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Two of the world's wealthiest men have put their vast resources behind what the nuclear industry calls small modular reactors (SMRs) in the quest for the perfect carbon-free energy source. TerraPower, founded by Bill Gates, and PacifiCorp, owned by Warren Buffett's Berkshire Hathaway, are sponsors of the project. The first SMR from TerraPower, the Natrium reactor project, will be built in Wyoming--the nation's primary coal producer--at the very location that once housed a coal station, where the infrastructure for a steam-cycle power plant and distribution to the electrical grid already exist. Last year, the state legislature passed a law authorizing utilities to replace coal or natural gas generation with small nuclear reactors and the US Department of Energy awarded TerraPower $80 million in initial funding to demonstrate Natrium technology; the department has committed additional funding subject to congressional approvals. Just ask anyone in Texas where a combination of frozen wind turbines and unprecedented demand last winter darkened the state for days.
ABSTRACT: The study is conducted in a coal mining which elongated at South Kalimantan to East Kalimantan covering Tanjung Formation and Kampungbaru Formation. As the area is an open-pit mine, a rapid assessment is required in order to determine slope stability. One of the assessment methods is by using SMR (Slope Mass Rating) based on Bienawski’s RMR. SMR has been studied and formulated by a lot of researchers. However, those SMR results might be inappropriate for some field condition, including the study area. Therefore, in order to get the optimal value of SMR, a correction must be done to all value of obtained SMR. The correction provides modified SMR formula as follow: SMR = 7.2251 RMR0.5207; R2 = 0.89. Based on the formula, slope stability can be determined and applied to slope design for rock slope with following criterions: (1) Very poor rock: slope will stable with dip-slope <35°; (2)Poor rock: slope will stable between 35°-49°; (3)Fair rock: slope will stable between 50°-61°; (4) Good rock: slope will stable between 61°-71°; (5) Very good rock: slope will stable between 71°-79°.
The research area is an open-pit mine, a rapid assessment is required in order to determine slope stability. One of the assessment methods is by using SMR (Slope Mass Rating) based on Bienawski’s RMR (Rock Mass Rating). Slope Mass Rating is a method that can provide quick suggestion for determining stable slope angle in mining engineering (open-pit mining). Some researchers proposed different formulas of SMR, therefore to get optimum value of SMR, an approach was carried out through modification (Zakaria et al. 2015). Geomechanics classification is based on Rock Mass Rating (Bieniawski, 1989). The study is conducted in a coal mining which elongated at South Kalimantan to East Kalimantan covering Tanjung Formation and Kampungbaru Formation. Tanjung Formation at Satui and surrounding is located in South Kalimantan, and Kampungbaru Formation at Sangasanga located at East Kalimantan (Fig. 1).
The Slope Mass Rating (SMR; Romana, 1985) geomechanics classification was developed as a sequel of Bieniawski’s Rock Mass Rating (RMR) system, which was almost impossible to use in slopes due to the extreme range of the correction factors (up to 60 points of a maximum of 100) and to the lack of definition of them. A detailed quantitative definition of the correction factors is one of the advantages of SMR classification. During the last thirty years the use of SMR system has been extended to many countries from the five continents and, thus, it is time to review the most interesting developments. Both RMR and SMR are discrete classifications, depending on the values adopted by the variables that control the parameters. This can cause major changes in the parameters value due to small differences in the variables value, with changes in the final rock mass assigned quality. On the other hand, geomechanics quality indexes are extremely biased. To avoid this problem, some authors have proposed continuous functions for SMR. This classification has been also adapted for its application in heterogeneous and anisotropic rock masses, for high slopes, for is application trough stereographic projection and Geographical Information Systems, has been used as susceptibility rockfall parameters and has been included in the technical regulations of several countries. Additionally, some open access computer tools have been developed for the computation of SMR. Consequently, this paper reviews: 1) the most important modifications and adaptations of slope classifications which derive directly from SMR; 2) the use of SMR throughout the world; 3) many significant papers on slopes analysed with SMR all over the world; and 4) future trends in the use of SMR.
Rock mass classifications are a universal communication system for engineers which provide quantitative data and guidelines for engineering purposes that can improve originally abstract descriptions of rock mass from inherent and structural parameters (Pantelidis, 2009) by simple arithmetic algorithms. The main advantage of rock mass classifications is that they are a simple and effective way of representing rock mass quality and of encapsulating precedent practice (Harrison and Hudson, 2000). Some of the existing geomechanical classifications for slopes are Rock Mass Rating (RMR, Bieniawski, 1976; 1989), Rock Mass Strength (RMS, Selby, 1980), Slope Mass Rating (SMR, Romana, 1985), Slope Rock Mass Rating (SRMR, Robertson, 1988), Chinese Slope Mass Rating (CSMR, Chen, 1995), Natural Slope Methodology (NSM, Shuk, 1994), Slope Stability Probability Classification (SSPC, Hack et al., 2003), modified Slope Stability Probability Classification (SSPC modified, Lindsay et al., 2001), Continuous Rock Mass Rating (Sen and Sadagah; 2003), Continuous Slope Mass Rating (Tomás et al., 2007), Fuzzy Slope Mass Rating (FSMR; Daftaribesheli et al., 2011) and Graphical Slope Mass Rating (GSMR; Tomás et al., 2012). Some of the above mentioned geomechaniccs classifications are variants from the original ones. SMR is universally used (Romana et al., 2003). SMR is computed from basic RMR (Bieniawski, 1989) which was originally proposed for tunnelling but also included a correction factor for slopes to take into account the influence of discontinuities orientation on the slope stability which was almost impossible to be used due to the extreme range of the correction factors (up to 60 points of a maximum of 100) and to the lack of definition of them in practice. In this paper a review of the last thirty years of the SMR is performed, discussing its main modifications, adaptations and applications worldwide.
The SMR geomechanics classification system (adaptation of RMR for slopes) is reviewed with data from 87 actual slopes in Valencia. In a research project, SMR has been applied by a GIS system, as a method to forecast stability problems in future road construction.
On revient sur la classification geomechanique SMR ( une adaptation du RMR pour talus et pentes) avec les dates de 87 talus existant autour de Valencia. Dans le cadre d'un projet de recherche SMR a ete appliquee, avec un système GIS, comme methode de prevision de stabilite problèmes dans la construction de futures routes. Une methodologie pour l'application du GIS a ete developpe.
Das Geomechanische Einteilungssystem SMR (eine Anpassung des RMR an Böschungen) wird an Hand der Daten von 87 Böschungen im Gebiet von Valencia ueberdacht. In einem Forschungsprojekt wurde das SMR in einem Geographischen Informationssystem (GIS) als Methode zur Vorhersage von Stabilitatsproblemen bei zukuenftigen Straßenbauprojekten eingesetzt. Das Ergebnis dieser Arbeit ist die Entwicklung einer Methodologie fuer die GIS- Anwendung
RMR “Rock Mass Rating” geomechanics classification (also called CSIR) was introduced and developed by BIENIAWSKI (1973, 1984, 1989) deal extensively with RMR (and other geomechanics classification systems). A good recent reference to RMR application to tunnels in BIENIAWSKI (1993). RMR has become a standard for use in tunnels and many professionals apply it to describe any rock mass. ORR (1996) has given a good overview of the RMR use in slopes. LAUBSCHER (1976), HALL (1985) and ORR (1992) proposed different relationships between RMR value and limit angle for slopes. STEFFEN (1978) classified 35 slopes and concluded that “results had a statistical trend”. ROBERTSON (1988) established that when RMR > 40 the slope stability is governed both by orientation and shear strength of discontinuities whereas for RMR < 30 the failure develops across the rock mass.
In the 1976 version, the “rating adjustments for discontinuity orientation” for slopes were: very favourable 0, favourable - 5, fair -25, unfavourable -50, very unfavourable -50, very unfavourable -60. No guidelines have been published for the definition of each class. A mistake in this value can supersede by far any careful evaluation of the rock mass, and classification work becomes both difficult and arbitrary. ROMANA (1985, 1993, 1995) proposed a new addenda to RMR concept, specially suited to slopes. BIENIAWSKI (1989) has endorsed the method.
SMR Classification system
The “Slope Mass Rating” (SMR) is obtained from RMR by adding a factorial adjustment factor depending on the relative orientation of joints and slope and another adjustment factor depending on the method of excavation.
(Equation in full paper)
The RMRB (see Table 1) is computed according Bieniawski´s1979 proposal, adding rating values for five parameters: (i) strength of intact rock; (ii) RQD; (iii) spacing of discontinuities; (iv) condition of discontinuities; and (v) water inflow through discontinuities and/or pore pressure ratio.
The adjustment rating for joints (see Table 2) is the product of three factors as follows: (i) F1 depends on parallelism between joints and slope face strike.
Summary For environmental reasons, there are times when the use of radioactive chemical sources for density and neutron logging is not possible. The inability to use these logging tools seriously affects porosity determination in gas-bearing reservoirs. Several tools, such as the nuclear magnetic resonance (NMR) tool, the sonic tool, or a minitron-based tool, determine porosity without using a radioactive source. These tools, however, are influenced by many effects and, when used alone, cannot deliver an accurate gas-independent porosity. A new methodology that combines sonic and NMR logs for improved porosity evaluation in gas-bearing reservoirs is proposed. The first variant of the method uses the sonic compressional transit time and the total NMR porosity (ft, NMR) to determine the total porosity, corrected for the gas effect, and the flushed-zone gas saturation. In this approach, a linear time-averaged equation corrected for compaction is applied to the sonic compressional log. The simplicity of the solution, much like the previously published DMR1 Density-Magnetic Resonance Interpretation Method, allows fast, easy computation and a complete error analysis to assess the quality of the results. In the second variant of the method, we show that the rigorous Gassman equation has a very similar response to the Raymer-Hunt-Gardner (RHG) equation for a water/gas mixture. This allows substitution of the complex Gassman equation by the much simpler RHG equation in the combined sonic-NMR (SMR) technique to estimate total porosity and flushed-zone gas saturation in gas-bearing formations. Both techniques are successfully applied to an offshore gas well in Australia. In this well, the porosity in the well-compacted sands is in the 20 to 25 p.u. range and the compaction factor is approximately 0.77. The sonic-magnetic resonance results compared favorably to the established density-magnetic resonance results and also to core data. In another offshore gas well from the North Sea, the porosity in the highly uncompacted sands is in the 35 to 40 p.u. range, and the compaction factor is around 1.85. Both SMR techniques were able to produce a very good porosity estimate comparable to that estimated from the density-neutron logs. Introduction Many authors have discussed the applications of sonic logs in gas-bearing formations. Stand-alone sonic techniques that use Wyllie's equation or the RHG equation are based on empirical observations of water-saturated samples that are extended to water/gas mixtures. Stand-alone sonic techniques that involve the Gassman theory are generally too complex for the petrophysicist to consider the effects of many sonic moduli parameters that must be determined to solve for porosity. Other authors have discussed the applications of NMR logs in gas-bearing formations. Porosity logs derived from NMR alone suffer from the low hydrogen index of the gas and the long T1 polarization time of the gas when the data is acquired with insufficient wait time. To provide a robust estimate of total porosity in gas-bearing formations, a combined density-NMR technique has been proposed. However, density logging uses a radioactive chemical source, and in certain sensitive environments, it is not used because the radioactive source might be lost in the hole. The sonic-magnetic resonance technique has been developed to provide an accurate porosity in these situations. This paper will demonstrate the following:The Gassman and RHG methods predict very similar sonic responses. Both Gassman and RHG sonic porosities are quite insensitive to fluid type, and hence to water saturation. The solution of the Gassman approach is more complex, requiring five parameters compared to only one for the RHG method (RHG is, therefore, more practical). Combining ft, NMR and RHG provides a good estimate of porosity in gas-bearing formations. Combining ft, NMR and a modified Wyllie scheme gives a simple analytic solution analogous to the DMR method. Gas-corrected porosity could be estimated at the wellsite by rescaling the sonic log. The ft, NMR/RHG and ft, NMR/Wyllie schemes are applied to two field examples. The results are compared to those from DMR, to core data in the first well, and to density/neutron analysis in the second well. Sonic Porosity Equations The three methods (in order of increasing complexity) used to compute sonic porosity from the compressional slowness are based on the Wyllie, RHG, and Gassman formulas. In this section, each approach is analyzed, and the predictions from each are compared with the others. Wyllie Method. The Wyllie equation isEquation 1 Eq. 1 can be rearranged intoEquation 2a withEquation 2b In these equations, f=porosity, ?tc=the sonic compressional slowness, ?tma=the matrix compressional slowness, ?tf=the fluid compressional slowness, and Cp=the compaction factor needed to correct the sonic porosity to the true porosity.
All screening tests were selective mobility reduction (SMR). SMR in installed outside of the water bath, and conducted at 77 F and 2,000 psig. Surfactants 1 through 5 are 0.04, 0.06, 0.07, For this study a high-pressure foam-durability Surfactant solutions (1 wt% active component) 0.07, and 0.35 wt %, respectively. The major part of the This article is a synopsis of paper SPE 37221, "Assessment of Foam Properties and Effectiveness in Mobility Reduction for CO In general, the value of the introduced. A cathetometer is used to measure ratio of Darcy or superficial velocity of the slope decreases when surfactant is added to the foam height and the weight of the fluid to the average pressure gradient along the brine as a foaming agent.
Abstract CO2-foam has been long realized as an effective mobility reducing agent for CO2 flooding in oil recovery process. Recent researches indicate that some CO2- foams also show an exciting additional characteristic, selective mobility reduction (SMR), in which the mobility of foam is reduced by a greater fraction in high than in low permeability cores in laboratory experiments. Examples of such an unusual property are presented first in this paper to show the mobility dependence of CO2-foams on the rock permeabilities ranging from 30 to 900 md. Secondly, a simple modeling procedure is introduced to evaluate the benefits of using an SMR displacing agent in a typical oil recovery process. In this model, the mobility of the displacing fluid is considered to be proportional to the permeabilities raised to a specific exponent. This allows us, for different values of exponent from zero to one, to examine how different degrees of SMR will affect the oil recovery. The modeling results show that, as expected, the breakthrough time of the faster (higher permeability) layer is delayed and the vertical sweep efficiency of the model is improved if the mobility of the injected fluid is reduced. Furthermore, this improvement becomes even more significant when an SMR fluid is used for the displacement. Even a slightly favorable SMR fluid, that shows a slight dependence of mobility on rock permeability, can significantly reduce the number of pore volumes required to achieve the same degree of recovery as that realized with an ordinary mobility reducing agent.