Oil Reservoir Permeability Estimation from Well Logging Data Using Statistical Methods (A Case Study: South Pars Oil Reservoir)

Permeability is a key parameter that affects fluids flow in reservoir and its accurate determination is a significant task. Permeability usually is measured using practical approaches such as either core analysis or well test which both are time and cost consuming. For these reasons applying well logging data in order to obtaining petrophysical properties of oil reservoir such as permeability and porosity is common. Most of petrophysical parameters generally have relationship with one of well logged data. But reservoir permeability does not show clear and meaningful correlation with any of logged data. Sonic log, density log, neutron log, resistivity log, photo electric factor log and gamma log, are the logs which effect on permeability. It is clear that all of above logs do not effect on permeability with same degree. Hence determination of which log or logs have more effect on permeability is essential task. In order to obtaining mathematical relationship between permeability and affected log data, fitting statistical nonlinear models on measured geophysical data logs as input data and measured vertical and horizontal permeability data as output, was studied. Results indicate that sonic log, density log, neutron log and resistivity log have most effect on permeability, so nonlinear relationships between these logs and permeability was done

A Case Study of High School Chinese as a Foreign Language Blended Program

This qualitative case study investigated a Chinese as a foreign language program composed of three different instructional modes: synchronous instruction with videoconferencing technology, asynchronous instruction with online tutorials, and physically co-located face-to-face instruction. The study adopted Larry Cuban's multi-layered curriculum framework and investigated the four curriculum layers within the blended program: intended curriculum, taught curriculum, learned curriculum, and tested curriculum. This research utilized interviews, observation, and document analysis as the instruments in data collection. The participants consisted of one administrator, eight language teachers, four facilitators and twelve high school students. In addition to teaching site observation, the researcher also traveled to four remote school sites to observe how the curriculum was learned from the students' perspective. The results of the study indicated that although the intended curriculum reveals the administrator's ideal picture of blended learning design and defines what teachers should teach and what students should learn in each instructional delivery mode, the actual implementation process of blended learning is much more complex. The findings of the study showed that language teachers' specific operation of the daily lessons in a blended context and students' actual learning experiences at the remote sites can be influenced by many other variables; these variables lead the intended curriculum into different versions between the classes of the taught curriculum, learned curriculum and tested curriculum. Therefore, technology integration should not only be focused on the design of the external layer of the curriculum (the intended curriculum), but should also be focused on the implementation through the rest of the curriculum layers

Relations between Texture Coefficient and Energy Consumption of Gang Saws in Carbonate Rock Cutting Process

Texture coefficient is one of the most influential parameters in rock engineering specifications in various projects including drilling, cutting, permeability of all-section drilling devices, etc. Meanwhile, investigating and forecasting the energy consumption of saw cutters are one of the most important factors in estimating the cutting costs. The present study aims to investigate the relationship between rock texture characteristics and the amount of energy consumption of the gang saw machine in the process of cutting carbonate rocks. To evaluate the effects of texture on the rocks' engineering specifications, 14 carbonate rock samples were studied. A microscopic thin section was made from each rock specimen. Then, five digital images were taken from each section under a microscope and the values of area, environment, the largest diameter and the smallest diameter of all grains in each image were determined. Using these specifications, the coefficient of texture of all rock samples was calculated and the relationship between the texture coefficient and the rate of energy consumption of the gang saw machine was investigated for the studied samples. The study results indicated that there was a significant relation between the texture coefficient and energy consumption rate in the three groups of carbonate rocks

Assessment of risks of tunneling project in Iran using artificial bee colony algorithm

The soft computing techniques have been widely applied to model and analyze the complex and uncertain problems. This paper aims to develop a novel model for the risk assessment of tunneling projects using artificial bee colony algorithm. To this end, the risk of the second part of the Emamzade Hashem tunnel was assessed and analyzed in seven sections after testing geotechnical characteristics. Five geotechnical and hydrological properties of study zone are considered for the clustering of geological units in front of tunneling project including length of tunnel, uniaxial compressive strength, rock mass rating, tunneling index Q, density and underground water condition. These sections were classified in two low-risk and high-risk groups based on their geotechnical characteristics and using clustering technique. It was resulted that three sections with lithologies Durood Formation, Mobarak Formation, and Ruteh Formation are placed in the high risk group and the other sections with lithologies Baroot Formation, Elika Formation, Dacite tuff of Eocene, and Shear Tuff, and Lava Eocene are placed in the low risk group. In addition, the underground water condition and density with 0.722 and 1 Euclidean distances have the highest and lowest impacts in the high risk group, respectively. Therefore, comparing the obtained results of modelling and actual excavation data demonstrated that this technique can be applied as a powerful tool for modeling risks of tunnel and underground constructions

Assessing the system vibration of circular sawing machine in carbonate rock sawing process using experimental study and machine learning

Predicting the vibration of the circular sawing machine is very important in examining the performance of the sawing process, as it shows the amount of energy consumption of the circular sawing machine. Also, this factor is directly related to maintenance cost, such that with a small increase in the level of vibration, the maintenance cost increases to a large extent. This paper presents new prediction models to assess the vibration of circular sawing machine. An evaluation model based on the imperialist competitive algorithm as one of the most efficient artificial intelligence techniques was used for estimation of sawability of the dimension stone in carbonate rocks. For this purpose, four main physical and mechanical properties of rock including Schimazek's F-abrasivity, uniaxial compressive strength, mean Mohs hardness, and Young's modulus as well as two operational parameters of circular sawing machine including depth of cut and feed rate, were investigated and measured. In the predicted model, the system vibration in stone sawing was considered as a dependent variable. The results showed that the system vibration can be investigated using the newly developed machine learning models. It is very suitable to assess the system vibration based on the mechanical properties of rock and operational properties

ANALIZA POUZDANOSTI STROJEVA ZA PUNOPROFILNI ISKOP TUNELA PRIMJENOM SIMULACIJSKE METODE MONTE CARLO

The high boring capability of full-face tunnel boring machines, especially in urban tunnels, has led to their increased use in tunnel excavation in various and unfavourable geological conditions. Therefore, many efforts have been made to predict and improve the performance of these machines. In this regard, most of the previous studies have focused on the effect of geological and mechanical properties of rock or soil. However, delays due to the maintenance and repair of these machines, which contribute to a major share of unwanted and unpredicted stops at work, have not been considered. Reliability analysis is a practical method based on studying the behaviour of breakdowns and maintenance of machines and systems. This approach can be suggested as part of the appropriate planning for machine maintenance and consequently reducing downtime and costs. In this way, it is possible to identify weaknesses and critical points of a machine or system of the boring process. In the present study, the reliability of the full-face tunnelling machine was analysed with the Monte Carlo simulation method. The studied machine is divided into 5 subsystems including mechanical, electrical, hydraulic, water and compressed air subsystems. Using breakdown data of about 24 months of boring operation, the reliability of each subsystem was simulated and evaluated. Eventually, the reliability of the boring machine was simulated using the Kamat-Riley (K-R) method. The results showed that if no maintenance operation is performed on the subsystems, the overall reliability of the boring machine will decline to zero after about 38 hours of continuous boring operation. Finally, to improve the overall reliability of the boring machine, based on accomplished reliability analysis, we suggest an effective preventive maintenance and repair system for keeping the machine in optimal operating conditions for a longer period.Visoka učinkovitost strojeva za bušenje punoga profila tunela, posebno u gradskim tunelima, dovela je do njihove sve veće upotrebe u iskopu tunela u različitim i nepovoljnim geološkim uvjetima. Stoga su uloženi veliki napori sa svrhom predviđanja i poboljšanja učinkovitosti ovih strojeva. Većina prethodnih studija bila je usmjerena na utjecaj geoloških i mehaničkih svojstava stijene ili tla. Međutim, kašnjenja zbog održavanja i popravka ovih strojeva, koji doprinose velikomu udjelu neželjenih i nepredviđenih zaustavljanja pri radu, nisu uzeta u obzir. Analiza pouzdanosti praktična je metoda koja se temelji na proučavanju utjecaja kvarova i održavanja strojeva i sustava. Ovaj pristup može poslužiti za prikladno planiranje održavanja strojeva i posljedično smanjenje zastoja i troškova. Na taj način moguće je identificirati slabosti i kritične točke stroja ili sustava procesa bušenja. U ovome je istraživanju pouzdanost stroja za probijanje tunela analizirana primjenom simulacijske metode Monte Carlo. Stroj na kojemu je provedena analiza podijeljen je u 5 podsustava uključujući mehanički, električni, hidraulički te podsustave za komprimirani zrak i vodu. Koristeći se podatcima o kvarovima za oko 24 mjeseca bušenja simulirana je i procijenjena pouzdanost svakoga podsustava. Na kraju je simulirana pouzdanost stroja za bušenje korištenjem Kamat-Rileyjeve (K-R) metode. Rezultati su pokazali da ako se na podsustavima ne provodi operacija održavanja, ukupna pouzdanost stroja za bušenje past će na nulu nakon otprilike 38 sati neprekidnoga rada bušenja. U konačnici, radi poboljšanja sveukupne pouzdanosti stroja za bušenje, na temelju provedene analize pouzdanosti predlažemo učinkovit sustav preventivnoga održavanja i popravaka za održavanje stroja u optimalnim radnim uvjetima dulje vrijeme

Relationship between Texture and Uniaxial Compressive Strength of Rocks

Uniaxial compressive strength (UCS) is one of the most important parameters of rocks that is routinely used in rock engineering designs. This parameter is influenced greatly by textural properties of rocks; hence it is possible to estimate it from quantified texture coefficient (TC). In this paper, fourteen different types of rocks were experimentally studied to evaluate the effect of texture coefficient on UCS. Thin sections were first prepared, and then some digital photographs were taken from each section and were digitized in computer. Then, the texture coefficient for all samples were calculated. Subsequently, UCS of the samples were measured in laboratory. Finally, relationships between TC and UCS of rock samples were evaluated and related mathematical equations were presented. Results showed that the UCS has a power relationship with TC which can be utilized for future estimation purposes

AN INVESTIGATION OF THE EFFECT OF TOUGHNESS AND BRITTLENESS INDEXES ON AMPERE CONSUMPTION AND WEAR RATE OF A CIRCULAR DIAMOND SAW

Cirkularna dijamantna pila (skr. CDP) jedan je od glavni reznih strojeva ukrasnoga kamena. Predviđanje svojstava rada toga stroja važno je u procjeni troškova i planiranju rada. Svojstva takvih pila ovise o nekoliko važnih čimbenika koji se odnose na obilježja alata, svojstva stijena i stupnja trošenja prilikom rada. Prikazan je odnos između potrošnje struje, indeksa lomljivosti i čvrstoće, tj. otpornosti na trošenje kod takvih pila. Eksperiment je načinjen uporabom potpuno praćenoga rezanja 14 različitih uzoraka tvrdih stijena, uz stalnu brzinu te dubinu ureza. Trošenje, tvrdoća i lomljivost procijenjeni su jednostavnom i višestrukom regresijom, a zatim su izračunana predviđanja. Postoji znatna korelacija između trošenja, utroška struje i čvrstoće. Trošenje samih CDP-a može se pouzdano procijeniti uporabom višestruke regresije, koja se temelji na potrošnji struje i čvrstoći.The circular diamond saw (CDS) is one of the major sawing machines in dimension stone processing plants. Predicting the performance of a circular diamond saw is very important to estimate the cost and the planning of the stone processing plants. The performance of a CDS depends on some important factors such as machine and tool characteristics, physical and mechanical characteristics of rock and tool wear rate. In this research, it is aimed to investigate the relationship between ampere consumption, brittleness indexes and toughness with the wear rate of a CDS. This aim was pursued by using a fully instrumented cutting rig to cut 14 types of hard rock at constant feed rates, cut depths and peripheral speeds. Wear rate, toughness and brittleness indexes were evaluated using simple and multiple curvilinear regression analysis and predicted models were developed. The results indicated that there is a significant correlation between wear rate, ampere consumption and toughness. It is concluded that, the wear rate of a CDS can be reliably estimated using a multiple curvilinear model which includes ampere consumption and toughness