that from RMR, the ground classification is “poor” at all the chainages whereas from Q-system is “very poor” at chainage (0+508 to 0+513) and “poor” at other chainages. Similarly, from NEXCO- system it was found that “DII” at chainages (0+497 to 0+502) and (0+508 to 0+513) and CII for chainages (0+581.8 to 0+587.8) and (0+584.2 to 0+590.2). These results revealed that the ground classification from NEXCO as DII is similar to poor from RMR and poor or very poor from Q system where as CII from NEXCO is similar to poor from both RMR and Q system.

Assessment of rock mass properties and load-bearing potential in low-grade metamorphic rocks: A study from the Tigray region, Ethiopia

<p>This study presents an engineering geological investigation aimed at assessing the bearing capacity of the proposed site for the Meli gold processing plant (GPP) located in the northwestern region of Tigray, Ethiopia. The geological composition of the site predominantly comprises low-grade metamorphic rocks, with intermediate metavolcanic rocks being the most prevalent. This research utilized an innovative combination of empirical methodologies, including the Hoek–Brown and Mohr–Coulomb criteria, to evaluate the strength and elasticity characteristics of the rock mass. Additionally, the rock mass foundation for the GPP was rigorously classified using renowned systems such as the rock mass rating (RMR), quality index (Q), and geological strength index (GSI). Employing five different empirical equations to estimate bearing capacity, this study significantly advances our understanding by comparing these diverse methodologies, which is a novel approach in this geological context where engineering property data are scarce or non-existent. The bearing capacities determined using the Hoek–Brown and Mohr–Coulomb criteria ranged from 11.6 to 46.2 MPa and 7.9 to 10.5 MPa, respectively. These findings not only offer valuable insights into the assessment of bearing capacity in metamorphic rock formations but also underscore the effectiveness of combining multiple empirical approaches to enhance the reliability of geological assessments. This research contributes to the advancement of construction practices and enhances project planning strategies in comparable geological environments, particularly highlighting the utility of robust empirical data in the absence of extensive drilling data. By integrating comprehensive empirical analyses, the study provides a methodological framework that significantly aids in informed decision-making for future projects located in similar geological settings.</p>

Designing a more stable tunnel at PAARI mining syndicate

High fracturing and faulting at Paari Mine syndicate have resulted in weak ground conditions making it difficult to conduct mining operations safely. The hanging walls and the side walls are covered with numerous faults and intersecting striking joints forming wedges which are extremely unstable. The project aims to solve the mines problem of tunnel subsidence. The work performed included studying the rock formations within the mine and determining their properties and response to excavations. The rock mass was then classified according to the rock mass rating and the rock quality index. Support design was done using guidelines according to rock mass rating tables. Ground support practices that are currently used at the mine and analysing vulnerabilities of the system were then studied and the use of systematic rock bolting, 2 meters long with a diameter of 24 mm fully grouted was proposed. In addition, we recommend that a spacing of 1 m to 1.5 m of the bolds should be used on the crown pillars as well the walls and that wire mesh should also be used as an additional support mechanism.

Investigating the geomechanical properties and permeability of the rocks of the Kurit dam site using geostatistical methods

As dams play a very important role in the optimum use of water resources, it is very important to keep them stable and the water stored in the reservoir. It is particularly important to investigate how water moves through rocks and the permeability and quality of the rock mass in structures like dams. Therefore, one of the issues considered in dam stability is monitoring the quantity of leaks. In this research, the engineering geological and geotechnical parameters of the rock mass for the construction of the Kurit Dam located in the city of Tabas in eastern Iran were evaluated. Initially, following the determination of geotechnical parameters, the engineering classification of the rock mass of the study area was carried out. In addition, in order to study and trace the water evacuation routes of the dam construction, two parameters of the RQD and Lugeon were studied and modelled. Analyses have been conducted to examine the permeability and rock quality index in three parts of the left and right abutment, the dam’s axis and reservoir with geostatistics and kriging methods. Three-dimensional model of the construction of the Kurit dam was presented and the results were analyzed. Based on the results, the quality of the rock mass in the right and left abutments is arguably better than the dam axis and reservoir. Additionally, as the depth increases, the permeability decreases and the permeability is higher at shallow depths. The highest level of permeability is located at the surface and near the BH4 borehole.

Comparison of existing joint orientation parameters and their effect on rock erodibility in dam spillways

Rock mass erosion in unlined spillways causes significant structural damage and necessitates expensive repairs. The rock mass is made up of blocks formed by various arrangements of joint sets. The volume and the protrusion of these blocks, as well as the orientation, opening and roughness of the joints, are all features that can affect rock erodibility. Most of these features are incorporated in parameters developed for rock mass characterization. Three joint orientation parameters are compared in this article using a database containing geological and hydraulic information on scoured spillways. According to the detailed method, data are first classified according to rock quality using the Geological Strength Index obtained with the chart suggested by Marinos and Hoek (GSI chart ). Then, for each GSI chart class, data are distributed according to the damage level, stream power and joint orientation parameter chosen. This study shows that no joint orientation parameter is currently able to accurately represent the effect of joint orientation on erosion of excellent- to poor-quality rock mass. Moreover, this study shows that the GSI chart index is not a rock quality index that completely evaluates rock erosion, as some relevant parameters for evaluating rock erodibility are not considered.

Intelligent recognition of drill cores and automatic RQD analytics based on deep learning

Rock quality designation (RQD), as a well-accepted and appliable rock quality index, is crucial in geotechnical engineering. Current RQD estimation mainly relies on either manual statistics or the image binarisation method, while the former approach surrenders high labour intensity and low efficiency and the latter one is constrained by image acquisition. Considering the above-mentioned limitations in RQD estimation, this study proposed a novel convolutional neural network (CNN) approach to automatically perform core recognition and RQD cataloguing with significant improvement in accuracy and efficiency. Firstly, the proposed neural network automatically identified the prefabricated round markers to distinct drilling rounds. To maximumly strengthen the engineering capability of CNN without losing generality, we considered image inversion, rotation, noise addition, and RGB conversion of 200 core box samples in total. Secondly, replacing the unstable image binarisation method, the advanced YOLO V2 object detection model, a single-stage real-time object detection model, was adopted in this study. We also proposed the modified four-layer downsampling structure as our CNN, and then developed an automatic recognition approach for both cores and the round markers, resulting in a 93.1% accuracy according to the validation set. Thirdly, this study proposed an auto-ranking algorithm to sequence the core sample according to the confidence of core recognition by the CNN and row-scanning results for subsequent RQD cataloguing. In addition, the optimal scan width was proved to be 1.33 times larger than the average core width. Finally, a quick cataloguing platform for drill cores was developed. Compared with manual measurement and visual statistics, intelligent RQD cataloguing is characterised by its unparalleled accuracy and efficiency, which is merited by the low relative error (1.84%) and fast processing time (around 0.2 s). Moreover, the application presented in this paper is applicable to most geotechnical engineering scenarios. This is attributed to its low requirements in image acquisition, high efficiency, precise recognition, and robustness.

Determination of Reservoir Hydraulic Flow Units and Permeability Estimation Using Flow Zone Indicator Method

Reservoir characterization plays a crucial role in comprehending the distribution of formation properties and fluids within heterogeneous reservoirs. This knowledge is instrumental in constructing an accurate three-dimensional model of the reservoir, facilitating predictions regarding porosity, permeability, and fluid flow distribution. Among the various methods employed for reservoir characterization, the hydraulic flow unit stands out as a widely adopted approach. By effectively subdividing the reservoir into distinct zones, each characterized by unique petrophysical and geological properties, hydraulic flow units enable comprehensive reservoir analysis. The concept of the flow unit is closely tied to the flow zone indicator, a critical parameter that defines the porosity-permeability relationships of each hydraulic flow unit. Additionally, the flow zone indicator method proves valuable in estimating permeability accurately. In this study, we demonstrate the application of the flow zone indicator method to determine hydraulic flow units within the Khasib formation. By analyzing core data and calculating the Rock Quality Index (RQI) and Flow Zone Indicator (∅Z), we differentiate the formation into four hydraulic flow units based on FZI values. Specifically, HFU 1 represents a rock of poor quality, corresponding to compact and chalky limestone. HFU 2 represents intermediate quality, corresponding to argillaceous limestone, while HFU 3 represents good quality, corresponding to porous limestone. Lastly, HFU 4 signifies an excellent reservoir rock quality characterized by vuggy limestone. By establishing a permeability equation that correlates with effective porosity for each rock type, we successfully estimate permeability. Comparing these estimated permeability values with core permeability reveals a strong agreement with a high correlation coefficient of 0.96%. Consequently, the flow zone indicator method effectively classifies the Khasib formation into four distinct hydraulic flow units and provides an accurate and reliable means of determining permeability in the reservoir. The resulting permeability equations can be applied to wells and depth intervals lacking core measurements, further emphasizing the practical utility of the FZI method.

A rockburst grade evaluation method based on principal component analysis and the catastrophe progression method

Rockburst disasters always have a great influence on engineering practice. In order to accurately predict the occurrence of rockburst hazards, this paper proposes a rockburst rating evaluation method based on principal component analysis (PCA) and the catastrophe progression method, taking into account several influencing factors. In this paper, 15 indicators, such as strength brittleness factor (R), stress factor (P), and rock quality index (RQD) (reflecting the strength and fragmentation degree of rock mass), were selected from seven samples and were analyzed and downscaled by principal component analysis. Combined with the catastrophe progression method, each layer index was dimensionless and normalized to determine the mutation level value of each layer. Based on the principle of complementarity or non-complementarity, to determine the total mutation level value, the layer index was used to divide the rockblast-level interval and predict the rockblast level. The results show that the method proposed in this paper can be used to not only distinguish the importance of each of the same level of indicators but also avoid the impact of superimposed factor correlations between the same level of indicators, making the results more objective. This paper presents accurate rock explosion assessment results and an actual engineering situation. The number of factors affecting the assessment of the rock explosion level provides new insights.

„ხობი 2 ჰესის“ ჰიდროტექნიკური კომპლექსის სათავე ნაგებობის და ჰესის შენობის სამშენებლო მოედნის ამგები გრუნტების ფიზიკურ-მექანიკური თვისებები

Modern methods of rock evaluation, such as Rock Quality Index (RQD), Rock Mass Rating (RMR) and Rock Mass Classification System (Q), are used within the field of geotechnical surveys. RQD was determined by D.U. Deere in 1963, as a simple classification system of rock mass stability. While using RQD index five classes of rocks (A-E) are determined. Q value can be determined in different ways: during mapping in underground excavations, on the surface or alternatively – on basis of core description. The most accurate values are obtained during underground geological mapping. Dividing the underground excavations into several parts might be required during mapping, so that variation of Q value is moderate in each section, meaning that such variation should not exceed the rock class variation index according to the reinforcement scheme. During excavation works single blasting often represents natural section for individual mapping. A variation may take place in sections of several meters, but for showing this variation histograms can be used during mapping.

Application of Internet of Things Technology in the Construction of Bored Pile Foundation in a High Altitude Environment

In order to solve the problem that the current geophysical method is difficult to locate in the mud of bored piles, the problem of effective exploration of karst caves at the bottom of piles, the author puts forward the application of Internet of Things technology and sonar technology in the construction of bored pile foundation in a high altitude environment. Combined with the propagation characteristics of sonar stress waves, a sonar detection method for karst caves at the bottom of bored piles is proposed, and a sonar detector for karst caves at the bottom of piles (JL-SONAR) and signal analysis software (PBCA) are developed. The JL-SONAR detector realizes the emission and acquisition of onsite sonar signals, and the PBCA software completes the analysis and arrangement of the detection data. This technology makes full use of the mud conditions of bored piles, the development of karst caves within 10 m of the pile bottom can be tracked and detected in the process of hole formation, which has the advantages of low cost, high speed, and high precision. Experimental results show that Project A has been drilled in multiple directions at the bottom of the pile, the rock cores on the west side of the pile bottom are mostly fragmented, the rock quality index RQD is 15–30, and the quality of the foundation rock at the pile bottom is extremely poor, which verify the results of sonar detection. No slurry leakage occurred in Project B after drilling, and the cores were mostly short columns. The rock quality index RQD was 75 to 90, and the quality of the foundation rock at the bottom of the pile was good, which verifies the results of sonar detection. Conclusion. The research results provide a new solution for karst cave exploration in karst areas, especially in liquid environments.

Polymer induced permeability reduction: The influence of polymer retention and porous medium properties

Polymer injection is broadly applied for enhanced oil recovery (EOR) in high crude oil viscosity and heterogeneous reservoirs. Although polymer flooding is very effective to decrease the mobility ratio towards favorable values and improve sweep efficiency, some side effects have to be considered including the risk of a severe polymer induced permeability reduction (PIPR) resulting from polymer/rock interaction either near the wellbore of in-depth of the reservoir. Many factors affect the degree of PIPR such as rock mineralogy, oil saturation, temperature, formation water salinity, rock pore structure, polymer type, polymer molecular weight, shear rates in the porous medium, and quality of the injection water (solid particles and oil droplets content). Accurate assessment of PIPR is very important for polymer selection to define the relative merits of polymer flooding for a certain reservoir and avoid polymer injectivity loss during field operations. A severe PIPR can be due to excessive polymer retention inside the reservoir rock, fluid incompatibility of polymer with formation fluids and rocks, clogging of pore throats (accumulation of large polymer molecules at the pore throat), shear thickening due to high shear rate in the near-wellbore area, Improper preparation of the polymer solution, and bad quality of the injection brine used to prepare the polymer solution.In this paper, coreflooding as an assessment technique for PIPR is reviewed and a new interpretation technique is presented to correlated the polymer retention to permeability reduction measured from coreflooding experiments. Coupling the polymer retention and rock quality index was very effective in matching the permeability reduction for data presented in the literature for sandstone and carbonate rock samples.PIPR should be considered as an important design characteristic during any polymer selection workflow. Although different techniques are presented earlier, most of them lack the ability for upscaling. An accurate assessment of PIPR using experimental data permits critical evaluation of polymer flow deeper in the reservoir and prediction of any injectivity problems as well as improving project design.

NMR-Supported Near-Wellbore Data Analysis to Improve the Petrophysical Evaluation of a Sandstone Reservoir Drilled With Barite-Enriched Water-Based Mud

The effect of mud filtrate and eventually fine migrations in high-quality rocks considerably influence the reading of NMR and conventional logs. It poses a challenge in extracting useful information that can contribute to the petrophysical evaluation of the virgin zone, e.g., the rock quality index. This is critical for determining the permeability index and the saturation exponent n required for accurate determination of the water saturation. The rock quality index is understood as the ratio between free-fluid volume (FFV) and bound-fluid volume (BFV). This is equivalent to the pore-throat radius, which dominates fluid flow, that is negatively affected by the fine migration. This is reflected in a reduction of the porosity filled by free fluid. The free-fluid porosity undercall is corrected with the help of deeper-reading density data. After this correction, the NMR-derived permeability in the flushed zone, probably damaged by migrated fines, is used to calculate the permeability in the virgin zone. The determination of the oil saturation in the flushed zone from NMR logs was done in two ways—first, by applying statistically based machine-learning tools, and secondly, by applying the widely used 2D-NMR method, diffusion vs. T2 maps. Comparative analysis of these two methods shows that both lead to consistent results. The water saturation in the flushed zone is estimated to be eight times higher than in the virgin zone because of the high degree of invasion.

Multiscale petrophysical characterization and flow unit classification of the Minnelusa eolian sandstones

Integration of petrophysical and geological information is critical to simulation of subsurface carbon storage (GCS). In this sense, two depositional facies were identified from the core description and well-log interpretation, namely massive (MS) and cross-bedded (CB) facies groups. Additionally, pore-scale characteristics were studied by a combination of techniques, e.g. Nuclear Magnetic Resonance (NMR) and mercury intrusion capillary pressure (MICP). Scanning electron microscope (SEM) and petrographic analyses show that the pore structure is dominantly controlled by the depositional environment and dolomite cementation. NMR-T2 distributions of MS and CB facies show triple and quadruple modes, respectively. In addition, MICP of high- and low-permeability MS facies samples, and their CB facies group mixtures were collected. The MS sample pore-throat size distribution is uni-modal, while the triple-modal characteristic of the mixtures indicates heterogeneous pore structures at the sub-core scale for CB facies. The reliably estimates of porosity and permeability for both facies groups via NMR techniques and the MLR (Multiple Linear Regression) approach demonstrate the applicability of these techniques to eolian sandstone. Moreover, irreducible water saturation via the T2-cutoff method correlates strongly with T2LM instead of porosity. Finally, the rock quality index and flow zone indicator were calculated based on Combinable Magnetic Resonance (CMR) log interpretations. This provides direct connection to properties measured in the well. Four flow units were classified for both facies groups. Results show that better reservoir quality with significant heterogeneities is observed in the CB facies. This study highlights the importance integrating multiscale petrophysical properties including facies, pore architecture and diagenesis analysis with core- to log-scale property characterization. The results herein validate our reservoir characterization and flow unit classification in eolian reservoirs.

Predicting Tunnel Squeezing Using the SVM-BP Combination Model

Rock squeezing has a large influence on tunnel construction safety; thus, when designing and constructing tunnels it is highly important to use a reliable method for predicting tunnel squeezing from incomplete data. In this study, a combination SVM-BP (support vector machine-back-propagation) model is proposed to classify the deformation caused by surrounding rock squeezing. We design different characteristic parameters and three types of classifiers (a SVM model, a BP model, and the proposed SVM-BP model) for the tunnel-squeezing prediction experiments and analyse the accuracy of predictions by different models and the influences of characteristic parameters on the prediction results. In contrast to other prediction methods, the proposed SVM-BP model is verified to be reliable. The results show that four characteristics: tunnel diameter (D), tunnel buried depth (H), rock quality index (Q) and support stiffness (K) reflect the effect of rock squeezing sufficiently for classification. The SVM-BP model combines the advantages of both an SVM and a BP neural network. It possesses flexible nonlinear modelling ability and the ability to perform parallel processing of large-scale information. Therefore, the SVM-BP model achieves better classification performance than do the SVM or BP models separately. Moreover, coupling D, H, and K has a significant impact on the predicted results of tunnel squeezing.

Prediction of rock mass quality index in the Q-system by multivariate regression using the most influential parameters

The extensive use of underground spaces is an index of development in countries. Choosing the right supporting system to achieve a safe and stable space is an important issue in tunnel construction. One of the methods used to classify rock masses is the Q-system. The Q-system depends on rock quality designation, joint strength, joint roughness, joint alteration, groundwater, and stress reduction factor, which are not always available. Sometimes it is not possible to access all the parameters of the Q-system due to time and cost. This paper aims to obtain the value of the rock quality index in the Q system using the most important parameters affecting it. Therefore, using the Pearson analysis method and SPSS software, the Q-system's most effective parameters are identified. In this regard, three models were selected to determine Q. The first and second models have three input parameters and one output parameter, and the third model has four input parameters and one output parameter. Using multivariate regression, a relationship to predict the Q-value using the most effective parameters is proposed. For this purpose, 140 experimental data were used, and 34 test data checked the results' accuracy. Determining the Q-value using three or four parameters instead of the six most effective parameters is the novelty of this paper. Comparing the results of the proposed relationship and the actual values obtained from the field measurements show that these results are in good agreement with each other. The results show that the second model with a correlation coefficient of 0.81 for the initial data and 0.8 for the test data and the root mean square error of 2.68 for the initial data and 2.55 for the test data has the best performance.

Petrophysical and petrographic characteristics of Barail Sandstone of the Surma Basin, Bangladesh

The Barail sandstone in the Surma Basin is a medium- to coarse-grained pinkish-colored rock exposed near the northeastern margin of Bangladesh. In this study, we evaluated the reservoir quality of the Barail sandstone based on its petrophysical and petrographic characteristics. Petrophysical analyses of outcropped samples showed that sandstones are made up of 16.48% porosity and 132.48 mD permeability. Sandstone density ranges from 1.94 g/cm3 to 2.37 g/cm3, with a mean value of 2.12 g/cm3, shown as moderately compacted sandstone. Integrated data such as bulk density, porosity, permeability, Rock Quality Index (RQI), Normalized Porosity Index (NPI), Flow Zone Indicator (FZI), compressive strength, etc. with their relationships indicate that Barail sandstone owing characters to become a good petroleum reservoir. The rock samples consisted mainly of quartz with an insignificant amount of rock fragments and plagioclase feldspar and are categorized as sub-arkose to sub-litharenite. The rock samples also contains lithic (andesine, microcline, muscovite, biotite, etc.) of granitic and gneissic fabric and some volcanic product like aguite, albite, andesine, garnet, spinel and ulvo-spinel indicating the source of nearby orogeny. The euhedral to subhedral shape of the quartz grain in a porphyritic texture, moderately sorted with a smaller amount of clay minerals indicating the moderately mature rock type. The iron oxide border around the quartz grain also indicates that the Barail sandstone was deposited under dry climatic condition.