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Optimizing or revising support systems are inevitable due to the existence of high probabilities and uncertainties in underground mines. For this aim, field data and measurements are the only scales available to truly measure the performance of these systems. This paper presents a site-dependent approach for optimizing/revising the applied rock bolt support systems and estimating the efficiency of installation operation based on the field data for underground coal mines. For this purpose, a comprehensive database containing field data from 128 different mining locations of an underground coal mine was taken into account. At first, the relationships between field data and measured displacement by installed tell-tale extensometers (TTD) in the roof to determine the effective parameters on the roof instability were analyzed. In the following, a method was introduced to calculate the weighting factor of the effective parameters in the system using coefficient of determination (R2) and sensitivity index (SI). The sensitivity index was developed for sensitivity analysis of all considered parameters on TTD under fair conditions. Then, a method entitled field data-based risk index (FDRI) model was presented to evaluate the risk of roof instability supported by rock bolt systems which was validated by the considered case study. Finally, a process was proposed to optimize/revise a rock bolt design using the results of FDRI model and introduced data-driven efficiency (DDE) theory. DDE theory was provided to relative estimation of the efficiency of the installation operation of rock bolts. This research presents a systematic method for selecting the effective parameters on an issue or hazard, determining their weight in the system and carrying out relevant ratings needed for risk assessment.

Rate of penetration management is a matter of importance in drilling operations and it has been used in some research studies. Although conventional approaches for rate of penetration management are mainly focused on analytical and semi-analytical models, several correlations have also been developed for this purpose. The history of rate of penetration management studies extends back more than half a century and ever since, research interest in this concept has never declined, making it a focus of industry and academic studies. In this article, some of these studies are reviewed to achieve a better understanding of rate of penetration management concept, its financial benefits and also its research capacities. This review reveals the most common rate of penetration management methods which applied analytical, semi-analytical and empirical correlations in different fields around the world. In other words, the main purpose of this study is to evaluate the research studies in which different models and correlations have been used as the main approach for rate of penetration management. Based on the results of this review, the best models for performing rate of penetration management studies and the best objective functions for optimization algorithms are introduced. Cited as: Najjarpour, M., Jalalifar, H., Norouzi-Apourvari, S. A review on half a century of experience in rate of penetration management: Application of analytical, semi-analytical and empirical models. Advances in Geo-Energy Research, 2021, 5(3): 252-273, doi: 10.46690/ager.2021.03.03

In practice, the shear strength of joints is not only determined by the roughness, but also by the degree of joint matching. Due to alteration or movement, the joints with equal roughness might be mismatched. The matching degree of the joint is a significant factor that controls the normal closure, aperture, stiffness, hydraulic conductivity, and shear strength of the jointed rock mass. Studying the shear behavior of natural mismatched rock joints obtained from core drilling with different morphological characteristics, degrees of matching, and irregular shapes is an issue that has gained less attention due to the lack of samples and difficulty to obtain data. This study investigates the shear behavior of mismatched joints obtained from core drilling. Here, a new criterion is developed based on 35 series of direct shear tests, Barton and other classical theories, three-dimensional morphological characteristics, and matching condition of joints. To validate the proposed criterion, the estimation accuracy of the available classical models is compared with that of the new model. It is observed that the new criterion could achieve higher prediction accuracy for mismatched joints. Moreover, it is found that the average estimation error of the predicted values is reduced by considering the matching conditions.

Underground gas storage (UGS) in depleted reservoirs affects caprock properties. The resemblance of Qom anhydrite outcrop with cutting obtained from a 2629 m depth was confirmed using X-ray diffraction (XRD) results and scanning electron microscope (SEM) tests. The anhydrite specimens unconfined compressive strength (UCS) changed under static cyclic loading conditions, and also petrophysical properties, such as porosity and permeability altered under 10, 20, and 30 cycles of loading. The magnitude of loading ranged from 30 to 43% of intact anhydrite UCS. The loading rate used for cyclic loading tests was 0.004 mm/s. The samples’ UCS decreased between 3.5 to 23.9% under cyclic loading conditions. The study of specimens computed tomography (CT) imaging with porosity and permeability indicated the growth of cracks, the cracks did not initiate in all lengths of specimens, hence the incremental increase in porosity did not increase the permeability of specimens. Even being under cyclic loads, the permeability of specimens stayed lower than 10-15 m2 (0.001 mD) but the trend of pressure versus time for measuring permeability shows a higher drop in pressure due to changes in permeability. The study indicated that the CT imaging results are in good accordance with petrophysical findings., Podzemno skladište plina smješteno u iscrpljenim ležištima utječe i na svojstva krovine. Sličnost između anhidrita Qom uzorkovanoga na površinskome izdanku te iz krhotina dobivenih s 2629 m dubine opisana je na temelju rezultata difrakcije x-zraka i skeniranja elektroničkim mikroskopom. Maksimalna jednoosna tlačna čvrstoća uzorka anhidrita mijenja se u uvjetima statičkih, promjenjivih, cikličkih opterećenja, pri čemu dolazi i do promjene petrofizičkih svojstava poput šupljikavosti i propusnosti, npr. tijekom 10, 20 i 30 ciklusa. Magnituda opterećenja bila je u rasponu od 30 do 43% maksimalne tlačne čvrstoće anhidrita, dok je intenzitet opterećenja kod cikličkih testova iznosio 0,004 mm/s. Kod ispitivanih uzoraka zamijećeno je smanjenje maksimalne tlačne čvrstoće u rasponu od 3,5 do 23,9% pri različitim uvjetima promjena opterećenja. Proučavanjem šupljikavosti i propusnosti uzoraka i snimki računalne tomografije vidljiv je porast broja pukotina u uzorku, pri čemu je uočeno da do stvaranja pukotina nije došlo uzduž cijeloga uzorka, kao što niti porastom šupljikavosti nije došlo do rasta propusnosti. Iako su uzorci bili izloženi cikličkim opterećenjima, propusnost uzoraka ostala je manja od 10-15 m2 (0,001 mD). Proučavanjem promjene tlaka u vremenu uočen je veći pad tlaka zbog promjene propusnosti uzorka. Rezultati istraživanja upućuju na dobro podudaranje podataka dobivenih snimkama računalne tomografije i rezultata petrofizičkih ispitivanja.

One problem that has always been a challenge for geotechnical engineers is construction on problematic and soft soils. Traditional methods of lime and cement stabilisation can be used to treat soil...

This study employs Interferometric Synthetic Aperture Radar (InSAR) data sets to monitor the surface deformation of the Nasr-Abad buried salt diapir in the Central Basin of Iran. The Nasr-Abad salt diapir is one of the largest buried salt diapir in Iran and could be ideal site for oil/gas storage and industrial waste disposal. Forty ENVISAT Advanced Synthetic Aperture Radar (ASAR) images acquired during 2003–2010 were used to monitor surface activities of this diapir and its surrounding regions in that time window. One hundred and one interferograms were generated from both descending and ascending orbits by applying the Small-BAseline Subset (SBAS) method. Tropospheric artefacts in the displacement interferograms were mitigated using the power law correction method in TRAIN software. A time series of line-of-sight (LOS) displacements on the residual cap of Lower Red Formation above the buried diapir was also generated as well as the area. Finally, the data for temperature, precipitation, and tidal forces were correlated with the time-series displacement results of four points A, B, C, and D that located on the residual cap. Our analyses of our data indicate that surface above the diapir and an area of about 28 square kilometres subsided with maximum LOS velocity of about 7 mm/year for ascending images and 5 mm/year for descending images. Comparing the temperature and precipitation data with the time-series of displacement confirmed that they correlated with the same seasonal effects. Monitoring the activities of the Nasr-Abad region over 7 years shows that the region of surface subsidence is confined to the area that relates directly to the geological structures of the region.

One of the most important problems that the drilling industry faces is drilling cost. Many factors affect the cost of drilling. Increasing drilling time has a significant role in increasing drilling costs. One of the solutions to reduce drilling time is to optimize the drilling rate. Drilling wells at the optimum time will reduce the time and thus reduce the cost of drilling. The drilling rate depends on different factors, some of which are controllable and some are uncontrollable. In this study, several smart models and a correlation were proposed to predict the rate of penetration (ROP) which is very important for planning a drilling operation. 5040 real data points from a field in the South of Iran have been used. The ROP was modelled using Radial Basis Function, Decision Tree (DT), Least Square Vector Machine (LSSVM), and Multilayer Perceptron (MLP). Bayesian Regularization Algorithm (BRA), Scaled Conjugate Gradient Algorithm and Levenberg–Marquardt Algorithm were employed to train MLP and Gradient Boosting (GB) was used for DT. To evaluate the accuracy of the developed models, both graphical and statistical techniques were used. The results showed that DT-GB model with an R2 of 0.977, has the best performance, followed by LSSVM and MLP-BRA with R2 of 0.971 and 0.969, respectively. Aside from that, the proposed empirical correlation has an acceptable accuracy in spite of simplicity. Moreover, sensitivity analysis illustrated that depth and pump pressure have the highest effects on ROP. In addition, the leverage approach approved that the developed DT-GB model is valid statistically and about 1% of the data are suspected or out of the applicability domain of the model.

This study employs interferometric synthetic aperture radar (InSAR) data sets to monitor the surface deformation of the Nasr Abad buried salt diapir in the Central Basin of Iran. The Nasr A...

A new approach for prediction of face advance rete (FAR) prior to mining operation and determination of the operation efficiency after mining operation in retreat longwall mining panel is presented based upon the concepts of rock engineering system (RES). For this purpose, six longwall panels considered in Parvadeh-I coal mine. Seven major effective parameters on FAR was selected including coal mine roof rating, gas propagation, safety factor of longwall face, ratio of joint spacing to cutting depth at longwall face, longwall face inclination, panel width, floor rock mass rating. To performance evaluation of the presented model, the relationship between the average vulnerability indexes of advance operation with FAR was determined in considered panels with coefficient of determination (R 2) equal to 0.884 that indicate relatively acceptable correlation and compatibility. Investigations of the research indicated that it is possible to determine the actual operation efficiency under fair conditions by a RES-based model. The inevitable reduction of FAR for each longwall panel was determined by presented model that the difference amount between the maximum possible practical face advance rate (FARmpp) and recorded actual face advance rate (FARa) indicate the operation efficiency. Applied approach in this paper can be used to prediction of FAR in retreat longwall mining panel for same conditions that can have many benefits, including better and more accurate planning for the sales market and mine operation. Also, presented method in this paper can be applied as a useful tool to determination of actual operation efficiency for other sections and extraction methods in coal mines.

Rock failure mechanism is one of the most important issues in rock mechanics engineering which plays a key role in the stability analysis of various structures. Therefore, different failure criteria have been proposed to understand the failure mechanism of rocks. One of the most commonly used rock failure criteria is the Hoek-Brown criterion, in which there is a parameter called mi, which is very important to the response provided by this criterion. Due to the importance of conducting extensive studies on this parameter, in this current research, by performing a series of experimental triaxial compressive strength test and numerical simulating in PFC-2D code, the effect of the Hoek-Brown constant mi on the failure mechanism and crack growth of different rocks has been studied. Based on the results of this study, it was found that the effect of parameter mi on the failure mechanism of different rocks varied according to the type of rocks, and the greatest effect of this parameter was on the peak strength of rocks. In addition, it was found that under higher lateral pressures, there are less destructive cracks in rocks, and as a result, they show more ductile behaviour., Mehanizam loma stijene jedno je od najvažnijih pitanja u mehanici i inženjerstvu stijena te je ključno u analizi stabilnosti raznih struktura. Za različite kriterije loma predloženi su različiti mehanizmi odgovorni za takav proces. Jedan od najčešće korištenih kriterija kojim se opisuje lom stijena jest Hoek-Brownov kriterij, u kojemu postoji varijabla zvana mi, koja je vrlo važna kod ocjene tim kriterijem. Zbog važnosti provođenja opsežnih studija o prilagođavanju te varijable u prikazanim istraživanjima ona je određena izvođenjem serije eksperimentalnih ispitivanja troosne tlačne čvrstoće i numeričke simulacije u PFC-2D kodu. Time je istražen učinak vrijednosti mi na lom stijene i rast pukotina različitih stijena. Na temelju rezultata utvrđeno je kako je utjecaj varijable mi na lom različitih vrsta stijena varijabilan, a najveći je učinak na vršnu čvrstoću stijena. Također, utvrđeno je da su pod većim bočnim pritiscima razarajuće pukotine u stijenama manje (uspoređeno s prethodnim testom), a kao rezultat pokazuju više duktilno ponašanja.

Rocks are formed from particles and the interaction between those particles controls the behaviour of a rock’s mechanical properties. Since it is very important to conduct extensive studies about the relationship between the micro-parameters and macro-parameters of rock, this paper investigates the effects of some micro-parameters on strength properties and the behaviour of cracks in rock. This is carried out by using numerical simulation of an extensive series of Uniaxial Compressive Strength (UCS) and Brazilian Tensile Strength (BTS) tests. The micro-parameters included the particles’ contact modulus, the contact stiff ness ratio, bond cohesion, bond tensile strength, the friction coefficient and the friction angle, and the mechanical properties of chromite rock have been considered as base values of the investigation. Based on the obtained results, it was found that the most important micro-parameters on the behaviour of rock in the compressive state are bond cohesion, bond tensile strength, and the friction coefficient. Also, the bond tensile strength showed the largest effect under tensile conditions. The micro-parameter of bond tensile strength increased the rock tensile strength (up to 5 times), minimized destructive cracks and increased the corresponding strain (almost 2.5 times) during critical stress., Svaka je stijena stvorena od čestica čijim se međudjelovanjem određuju njezina mehanička svojstva. Budući da je vrlo važno provesti opsežne studije o povezanosti mikroparametara i makroparametara stijene, u ovome su radu istraživani učinci nekih mikroparametara na svojstva čvrstoće i ponašanje pukotina stijene numeričkim simulacijama jednoosne tlačne čvrstoće (UCS) i brazilske vlačne čvrstoće (BTS). Ispitivani mikroparametri uključivali su kontakt čestica, omjer kontaktne krutosti, koheziju veze, vlačnu čvrstoću, koeficijent trenja i kut trenja, a mehanička svojstva stijene bogate kromitom bile su osnovne vrijednosti ispitivanih mikroparametara. Utvrđeno je kako su najvažniji mikroparametri na ponašanje stijene kod tlačenja kohezija veze, vlačna čvrstoća veze i koeficijent trenja. Također, vlačna čvrstoća ima najveći učinak u vlačnim uvjetima. Ovaj mikroparametar povećava vlačnu čvrstoću (do 5 puta), minimalizira destruktivne pukotine i povećava odgovarajuće naprezanje (gotovo 2,5 puta) pri kritičnome naprezanju.

Successful acid fracturing operation could reduce formation damage and increase production rate in a carbonate reservoir. Final fracture conductivity is a critical parameter that determines the success of the acid fracturing operation. A wide range of parameters could affect the fracture conductivity, making its prediction quite difficult. The effect of contact time, type of acid, and rock type has been evaluated before. In this study, however, the effect of concentration of hydrochloric acid (HCl), rock strength, injection rate, acid type, and rock type on the conductivity of the fracture was investigated. Based on our observations, for calcite rock types, greater fracture conductivities were achieved by using HCl 15% compared to HCl 7%. For dolomite, the result was completely different and lower concentration of HCl had better outcome. Depending on the type of acid that was used, different results achieved for rocks with different strength. When low concentration of HCl, HCl 7%, was used as an injection fluid, dolomite with higher strength had better conductivity. However, for strong acid, HCl 15% and emulsified acid, the best results were obtained for calcite with low strength. Injection rates resulted in two different outcomes. At low concentration, the injection rate of 4 ml/min created better fracture conductivity while at high concentration, the injection rate of 10 ml/min generated better results, when injection fluid was HCl. As for emulsified acid, higher injection rate resulted in proper conductivity. In most cases, emulsified acid had better final fracture conductivity. Based on experimental results obtained, three models for three different acid types were developed. The conductivity of rocks after acid etching was predicted based on injection rate, rock strength, and closure stress. Statistical and graphical analysis proved that developed models have a good performance.

Rate of penetration (ROP) management is a matter of importance in drilling operations and it has been considered in different studies. Different machine learning methods such as simple and optimized artificial neural networks (ANNs), support vector machines (SVMs), fuzzy logic (FL) or adaptive neuro-fuzzy inference system (ANFIS), ensemble methods of machine learning and meta-heuristic algorithms have been used for this purpose so far. In this article, some of the studies by using these methods as the main approach for ROP management are reviewed to achieve a better understanding of this concept, its economic benefits and also its research capacities. Results indicate that ANNs are the most popular machine learning method in ROP management, while simple ANNs excel the modified types in this regard. Still, modified ANNs outperform simple ones in terms of prediction accuracy, but as ANNs fall short in superior prediction performance, other machine learning approaches of ROP management such as linear regression (LR), random forest (RF) and gradient boosting method (GBM) have compensated this shortcoming and proved their efficiency and applicability.

Rate of penetration (ROP) management is a matter of great importance in drilling operations, therefore it has been considered in different field management projects and research studies. In this way, several drilling technologies and concepts such as managed pressure drilling (MPD) and mechanical specific energy (MSE) have found their applications in this category. Moreover, some studies have used the bit management approach, while some other authors have developed special computer software and expert systems for this purpose. The history of ROP management studies reaches to more than half a century. In this article, some of these studies are reviewed to achieve a better understanding of this concept, its economic benefits and also its research capacities. Results indicate that among different methods which are discussed in this paper, bit management have the most field applications in ROP management studies.

This study presents a model based on rock engineering systems (RES) to evaluate the risk of roof falls and determine damaged regions, using recorded roof falls, prior to mining with a retreat from a longwall face. In this regard, a case study was considered to examine the model. The results showed that the level of determined risk has an acceptable correlation with the special roof fall (SRF), with R-squared value (R2) equal to 0.792 for all estimated vulnerability indexes (VIs) in considered longwall panels. By investigating and comparing the evaluated values of VI in considered panels and their corresponding recorded roof falls, damaged regions were distinguished from undamaged regions. Based on these investigations, four classes including safe, moderate, danger, and critical regions were determined to identify the safe and damaged regions prior to the mining operation. The results of the research showed that the identification of damaged regions is feasible to provide a detailed operation plan to control roof falls in longwall mining faces through the developed approach. The RES-based model could be used for the same conditions and the presented methodology could be applied to other parts in underground coal mines., U ovome radu prikazan je model utemeljen na sustavima inženjerskih stijena za procjenu rizika od urušavanja (pada) krovine i određivanje oštećenih područja primjenom zabilježenih padova krovine, prije rudarenja metodom širokoga čela. Razmatrana je studija slučaja koja je ispitala model. Rezultati su pokazali da je razina utvrđenoga rizika imala relativno prihvatljivu korelaciju i kompatibilnost s posebnim padom krovine (PPK), s koeficijentom determinacije (R2) jednakim 0,792 za sve procijenjene indekse ranjivosti (IR) u razmatranim područjima rudarenja. Istražujući i uspoređujući procijenjene vrijednosti indeksa ranjivosti na razmatranim područjima i pripadajućim zabilježenim padovima krovine, otkrivena su oštećena područja unutar onih neoštećenih. Na temelju tih istraživanja izvedene su četiri klase: sigurno, umjereno, opasno i kritično područje, radi identificiranja sigurnih, umjereno opasnih i kritičnih područja prije rudarskih operacija. Rezultati istraživanja pokazali su da je identificiranje štetnih područja razvijenim pristupom prikladno za izradu detaljnoga operativnoga plana za kontrolu pada krovine na širokom čelu. Konačno, model temeljen na inženjerskim sustavima stijena može se koristiti i drugdje za iste uvjete, a predstavljena metodologija može se primijeniti i na ostale dijelove podzemnih rudnika ugljena.

Presence of rock bridges (RB) in natural non-persistent discontinuity sets is an effective factor on the stability of rock structures. Investigations show that the bearing capacity of jointed rocks is changed with variation of different joint parameters. Therefore, in order to investigate the effect of parameters such as contact area and number of rock bridges, normal load, angle, length, and number of joints on shear strength of non-persistent rock joints and also to recognize the interaction of these parameters on the mechanical behavior of joints, experimental design methods of Taguchi and central composite design (CCD) were used for the sample generation, testing and numerical modeling. The effective parameters on the shear strength of jointed samples were obtained based on the previous studies. Using the Taguchi method, 16 samples were tested at CNL condition and the effect of parameters such as normal stress, number, and area of rock bridges was investigated. To evaluate other joints parameters, 30 experiments were designed using CCD method and examined using numerical modeling. Using the analysis of variance (ANOVA), it was found that the obtained models are statistically significant. According to the results of ANOVA, the area of rock bridges and the angle of joints showed the highest and the lowest effect on shear strength of coplanar and non-coplanar jointed samples, respectively. The results displayed that the dominant failure for planar non-persistent joints is pure shear and a combination of tensile and shear cracks is created from the both tips of adjacent joints. Moreover, it was found that the dominant failure of non-coplanar joints is the combination of shear and tension. Bonded particle model (BPM) and smooth joint model (SJM) were also applied for numerical modeling. A new method was considered for applying SJ to the models, which solved the interlocking problem during the test.

In presence of difficult conditions in coal mining roadways, an adequate stabilization of the excavation boundary is required to ensure a safe progress of the construction. The stabilization of the roadways can be improved by fully grouted rock bolt, offering properties optimal to the purpose and versatility in use. Investigations of load transfer between the bolt and grout indicate that the bolt profile shape and spacing play an important role in improving the shear strength between the bolt and the surrounding strata. This study proposes a new analytical solution for calculation displacement and shear stress in a fully encapsulated rock bolt in jointed rocks. The main characteristics of the analytical solution consider the bolt profile and jump plane under pull test conditions. The performance of the proposed analytical solution, for three types of different bolt profile configurations, is validated by ANSYS software. The results show there is a good agreement between analytical and numerical methods. Studies indicate that the rate of displacement and shear stress from the bolt to the rock exponentially decayed. This exponential reduction in displacement and shear stress are dependent on the bolt characteristics such as: rib height, rib spacing, rib width and grout thickness, material and joint properties. Keywords: Fully grouted bolt, Jointed rock, Displacement, Shear stress

The floor failure at longwall face decreases productivity and safety, increases operation costs, and causes other serious problems. In Parvadeh-I coal mine, the timber is used to prevent the puncture of powered support base into the floor. In this paper, a rock engineering system (RES)-based model is presented to evaluate the risk of floor failure mechanisms at the longwall face of E 2 and W 1 panels. The presented model is used to determine the most probable floor failure mechanism, effective factors, damaged regions and remedial actions. From the analyzed results, it is found that soft floor failure is dominant in the floor failure mechanism at Parvadeh-I coal mine. The average of vulnerability index (VI) for soft, buckling and compressive floor failure mechanisms was estimated equal to 52, 43 and 30 for both panels, respectively. By determining the critical VI for soft floor failure mechanism equal to 54, the percentage of regions with VIs beyond the critical VI in E 2 and W 1 panels is equal to 65.5 and 30, respectively. The percentage of damaged regions showed that the excess amount of used timber to prevent the puncture of weak floor below the powered support base is equal to 4,180,739 kg. RES outputs and analyzed results showed that setting and yielding load of powered supports, length of face, existent water at face, geometry of powered supports, changing the cutting pattern at longwall face and limiting the panels to damaged regions with supercritical VIs could be considered to control the soft floor failure in this mine. The results of this research could be used as a useful tool to identify the damaged regions prior to mining operation at longwall panel for the same conditions.

Understanding the interaction between rock bolts and underground rock movement is critical for safe and cost-effective underground excavation design. Although early research on this subject involved a balance of theoretical analysis and field measurement, the current work focused on analytical and numerical studies. The present study aimed to study fully grouted rock bolt in Tabas Coal Mine using numerical and instrumentation methods. Tabas Coal Mine is the first fully mechanized coal mine in Iran, producing 1.5 million tons of coal per year. The mine extracts coal by both longwall and room and pillar methods. The roadways have a rectangular profile of 4.5 m width and 3.5 m height. The field investigations and geotechnical characteristics of rocks showed that the rock masses are weak, requiring a suitable support system. The roadway is intersected by a major fault zone. For the designed roadway, four patterns (two types of bolt with transfer load capacity of 180 and 195 kN) were considered. FLAC analysis showed that 13 bolt 2.4 m with 2 NO flexi bolt 4-m patterns were better than other patterns within the faulted zone. Assessing the optimum pattern through instrumentation, there was compromise between the results of numerical modeling with instrumentation reading such as telltales, sonic extensometer, and strain gauge rock bolt. Thus, there was an inspiring agreement between numerical and field methods.

Rate of penetration (ROP) is one of the most important parameters in reducing drilling expenditure. In this paper, a ROP management study has been conducted for a well in Southwest of Iran. As a part of this study, the best approach for ROP prediction was determined by comparing the performance of several methods and particle swarm optimization (PSO) algorithm was implemented for optimization of ROP. This paper highlights the effects of formation thickness and the magnitude of working data-set on the performance of different algorithms which are being used for ROP management studies, especially in horizontal and inclined wells. This topic has special importance, when the results show a massive difference in thin and thick formations for some ROP prediction methods. Comparing the results of different ROP prediction methods showed that hybrid Bingham model has the best performance in ROP prediction; only if a powerful mathematical tool like trust-region method is being used for the determination of its unknown coefficients. This superiority was not generalized in all individual formations and there were different results in the cases of thin and thick formations; so, application of the bag-of-algorithms strategy by using the most accurate method in each formation is suggested for the prediction of ROP. Performing this ROP management project resulted in the prediction of ROP with a total relative error of 13.59% and also 48.30% improvement in ROP.

Wellbore instability is a big challenge in shale formations. The objective of this study is to investigate the effectiveness of a natural additive as a shale inhibitor. The capability of this additive for reducing ion movement into shale and plugging its pore throats has been tested and compared with salts and nano particles. The ions and water movement into shale and resultant swelling was measured by modified gravimetric, swelling and modified immersion tests. The results showed that using Henna extract could reduce the ion and water movement into shale. In addition, the results of pore pressure tests showed that 3 wt % of Henna extract are more effective than nano particles and could completely plug the pore throats of shale while the mud rheological properties are still maintained. The findings of this study show that the Henna extract could be considered as a cost-effective and an environmentally-friendly shale inhibitor.

The purpose of this study is to investigate the role of bolt profile configuration in load transfer capacity between the bolt and grout. Therefore, five types of rock bolts are used with different profiles. The rock bolts are modeled by ANSYS software. Models show that profile rock bolt T3 and T4 with load capacity 180 and 195 kN in the jointed rocks, are the optimum profiles. Finally, the performances of the selected profiles are examined in Tabas Coal Mine by FLAC software. There is good subscription between the results of numerical modeling and instrumentation reading such as tells tale, sonic extensometer and strain gauge rock bolt. According to the finding of this study, the proposed pattern of rock bolts, on 7 + 6 patterns per meter with 2 flexi bolt (4 m) for support gate road. Keywords: Fully grouted rock bolts, Numerical modeling, Load transfer, Bolt profile

This study proposes a new analytical solution to predict displacement of a fully grouted rock bolt intersected by single rock joint. The main characteristics of the analytical model, consider the bolt profile and joint movement under pull test condition. The anchorage capacity of fully grouted bolts has been studied for many years; however, the bolt profile and its effect on bolt shear resistance are poorly understood. Investigations of load transfer between the bolt and grout indicate that the bolt profile shape and spacing play an important role in improving the shear strength between the bolt and the surrounding strata. Rock displacement is a sum of elastic part and a jump part due to the presence of joints planes. The performance of the proposed analytical model is validated by experimental method and comparison with numerical modeling. The results showed that there is a promising agreement between analytical and numerical methods. Studies indicate that the displacement rate between the bolt and the rock declines exponentially. Which is dependent on the bolt characteristics such as: rib height, rib spacing, rib width and thickness grout, material and joint properties.

In this paper a geometric computational model (GCM) has been developed for calculating the effect of longwall face on the extension of excavation-damaged zone (EDZ) above the gate roadways (main and tail gates), considering the advance longwall mining method. In this model, the stability of gate roadways are investigated based on loading effects due to EDZ and caving zone (CZ) above the longwall face, which can extend the EDZ size. The structure of GCM depends on four important factors: (1) geomechanical properties of hanging wall, (2) dip and thickness of coal seam, (3) CZ characteristics, and (4) pillar width. The investigations demonstrated that the extension of EDZ is a function of pillar width. Considering the effect of pillar width, new mathematical relationships were presented to calculate the face influence coefficient and characteristics of extended EDZ. Furthermore, taking GCM into account, a computational algorithm for stability analysis of gate roadways was suggested. Validation was carried out through instrumentation and monitoring results of a longwall face at Parvade-2 coal mine in Tabas, Iran, demonstrating good agreement between the new model and measured results. Finally, a sensitivity analysis was carried out on the effect of pillar width, bearing capacity of support system and coal seam dip.

Survey properties of soil and rock mass have always been associated with uncertainty. Hence, the behavior of the soil or rock cannot be investigated specifically by choosing a value specified for these properties. One of the most common systems for studying properties of rock mass is the rock mass classification system (RMR) which was developed by Bieniawski. In this system the input parameters are divided into several classes, and each class has particular rating. In this system, because of uncertainties of the input parameters, determining the definite boundary between the classes and assigning a specified value to a particular class is difficult, so when the input parameters are close to the boundary between the classes, the class rating with certainity is not decided. The aim of this paper is to propose a hybrid nonlinear Chaotic and Neuro-Fuzzy system modeling for the basic RMR system uncertainty based on continuous functions. This model also proves the theory of Bieniawski that is based on nonlinear systems by using chaos theory and mathematical relations. The main advantage of proposed model is to directly predict output of RMR system classification system without considering the input parameters so that it leads to better results and a higher level of prediction rock quality.

Geological sequestration of carbon dioxide is a mitigation method for reducing greenhouse gas emissions to the atmosphere. Success and safety of a CO 2 sequestration operation is strongly dependent on the mechanical stability of the caprock overlying the storage reservoir. Subsurface CO 2 injection results in a pore pressure increase and thereby a decrease of the effective stresses, which may lead to caprock failure and subsequent CO 2 leakage. In this study, a three-dimensional geomechanical finite element model was built by using Abaqus software to investigate the geomechanical effects of CO 2 injection on the caprock and to estimate the risk of caprock failure. The CO 2 injection induced pore pressure increase, vertical displacement of the caprock, and the effective stress decrease have been investigated. The results show that the caprock remains stable during the 10-year injection period under the considered conditions. Through quantitative sensitivity analysis, the effects of the input parameters are ranked. CO 2 injection rate and initial stress state were found to have the most significant impact on the caprock failure tendency. Results of the numerical model were also validated against analytical solutions.

The purpose of this study was to investigate the effect of bolt profile on load transfer mechanism of fully grouted bolts in jointed rocks using analytical and numerical methods. Based on the analytical method with development of methods, a new model is presented. To validate the analytical model, five different profiles modeled by ANSYS software. The profile of rock bolts T3 and T4 with load transfer capacity, respectively 180 and 195 kN in the jointed rocks was selected as the optimum profiles. Finally, the selected profiles were examined in Tabas Coal Mine. FLAC analysis indicates that patterns 6+7 with 2NO flexi bolt 4 m better than other patterns within the faulted zone. Keywords: Fully grouted bolt, Load transfer mechanism, Jointed rocks, Analytical and numerical methods

To determine the bubble point oil formation volume factor (Bob), which is one of the most important PVT properties, several correlations have been proposed for different regions. None of the correlations could be applied as a universal correlation due to regional changes in crude oil compositions and properties. In this paper, a new correlation is proposed to predict the Bob for Middle East crudes. Genetic Algorithm (GA) was used as the dominant tool for development of the new correlation. A total of 429 data sets of different crude oils from Middle East reservoirs were used. These Data include Bob and conventional PVT properties. Among those, 286 data sets as training data and 143 data sets as test data were randomly selected for constructing the correlation and for correlation validation, respectively. The measured mean squared errors (MSEs) of predicted Bob from the correlation in the test data were 0.0029 and the correlation coefficient (R2) between predicted values from the model and experimental values in the test data was 0.9646. These results show a very good agreement with experimental data and are more accurate for Middle East crudes than those of all existing empirical correlations.

Summary In this study, a new analytical model, which is computationally lower in cost than current numerical methods, is presented to calculate the radius of the plastic zone around the borehole in underbalanced drilling (UBD) to prevent borehole instability. With this model, it is also possible to analytically calculate the optimal drilling-mud weight, which is the amount of mud weight with no plastic zone. The presented model is based on the Mouhr-Coulomb failure criterion. The model can be used in both vertical and inclined wells and in poroelastic formations with anisotropic horizontal stresses. Predictions from the model provide a reasonable match to the field data and numerical solution results.

Rock mass rating system (RMR) is based on the six parameters which was defined by Bieniawski (1989) [1]. Experts frequently relate joint and discontinuities and ground water conditions in linguistic terms with rough calculation. As a result, there is a sharp transition between two modules which create doubts. So, in this paper the proposed weights technique was applied for linguistic criteria. Then by using the fuzzy inference system and the multi-variable regression analysis, the accurate RMR is predicted. Before the performing of regression analysis, sensitivity analysis was applied for each of Bieniawski parameters. In this process, the best function was selected among linear, logarithmic, exponential and inverse functions and finally it was applied in the regression analysis for construction of a predictive equation. From the constructed regression equation the relative importance of the input parameters can also be observed. It should be noted that joint condition was identified as the most important effective parameter upon RMR. Finally, fuzzy and regression models were validated with the test datasets and it was found that the fuzzy model predicts more accurately RMR than regression models. Keywords: Fuzzy set, Fuzzy inference system, Multi-variable regression, Rock mass classification

Wellbore stability problems are known to cost the oil and gas industry billions of dollars each year. However, these costs can be significantly reduced through the application of comprehensive geomechanical models. This paper is relevant and is appropriate in the oil and gas industry. The objective of this paper is the comparison of four rock failure criteria, named the Mohr–Coulomb, Mogi–Coulomb, Modified Lade and Tresca yield criterion and to apply them to determine the optimum drilling direction and mud pressure. The stability models has been applied to a well located in Iran oil field and leads to easily computed expression for the critical mud pressure required to maintain wellbore stability. Then the finite difference method was used to show the validation and accuracy of predicted mud pressure and investigate the wellbore stability in different states of vertical, horizontal and deviated. The results showed that the Mohr–Coulomb and Tresca criteria estimate the highest minimum mud pressure required for wellbore stability while the Mogi–Coulomb and the Modified Lade criteria estimate the lowest minimum mud pressure. Nevertheless, the mud pressures predicted by all these four criteria are acceptable and can be used.

There are numerous difficulties involved in drilling operations of an oil well, one of the most important of them being well control. Well control systems are applied when we have irruption of liquids or unwanted intrusion of the reservoir's liquid (oil, gas or brine) into the well, during drilling when the pressure of well fluid column is less than formation pressure, and the permeability of the reservoir has a value that is able to pass the liquid through. For this purpose, a variety of methods including Driller, wait and weight, and the concurrent methods were used to control the well at different drilling sites. In this study, we investigate the optimum method for well control using a fussy method based on many parameters, including technical factors (mud weight, drilling rate, blockage of pipes, sensitivity to drilling network changes, etc.) and security factors (existence of effervescent mud, drilling circuit control, etc.), and cost of selection, which is one of the most important decisions that ar...

The rock engineering classification system is based on six parameters defined by Bieniawski [5] , who employed parallel sets of linguistic and numerical criteria that were acknowledged to influence the behaviour of rock masses and the stability of rock structures. Consequently, experts frequently relate rock joints and discontinuities as well as ground water conditions in linguistic terms, with rough calculations. Recently, intelligence system approaches such as artificial neural network (ANN) and neuro-fuzzy methods have been used successfully for time series modelling. Using neuro-fuzzy approaches, which enable the information that is stored in trained networks to be expressed in the form of a fuzzy rule base, would help to overcome this issue. This paper presents the results of a study of the application of neuro-fuzzy methods to predict rock mass rating. We note that the proposed weights technique was applied in this process. We show that neuro-fuzzy methods give better predictions than conventional modelling approaches.

Over the years, accurate prediction of pressure drop has been of vital importance in vertical multiphase flowing oil wells in order to design an effective production string and optimum production strategy selection. Various scientists and researchers have proposed correlations and mechanistic models for this purpose since 1950, most of which are widely used in the industry. But in spite of recent improvements in pressure prediction techniques, most of these models fail to provide the desired accuracy of pressure drop, and further improvement is still needed. This study presents an artificial neural network (ANN) model for prediction of the bottomhole flowing pressure and consequently the pressure drop in vertical multiphase flowing wells. The model was developed and tested using field data covering a wide range of variables. A total of 413 field data sets collected from Iran fields were used to develop the ANN model. These data sets were divided into training, validation and testing sets in the ratio of 4:1:1. The results showed that the research model significantly outperforms all existing methods and provides predictions with higher accuracy, approximately 3.5% absolute average percent error and 0.9222 correlation coefficient.