Search Documents

By Norman F. Schulz

The technical excellence of separation achieved in a mineral concentration process, or any other process where two constituents of any kind are physically separated from each other, is expressed uniquely and quantitatively by the separation efficiency (E,): E. = (R - R,), where R is the percentage of the valuable constituent and R, the percentage of the waste appearing in the concentrate. The separation efficiency meets all the usual requirements of a true efficiency and is independent of the nature of the process used. It can be visualized as the percentage of the feed material that, in effect, actually undergoes complete separation while the rest of the feed is distributed randomly and unchanged into the two separation products. The problem of quantitatively assessing the results of a mineral concentration process recurs whenever one tries to decide which of two similar test results is more desirable. Although economic factors may greatly influence the eventual choice of process, they usually have very little to do with the technical excellence of a separation and are, therefore, not a consideration at this point. Concentrate grade and recovery, used simultaneously are the most widely accepted measures of performance, and if both the grade and the recovery are greater for one case than for another, the choice is simple. However, when the results of closely competitive operations are compared, it often occurs that one set of test results shows a higher grade and a lower recovery than another and the choice is no longer obvious. Laboratory investigations of a mineral concentration process applied to a given feed material can often be designed to yield successive paired values of concentrate grade and recovery over the practical range of the course of a separation process.' These results may be plotted as some combination of the cumulative values of grade, weight recovery, or unit recovery in the concentrate. The resulting correlations for two slightly different sets of conditions can then be compared qualitatively, or even quantitatively in particular cases.2 Such comparisons are not applicable, however, to individual concentration test results. The reduction of a separation test result to a single efficiency figure, preferably as a percentage of ideality, would afford the simplest and most precise means for comparing the results of competitive tests. The effective proportion of feed material that undergoes complete separation in any real concentration process, hereafter referred to as "separation efficiency," is such a figure. It is essily calculated from the usual feed and product data and can even be evaluated, in many cases, from data in publications describing various concentration processes. Mineral Concentration Processes and Their Evaluation Mineral Concentration Processes: The overall concentration process may be subdivided into a liberation process which severs the bonds between unlike mineral species, and a separation process, which sorts the resulting liberated particles into two products—a concentrate rich in mineral A and a tailing lean in mineral A. A perfect mineral concentration process is represented by the idealized scheme shown in Fig. 1 in which liberation and separation are not differentiated. The feed mixture consists of two mineral types which are completely liberated early in the process and then sorted by type. All the mineral particles of type A which respond uniquely to the selection forces acting in the ideal separator, report to the concentrate, while all the mineral particles of type non-A report to the tail-

Jan 1, 1971

By William Paxton Hewitt

In the Santa Eulalia mining district, Chihuahua, Mexico, the main mineral zone occurs in a gently warped dome with simple associated structures and contains orebodies distributed through a vertical range of over 900 m. The stratigraphy of 1945 m of geologic column is described and an abrupt shrinkage is documented in the volume of limestones immediately associated with large orebodies. Termed collapse, this shrinkage occurred during the course of mineralization. Contacts of limestone with igneous sills, and 366 m of fossiliferous limestone beds, particularly the main fossil bed, have been important localizers of ore-bodies. Up-dip gravitational controls may have been important. Fractures have exerted only local controls and over short distances. Thrust zones have displaced diabase sills and in turn have been intruded by upper members of a group of rhyolite porphyry sills. Mineralizers were related to the rhyolite porphyry, and ore has been introduced to the limestone where certain sills lie between the displaced segments of diabase and have been cut by north-south fissures. Speculations are raised that fields of unreleased strain may have influenced orebody locations; the district's zoning pattern may be a reflection of the filtering effects of large volumes of limestone; and that metal-rich brines mobilized by or incorporated within the invading porphyry might be the source of the mineralizers. PRODUCTION AND LOCATION The Santa Eulalia district has a production record approaching or exceeding 35 million tons of silver-lead-zinc ore from replacement bodies in limestone. In operation since the first years of the 17001s, production has been confined to two intensely mineralized areas separated by 2 km of barren limestone, the West Camp and the East Camp. Probably 50% has been mined since 1908, with over 90% from the West Camp. The West Camp, exploited through a vertical depth of 1945 m and now approaching exhaustion, is the subject of this paper. The district lies in the northern part of the Santa Eulalia Mountains in central Chihuahua in northern Mexico, 400 km south of El Paso, Texas, and 22 km southeast of Chihuahua City. Dominating the northern part of the range is the Cerro de Santa Eulalia, a broad rolling upland which contains the district's West and East Camps. The West Camp, on the west side of the range, centers around the village of Santo Domingo, which is 2 km northeast of the Real de Santa Eulalia (Fig. 1). REGIONAL GEOLOGY Thick-bedded middle Cretaceous limestones, probably Aurora, form the great bulk of the Cerro de Santa Eulalia. These beds, warped into a gentle dome, are severed on the west by a faultline scarp and truncated on the north by the Dolores Pass, a wind gap that

Jan 1, 1969

By H. R. Cooper

Beginning from the point of view that process control of ore flotation can be approached by on-line analysis of processing behavior, an equation was developed which has characteristics useful for a multi-variable feedback loop. The application of this equation to optimizing control with a data acquisition system will be discussed in Part 11. OBJECTIVE OF CONTROL The purpose of developing a feedback method for concentrator control is to provide a means for determining ore processing behavior in order that data describing the ore can be used to make appropriate changes in control conditions while the ore continues to flow through the flotation circuit. In absence of simple linear relationships between pairs of variables in the flotation process, attention is directed to the need for a generalized relationship which possibly would incorporate all pertinent variables. It would be possible to apply such an equation to the control of variables in a concentrator in real time according to operational requirements as ore gradually changes in quality and processing behavior. To meet this objective, it is necessary to define relationships describing flotation performance in terms of performance variables capable of being measured on-line, either with on-line instruments and analyzers or with manual methods lending themselves to quick determination of meaningful information. Relationships derived to meet this objective form a model for the flotation process. The evaluation of flotation parameters of the ore and the execution of control on the basis of the derived information while the ore is continuing through the process would constitute a feedback control system. Data for the following control and performance variables can be made available: 1) ore feed rate, 2) collector addition rate, 3) lime addition rate, 4) pulp density, 5) assay or multiple assays in feed, tails, or concentrate sufficient for material balancing, 6) particle size distribution in flotation feed, 7) froth height, and 8) frother addition rate. Other process variables, such as flotation air input and mechanical agitation intensity, are usually not considered as control variables and were not taken into account in this analysis. Other data, such as that describing the ore, would be useful for concentrator process control. However, information of this type (such as ore hardness, grain size of the mineral, chemical species of the mineral, and ore surface properties) being not presently measurable in the on-line sense, has the effect of causing disturbances in the system which can be detected only indirectly. The process control system being sought must recognize disturbances by their effect on measured performance followed by determining control changes to compensate for them in meeting the objectives of improved performance (perhaps higher throughput, maximum return, etc.). A suitable model for the process having capability of recognizing the effects of ore disturbances should provide the means for introducing proper compensation through control changes. This would be done by processing on-line data with the model to calculate coefficients reflecting ore characteristics. This procedure can only be applied in a typical flotation system when on-line data can be processed at faster rates than the usual rate at which the ore in flotation feed takes on significantly different characteristics. For example, material balance data can be accumulated in approximately 5-min intervals using on-line X-ray fluorescence analysis. The flotation system time constant might be 15 min including grinding. Ore changes having time constants longer than 1 hr could be accommodated using on-line feedback control by this procedure. FORM OF A FLOTATION MODEL A suitable form for mathematical expression of the flotation process is an equation involving rates, when each of the components entering into the separation can be treated independently by a rate equation. A first-order, kinetic rate equation can be written on

Jan 1, 1967

By L. E. Lynd

Ilmenite concentrates prepared from beach and dune sands of Florida, India, Australia, and other localities deviate to varying degrees from the theoretical composition of pure ilmenite, and generally contain more TiO2 than the formula FeTi03 would indicate, and some Fe2O3. This variation in composition is due to different amounts of altered ilmenite in the concentrates. (') The alteration has been shown to take place by oxidation and leaching of the iron in ilmenite, to yield residual products consisting of amaphous or very finely crystalline titanium dioxide and ferric oxide. Other studies(2) have stressed that ilmenite may alter first to an amorphous titanium-iron oxide, or to an amorphous mixture of titanium and iron oxides, with later alteration to crystalline titanium dioxide. There has been some speculation as to whether alteration of ilmenite is usually caused by weathering or by hydrothermal pr0cesses.(3,4,5 Three main methods of approach were used to study the mechanism and rate of ilmenite weathering. (1) Etch tests were used to learn the relationship between crystallographic orientation and the rate of chemical attack on ilmenite. (2) Altered ilmenites in New Jersey sands were compared with ilmenite in rocks of the area from which the sands were probably derived. (3) Experiments were carried out to determine at what rate, and by what agents, originally fresh ilmenite could be altered in the laboratory under simulated weathering conditions. ETCH FIGURES ON ILMENITE CRYSTAL PLANES A rather large ilmenite crystal from Sannidal, Norway, about 11/2 x 11/2 x 2 inches, bearing a few natural faces with imperfect surfaces, was prepared for etching by grinding and polishing crystal planes whose Bravais-Miller indices (referred to hexagonal axes) had been determined by X-ray methods to be 00.1, 10.0, and 10.2. Metallographic examination showed that the crystal was homogeneous, and uniform in orientation, except for the presence of twin lamellae which were oriented with their broadest surfaces parallel to the 00.1 planes of the large crystal. Since ilmenite is rather inert to standard etch reagents, strong solutions of hot sulfuric acid and cold hydrofluoric acid were used. Preliminary tests established that better etch figures were obtained using HF than with H2So4 solutions. The etch figures produced on 00.1 and 01.0 planes of ilmenite by etching 3 to 5 minutes in cold concentrated HF solution are shown in Figures 1, 2, and 3. The figures on 00.1 are "etch hillocks", rather than pits, and according to Honess(6), this phenomenon

Jan 1, 1961

COUNCIL OF ECONOMICS, AIME Formerly Mineral Economics Division Established as a Division December 15, 1948 Established as a Council February 26, 1957 Sheldon P Wimpfen, Chairman John D Ridge, Vice-Chairman (Mining) A J Philips, Vice-Chairman (Metals) Warren B Davis, Vice-Chairman (Petroleum) COUNCIL OF EDUCATION, AIME Formerly Mineral Industry Education Division Established as a Division January 15, 1932 Established as a Council February 26, 1957 James D Forrester, Chairman Charles V Kirkpatrick, Vice Chairman (and Chairman-elect) Lysle E Shaffer, Past Chairman Truman H Kuhn, Secretary-Treasurer Colorado School of Mines Golden, Colorado John S Bell, Contact AIME Director

Jan 1, 1960

By J. E. Forciea, O. E. Palasvirta, L. G. Hendrickson

AH pilot and commercial plants working with Mesabi Range taconite employ wet magnetic separation. Progress is being made with a dry magnetic process, but this has not yet been applied to taconite except in the laboratory and pilot plants. Flowsheets in all five plants are similar, including multiple stages of grinding, each followed by magnetic separation, which rejects a finished tailing. The flowsheet in Fig. 1 is used in the preliminary and commercial plants of the Erie and Reserve mining companies and in Unit C of Oliver's Pilotac plant. At Erie the desliming operation is omitted. In the Reserve plants two ball mills are used with each rod mill. Pilotac uses flowsheet 2 in Unit A-B and has also tested flowsheet 3. Principal differences in the three flowsheets are the number of grinding stages and the type of roughing. The terms open-circuit roughing and closed-circuit roughing are best defined by the diagrams. Special Test Data Given in Table I: For the Erie and Reserve commercial plants, Table I reflects routine conditions. Pilotac, the experimental plant, has been run with several flowsheets, including those followed at Erie and Reserve's commercial operations. Pilotac data for these last two flowsheets are similar to commercial plant results and are not repeated in Table I; statistics are given, however, for special test conditions. using other flowsheets. when the objective was to 'to extra-grade concentrate, Variations Among Taconites: Although crude ore tributary to these plants is generally classified as taconite, there are important differences in mineralogy and fineness of dissemination.

Jan 1, 1959

By Cyril Wells, Paul E. Busby, Donald P. Hart

EARLY workers in the field have established that the diffusion of nitrogen follows normal diffusion laws. Concentration-penetration data from layer analyses of reasonably pure iron specimens nitrided in an atmosphere of CO-NH, are given in the literature,' and were utilized to calculate diffusion constants for nitrogen. The diffusion of nitrogen in y-iron may be represented approximately by the equation D - 1.07x10-' e-:".'m'"'r The diflusion coefficients, D, given by this relation represent mean values, since carburization occurred simultaneously with nitriding. The rate of diffusion in a-iron has been determined from calculations based on data obtained by measuring the internal friction of samples at each of several frequencies and temperatures.' The expression for the diffusion of nitrogen in a-iron derived from these experiments is D= 1.4x10-1 e-it tudent Increasing carbon content decreases the diffusion of nitrogen in a-iron.3 Oxygen, either dissolved or combined, has been shown' to exert a marked influence on the diffusion of nitrogen from a nitriding atmosphere. D values increase rapidly with increasing amount of dissolved oxide in the metal, but diffusion is completely inhibited if preliminary oxidation has produced the slightest trace of iron oxide on the surface. Diffusion coefficients have also been calculated from permeability and solubility data,' but these values are of questionable accuracy since the boundary conditions assumed may not actually exist. Experimental Method The method selected for determining the diffusion coefficient of nitrogen in a-iron in the present investigation was the so-called fractional saturation method. This method consists of heating the specimen in an atmosphere of H2-NH8 mixtures of known composition for a predetermined time. Following this treatment, the specimen is analyzed for nitrogen; and the diffusion coefficient is calculated from a known relationship of the fractional saturation, time of diffusion, and dimensions of the specimen. This relation is based on a solution of Fick's second law and assumes that the surface of the specimen immediately reaches a given concentration which remains constant during the diffusion anneal. Tabular solutions are available4-5 and provide the relationship between fractional saturation and the quantity \/Dt /a, where D is the diffusion coefficient in cm2 per sec, t is the time of the diffusion anneal in seconds, and a, in the present experiments, is the half-thickness of the slab specimen in cm. The method is adequately discussed elsewhere.9-10 Material The material for this study consisted of 3/32 in. thick (0.24 cm) carbonyl iron plate. The major impurities in this iron are oxygen and carbon, which are readily removed by long time high temperature treatment in an atmosphere of purified hydrogen. In order to reduce the diffusion anneal time for saturation runs, some of this material was rolled to a thickness of 0.015 in. (0.038 cm) prior to the hydrogen treatment. Hydrogen treatments were carried out in a hydrogen-purified Armco iron tube heated in a global

Jan 1, 1957

By C. F. Weinaug, R. W. Farley, J. F. Wolfe

A rapid, accurate method for predicting the dew points of gas condensate systems and their subsequent normal and retrograde phase behavior with pressure decline has been developed. The method predicts dewpoint pressure, volume percent liquid, condensate content of produced gas, and the liquid and gas compositions at pressures below the dewpoint pressure. Use of a modified form of the BWR equation of state, which was established by regression calculations on experimental data from several gas condensates, provides depletion behavior predictions that are significantly improved over predictions using K-values based on convergence pressures and Standing's correlation for density. INTRODUCTION Prediction of complex hydrocarbon-mixture thermodynamics is fundamental to reservoir and gas process engineering. In particular, accurate descriptions of phase behavior are needed to plan production operations for gas-condensate reservoirs. Although analysis of reservoir behavior during producing and cycling operations can be made for simple reservoir models, extensions of these studies to more complex reservoir systems are still difficult, both with regard to numerical techniques and the phase behavior of the fluids. This report presents a mathematical method for handling the complex phase relationships encountered in retrograde condensates; it represents an advance in reservoir behavior technology in that it will aid the development of closed-form mathematical representations of total production systems. A typical phase diagram for a complex hydrocarbon mixture is shown in Fig. 1. When the reservoir temperature T, is higher than the critical temperature Tc, and lower than the critical-condensation temperature Tct' the mixture is a gas condensate. Decreasing the pressure on a condensate while maintaining nearly constant temperature will result in two phases forming at the dew point. Further decrease in pressure will cause additional liquids to be formed. This phenomenon is called retrograde condensation. As pressure continues to decrease, normal phase behavior regions are encountered (liquid vaporizes as the pressure decreases) until the low-pressure dew point is encountered. When a gas-condensate reservoir is produced, gas is withdrawn and the volume of fluids in the reservoir remains nearly constant as the pressure declines. Heavier components tend to accumulate in the liquid phase as a result of retrograde condensation, while lighter components tend to concentrate in the vapor phase. Thus, as the gas is produced the composition of the gas and the condensate

Jan 1, 1970

By R. L. Fullman, J. W. Cahn

A method is derived for obtaining the distribution of sphere diameters and plate thicknesses (or pearlite spacings) from size distribution functions obtained along randomly oriented lines. The method described offers several advantages over existing methods. IT is often of interest to measure not only the average particle size but also the distribution in sizes of particles dispersed in an opaque material, such as an alloy. Particles of a single size will exhibit a range of apparent sizes on the plane of polish. If the sample contains a distribution of particle sizes, the distribution of observed sizes on the plane of polish is related to the distribution of actual particle sizes by an integral equation, For example, a distribution of sphere sizes, N(r),

Jan 1, 1957

By H. W. Fleming, R. R. Brooks

The Clearwater Deposit, a small occurrence of massive-sulphide mineralization enclosed in an envelope of disseminated-sulphide mineralization, was discovered as a result of an aeroelectromagnetic survey in New Brunswick in 1955. Subsequently, additional flights were made over the deposit and various ground follow-up methods were employed to ascertain the nature of their response. All methods proved to be capable of indicating the occurrence with varying degrees of precision. This paper is a presentation and a discussion of the magnetic and electromagnetic data, both airborne and ground, and the self-potential data obtained over this deposit. The attention of Canadian mining exploration companies was initially focussed on New Brunswick by the discovery, in 1953, of the Brunswick ore body. Ground electromagnetic surveys were of considerable assistance in locating and developing this deposit. In the following year, 1954, the Heath Steele base-metal deposits were discovered by employing an airborne electromagnetic device and ground electromagnetic surveys to follow-up the airborne indications. These discoveries demonstrated clearly that both airborne and ground electromagnetic techniques were applicable for locating the near-surface deposits of massive sulphides present in this region. Airborne electromagnetic equipment became available on a contract basis through Aeromagnetic Surveys Limited early in 1955 and was used extensively thereafter throughout a large portion of northern New Brunswick. It was as a result of one of these surveys with Aeromagnetic Surveys Limited equipment in the summer of 1955 that the Clearwater Deposit was detected. The airborne anomaly was located on the ground by means of an electromagnetic survey using a Swedish Slingram unit. During 1956, the region was investigated more thoroughly- in the hope that other sulphide bodies might be located. Airborne electromagnetic coverage was extended and the Clearwater Deposit itself was used as a testing ground for the various methods and types of equipment currently in use in New Brunswick. In this paper com prative data are presented for the airborne magnetic, airborne electromagnetic, ground magnetic and ground electromagnetic surveys over this deposit. The ground electromagnetic instruments used were the McPhar vertical-loop unit and the Slingram and Boliden horizontal-loop units. Self-potential surveys were carried out with a McPhar unit. From the geophysical point of view, all ground electrical methods employed indicated the presence and the extent of the massive-sulphide mineralization with a good degree of accuracy. The horizontal-loop methods however, defined the contacts more precisely as is to be expected when dealing with a flatly-dipping

Jan 1, 1961

By J. L. Green

Virginia-Carolina Chemical Corp., in its Florida Operations, uses both roller mills and ball mills in dry grinding of phosphate rock. The roller mills have been in operation since 1954 in the Mining Department. The ball mills were installed and put in operation in 1960 in the Harding Concentrate Superphosphate Plant. The roller mills in the Mining Department are used to grind phosphate rock for outside customers. This involves short notice orders of varying grinds, grades and types of rock. The ball mills grind phosphate rock for use in V-C's own phosphoric acid and concentrated superphosphate plant. These mills grind generally two types of rock for one grind. In 1959, a 10% speed-up was made in the operating speed of the roller mills. This paper deals with the operational gains and resulting cost savings which evolved from this speed-up, and compares the present operations of the roller mills and of the ball mills in grinding phosphate rock. In January 1959 it was decided to determine the feasibility of reducing the grinding cost on the roller mills, per ton of rock ground, by speeding up the mill 10%. At this time, one mill was completely reconditioned so it would be in top condition. Extensive tests were then run both before and after the mill speed-up to determine the resultant cost savings. These tests showed that, due to this 10% speed-up, the mill capacity was increased approximately 20% and grinding power costs per ton were reduced approximately 10%. Table I shows the results of these tests. Each test run actually represents several of the same type rock and grind, averaged together. Each test run lasted approximately three hours. The validity of these runs has been confirmed by subsequent operation in grinding over 1,000,000 tons of phosphate rock. Accurate records have been kept on power consumption and repairs as well as tons produced. Two types of feed rock were used for the tests — pebble phosphate rock and flotation phosphate concentrate rock. The pebble phosphate rock size is approximately 80-90% plus 20 mesh. The flotation concentrate phosphate rock size is approximately 15% plus 20 mesh and 95% plus 100 mesh. The same two types of rock feed were used for all the test runs. Test Nos. 1, 2, and 3 were run at the original mill speed of 85.5 rpm on the vertical shaft. Test No. 1 was run with a feed of high grade flotation concentrates; the desired fineness attempted was 70% passing 200 mesh. Tests No. 2 and No. 3 were run with a feed of low grade pebble. Test No. 2 was run for a desired fineness of 70% passing 200 mesh. Test No. 3 was run for desired fineness of 50% passing 200 mesh.

Jan 1, 1963

By H. J. de Haan, J. van Lookeren

In view of their size and favorable characteristics, Shell's heavy-oil fields on the eastern coast of Lake Maracaibo, Venezuela — known as the "Bolivar Coast" — are obvious candidates for the application of thermal recovery methods. During the last decade various methods have been tested, such as steam drive,', steam soak and in-situ combustion.3 Steam soak was discovered as a promising production method rather accidentally in 1969, during early steam drive testing in the Mene Grande Tar Sands1 When steam erupted at the surface due to breakdown of the overburden, the injection wells were back-flowed to relieve the reservoir pressure. This resulted in high oil production rates, all the more impressive because the reservoir is unproducible by primary means. It was concluded that injection of limited amounts of steam might be a very effective method for stimulation of heavy-oil wells. To obtain information that would be more widely applicable, testing of the process was continued in the eastern part of the Tia Juana field (Fig. 1). Here even more favorable results were obtained than in Mene Grande. This created sufficient confidence to prompt a large-scale project, which was considered essential for an adequate evaluation of ultimate recovery, steam requirements, mechanical problems and economic prospects. To obtain an early answer on the ultimate recovery a fairly depleted area was selected in the western part of the same field ("A" in Fig. 1). The first steam was injected in March, 1964. This paper describes the performance until the end of 1966. The production mechanism and well inflow performance are discussed in some detail. In view of the favorable results obtained so far, steam soak operations have expanded considerably since the start of this project. Presently, five other projects are under way, of which two are about the same size as the one under discussion, with further extensions being programmed. Description of the Project Reservoir Data Shell's part of the Main Tia Juana reservoir has a proven area of 8,800 acres and an average net oil sand thickness of 130 ft. It contained an initial quantity of 2,750 million bbl of stock tank oil (STOIIP), with an API gravity ranging from 10 to 15 API and a viscosity of 100 to 10,000 cp (at 122F). As a geological unit it is known locally as the Lower Lagun-illas member of the Lagunillas formation, which is early Miocene in age. The sand bodies are believed to be distributary channel sands deposited in a lower coastal plain. Most of the channel sands have lateral and some vertical communication. The field was developed mainly in the period from 1936 to 1950. The ultimate primary recovery is estimated at 18.1 percent of STOIIP, of which 12.5 percent STOIIP had been produced by the end of 1963 from some 540 wells. By then the average pressure had decreased from an initial value of 960 to 550

Jan 1, 1970

By P. K. Leung, S. R. Allada, P. M. Dranchuk, D. Quon

The alternating direction explicit procedure (ADEP) makes use of the boundary conditions to reduce multi-dimensional problems to a series of one-dimensional problems. The method, previously applied to reservoirs containing only an under-saturated oil, has now been extended to cover the case of natural gas reservoirs. l his involves solving a non-linear partial differential equation, application of the procedure is straightforward and no calcuIational problems were encountered. INTRODUCTION There has been a growing interest in formulating mathematical models of petroleum and natural gas reservoirs — models which permit the engineer to examine and evaluate the physical and economic consequences of various alternative production policies. The tremendous reduction in the cost of solving such models in recent years has made possible their use as an almost routine management tool. This reduction is the result not only of improved computer hardware but also of the development of more efficient mathematical techniques. The present paper is concerned with the application of a recently proposed numerical method (ADEP) to two-dimensional gas reservoirs. STATEMENT OF THE PROBLEM Given a two-dimensional Region R, bounded by a closed Curve C (Fig. 1) such that the behavior on Curve C is known, the differential mass balance for each fluid phase in R, neglecting gravitational effects and assuming Darcy's law for fluid transport, can be written as:

Jan 1, 1967

By L. E. Fish, G. S. Wyman

CHUQUICAMATA open-pit mine is capable of producing a total of 105,000 tons daily. When the sulphide plant is operating to capacity the distribution of this quantity will be approximately 30,000 tons sulphide ore, 30,000 tons oxide ore and 45,000 tons of waste. At that time the combined capacity of the oxide and sulphide plants will be about 540 million lb of copper per year. Twenty one benches have been opened to date and all are still active except the three top ones at the northeastern limit of the pit. These have been pushed back to final slope line. The pit is 8850 ft long, 3540 ft wide and 980 ft deep. Benches are not all developed to a standard height as the large development shovels used in cutting new benches have been of different size and range. At this time new benches 521 ft high are being developed with an' 11-yd shovel. Ore haulage through the greater part of the pit operation has been on down grades to the crushing plant. With the opening of bench F-4 in April 1944 the first adverse-grade ore haul was encountered. Of the total tonnage now being mined, 35 pct comes from the four benches that are below the level of the crushing plant yard. Waste had been dumped on the same or nearly the same level as the bench from which it was removed up to the opening of bench F-4. Waste from this and lower levels is hauled to the level of the crusher, yard where it must cross the flow of ore traffic to reach the only available dumping space to the east of the mine. The average ore haul is 3.13 miles one way shovel to crusher, and the average waste haul from that portion handled by railroad is 3.32 miles one way from shovel to waste dump. Waste that is being removed by truck haulage from the upper part of the -mine is hauled an average of 1 mile. Ore loaded by trucks is hauled 3/4 mile to a car loading ramp and then by rail to the crushing plant. Drilling and Blasting There are two types of development for blasting being used: One for opening new benches and the other for bank shooting. The former consists of 9a in. diam churn-drill holes drilled 11.8 ft center to center in rows 10.2 ft apart with the holes staggered in the rows thus giving an equilateral-triangle pattern of 11.8 ft on a side. After the first block, 492 ft long by 71.5 ft wide, is shot in the pattern described above, the cut is advanced by smaller shots consisting of four rows of holes spaced 23 ft center to center with the rows 23 ft apart. These shots are fired in conjunction with side shots in which the holes are drilled 33 ft center to center and 29.5 ft back from the toe, thus squaring up the bank for subsequent shooting. An average bank shot consists of about 60 holes drilled in two rows parallel to the face, 30 holes to

Jan 1, 1952

Jan 1, 1881

By A. B. Cook, C. J. Walker, G. B. Spencer

Although water will displace oil from a petroleum reservoir to a greater extent than gas will, there are some reservoirs in which gas rather than water should be used for pressure maintenance. This is indicated by the high-percentage oil recovery in the case history reports on the Pickton field1 in East Texas and the Raleigh field2 in Mississippi. In gas cycling, total oil recovery includes vaporized products from the immobile oil in addition to oil produced by displacement. If a large part of the immobile oil is vaporized, total oil recovery may be higher than that obtainable from pressure maintenance by water injection. However, the amount of immobile oil vaporized may range from almost 0 to 100 percent, and no simple and reliable method has been presented in the literature for calculating oil vaporization. Development of such a method was the purpose of this study. Several papers concerning the calculation of oil vaporization have been published,3 6 and each is based on the concept dealing with K values — equilibrium constants for the various components in reservoir oils. (K for a component in a system of vapor and liquid in equilibrium is the mole fraction in the vapor phase divided by the mole fraction in the liquid phase.) This appears to be the most logical approach. Yet, the problem is too great for a perfect solution, even with modem laboratories to analyze oils and high-speed digital computers to perform calculations; the number of components in reservoir oils is too large. Because of their complexity no two reservoir oils are exactly alike. Also, K values change not only with variations in pressure and temperature but also with composition of the reservoir oil. In addition, during gas cycling, the lighter hydrocarbons tend to vaporize first. Thus, the reservoir oil becomes more dense and less volatile as gas cycling continues. Furthermore, the greatest amount of oil vaporization occurs near the injection well. Therefore, a simplified method is required for calculating oil vaporization because a rigorous method is not practical. The present methods of calculating vaporization generally require knowledge of the reservoir oil composition in which the mole fractions of the lighter components through hexanes are given; the remaining oil is described as C, + (heptanes and others of greater molecular weights). Assigning one K value for the C,+ system provides the simplest solution, but this incorrectly assumes that K for C, + does not change as gas cycling continues. This assumption can cause large errors because the K value may become less than a thousandth of the original after a large amount of oil vaporization. Another way to solve the problem is to determine changing K values for C, + according to how much of the C, + has been vaporized. To determine these values a sample of the reservoir oil is injected into a pressure-volume cell, and dry gas is batched in and out of the cell. Appropriate measurements and tests are made to determine K

Jan 1, 1970

By H. H. Stoek

MINE models have three distinct uses: 1. As exhibits in expositions and museums. 2. As exhibits in law suits. 3. As illustrations in teaching mining engineering. All three uses are in a sense educational. The third, or distinctively teaching function, has not been extensively developed in America as it has been abroad, chiefly because of the cost of the models and the scarcity of model makers. In connection with expositions, such as the Columbian, the Louisiana Purchase, and the Panama-Pacific, a number of very good mine and metallurgical models were prepared with funds furnished by State commissions, by mining organizations or mining companies. At the close of these, expositions, some of these models have been deposited in National or State museums or in educational institutions, but too many of them have been lost, or have been stored, away in some mining company's office or in the basement of some State building, where they have been lost sight of and have gradually fallen to pieces. A visitor to a German mining school is impressed by two facts: 1. The mining laboratories are in general inferior to those in America. 2. The mining museums are infinitely superior -to ours, particularly in models exhibited. One may reply to this comparison by saying that a museum is necessarily a work of time. From the historical standpoint this is, of course, true, but it is not necessarily true in connection with a working museum intended to illustrate current practice. For instance, the oldest mining school in Germany, that at Freiberg, has much excellent historical material, but very little on modern practice, while Berlin, one of the youngest German mining schools, has a most extensive and valuable collection of modern appliances and models. This is true in spite of the fact that one of the best-known model shops is at Freiberg, from which many of, the models to be seen in America have come. Because many of the models in American mining schools have come from

Jan 4, 1917

By H. C. H. Darley

The principal causes of unstable boreholes* have been known for many years. For example, in a paper published in 1938, Halbouty and Kaldenbachl listed nearly all the classes of troublesome shales that we know today. Much progress has been made since then, but we still have difficulty in identifying the cause of hole problems and consequently in selecting the right technique for combatting them. This subject was discussed at length by Kelly2 in a recent paper and much valuable information was provided. In the Shell Laboratory it was felt that there was a need for a better understanding of the basic mechanisms underlying the various forms of hole instability, and accordingly, a study was undertaken. This entailed reviewing the physics and chemistry of shales, developing tests for characterizing shales, and constructing a model to study borehole stability. Full simulation of underground conditions was not attempted; for example, we used reconstituted shale specimens, and often simple solutions or suspensions rather than practical drilling muds. Such procedures are necessary in order to establish mechanisms, but caution must be exercised in applying the results to the more complex conditions in the field. Part I — Compaction Swelling and Dispersion of Shales Compaction of Sediments Shales are formed by the compaction of sediments. Water is expressed as sediments are buried by subsequent layers, and the degree of compaction is proportional to the depth of burial, provided the water is able to escape easily to permeable formations. The younger sediments, when recovered at the surface, soften and disperse when mixed with water; the older shales have undergone diagenesis (alteration of the clay minerals, secondary cementation, etc.), and remain hard and unaffected by water. In this paper we shall apply the term "shale", as the drilling engineer does, to everything from clays, which are highly reactive to water, to completely lithified materials such as claystones and slates, which are completely inert. However, because these materials behave quite differently when encountered in the drilling well, it is desirable to develop a simple means of characterizing them. The feature that distinguishes the various shales is their dispersibility in water —soft clays disperse readily, harder shales disperse slowly when agitated, the lithified materials will not disperse at all unless milled. In the dispersibility test used in our study, a weighed amount of dry shale particles in the 12-to-100-mesh-size range was placed in a tube filled with distilled water and allowed to soak for 16 hours. The

Jan 1, 1970

Trans. No. Place Date Vol. Page 1. Wilkes-Barre Pa......May.71 1 3 2. Bethlehem, Pa.........Aug., '71 I 10 3. Troy, N.Y............Nov..: 71 1 13 4. Philadelphia, Pa........Feb., 72.. 1 17 5. New York. N. Y.*......May, '72.. 1 20 6. Pittsburgh. Pa.........Oct..' 72.. 1 25 7. Boston, Mesa..........Feb., '73.. 1 28 8. Philadelhia, Pa.*......May, '73.. 2 3 9. Easton, is............Oct..' 73.. 2 7 10. New York, N. Y.......Feb..' 74 . . 2 11 11. St. Louie. Mo.*........May,' 74 . . 3 3 12. Hazleton, Pa...........Oct., '74.. 3 8 13. New Haven Conn......Feb., '75.. 3 15 14. Dover,N.J.*..........May, 75.. 4 3 15. Cleveland,O...........Oct. 75. 4 0 16. Washington D. C......Feb.'' 76.: 4 18 17. philadelphia, Pa.......June,: 76.. 5 3 18. Philadelphia Pa........Oct 76.. 5 19 19. New York, N. Y.......Feb: '77.. 5 27 20. Wilkes-Barre. Pa.*.....Mag :77.. 0 3 21. Amenia N. Y..........Oct. 77.. 6 10 22. Philadeiphia Pa........Feb.;' 78. . 6 18 23. Chattanooga' Term.*. . . May' 78. . 7 3 24. Lake George: N. Y....: Oct. 78. . 7 103 25. Baltimore, Md.*.......Feb:' 79.. 7 217 26. ~ittsburgi, Pa.........~a;' 79.. 6 3 27. Montreal, Canada......~ept.;' 79.. 8 121 28. New York, N. Y.*......Feb., '80.. 8 275 29. Lake Superior, Mich....Aug., '80. . 9 1 30. Philadelphia, Pa.*......Feb., '81. 9 275 31. Staunton, Va..........May, '81. .10 1 32. Harrisburg, Pa.........Oct.. '81..10 119 33. Washington, I). C.*....Feb., '82. . 10 226 34. Denver. Colo..........Aug.. '82. . ll 1 35. Boston. Mass.*.........Feb.. '83..11 217 38. Roanoke, Va...........June, '83.. 12 3 37. Troy, N. Y...........Oct.. '83. .12 175 38. Cincinnati. O.*.... Feb, '84..12 4 39. Chicago Ill............May, '84. . 13 1 40. philadelphia, Pa........Sept., '84. . 13 285 41. New York, N. Y.*......Feb., '85. . 13 586 42. Chattanooga, Tenn.....May, '85..14 1 43. Halifax, N. S..........Sept., '85.. 14 307 44. Pittsburgh, Pa.*........Feb.. '86 . . 14 587 45. Bethlehem. Pa.........May, '86 .. 15 Ixiii. 46. St. Louis, Mo..........Oct, 86.. 15 Ixx. 47. Scranton, Pa.*.........Feb.', '87. . 15 lxxvi 48. Utah and Montana.....July '87.. 16 xvii. 49. Duluth, Minn...........July' '87. -16 xxiv. 50. Boston. Mass.*.........Feb.: '88. . 16 xxviii. 51. Birmingham, Ala.......May, '88. .17 xix. 52. Buffalo N. Y..........Oct. '88.. 17 xxiv. 53. New york, N.Y........feb.' ;89 . . 17 xxxi. 54. Colorado..............June' 89 . . 18 xvii. 55. Ottawa, Canada........Oct., 89. . 18 xxiv. 56. Washington, I). C.*. . . Feb. 90. .18 xxx. 57. New York, N. Y........sept:, '93. .19 vii. 58. New York, N. Y.*......Feb. '91. . 19 xxv. 59. Cleveland, O.......... June, :91 . .a xvi. 60. Glen Summit, Pa.......Oct, 111. . 20 lxi. 61. Baltimore, Md.*.......Feb.: '92. .21 xix. 62. Plattsburg, N. Y.......June, '02. . 21 xxxiii. 03. Reading. Pa...........Oct., :92. .21 xliv. 64. Montreal. Canada*.....Feb. 93..21 65. Chicago, Ill............aug.: '93..22 XI. 66. Virginia Reach. Va.*. ...Feb., '04. .24 xwl. 67. Bridgeport Coon.......Oct., '94..24 xxx?. 08. Florida ...'............Mar., '95. .25 xix 69 Atlanta. Ga......... Oct 95. 25 xi 70. Pittsburgh. Pa.*........Feb., '96.. 26 xvii. Trans. No. Place Date Vol. Page 71. Colorado..............Sept. '96. .26 xxix. 72. Chicago, Ill............Feb.. "97.. 27 xvii. 73. Lake Superior..........July '97. .27 xxx. 74. Atlantic City, N. J.*. ..Feb.: :98. .28 xvii. 75. Buffalo N. Y..........Oct. 08. .28 XXXVI. 76. New York,N. Y.*......Feb.: '99. .29 xvii. 77. California.............Sept., ;99. . 29 xlix. 78. Washington, D. C.*.....Feb., 00. .30 xix. 79. Canada...............Aug.. '00. .30 xlv. 80. Richmond. Va.*........Feb.. '01. . 31 xix. 81. Mexico................Nov..'01.. 32 cxviii. 82. Philadelphia Pa. $......May, :02. . 33 xxxv. 83. New Haven, Conn......Oct.. 02.. 33 xlvii. 84. Albany N. Y.*........Feb '03. .34 xxiii. 85. New York, N. Y........Oct.': '03. .34 xi. 86. Atlantic City. N. J.*....Feb., '04. .35 XXIII. 87. Lake Superior..........Sept.'04. .35 dii. 88. Washington. D. C......May' '05. .36 xlii. 89. British Columbia.......July, '05. . 36 90. Bethlehem. Pa.........Feb. '06. .37 xli. 91. London, England.......July: '06. .37 xlviii. 92. New York, N. Y........April, '07. . 38 lii. 93. Toronto, Canada.......July. '07. .38 lix. 94. New York, N. Y........Feb., :08. .39 xli. 95. Chattanooga, Tenn.....Oct.. 08..39 xlviii. 06. New Haven Conn......Feb. '09. .40 xli. 97. Spokane,Wash.........Sept:.'09. .40 xlviii. 98. Pittsburgh, Pa.........Mar.,'10. .41 xxxviii. 99. Canal Zone............Nov.,'10. .41 dv. 100. Wilkes-Barre, Pa.......June. ' 11. . 42 xxxiv. 101. San Francisco, Cal......Oct.. '11..42 xliv. 102. New York. N. Y.*......Feb 12. .43 Ixxvii. 103. Cleveland, Ohio........0ct;' '12.. 44 wii. 104. New York, N. Y.*......Feb.. '13. .45 xv. 105. Butte, Mont...........Aug., '13. .46 ?' 108. New York, N. Y........Oct., 13..47 vii 107. New York. N. Y.*......Feb.. '14..48 xv. 108 Salt Lake City. Otah Aug. :l. 49 5: 109. Pittsburgh, Pa.........Oct., 14. .50 vii. 110. New York, N. Y.*......Feb., '15. .51 xvi. 111. San Francisco, Cal......Sept., '15. .52 xii. 112. New York,N. Y.*......Feb., '16..54 xvi. 1 Arizona...............Sept.,'l6. .55 VII 114. New York, N. Y.*......Feb., '17: .56 vii. 115. St. Louis, Mo..........Oct.. '17..57 vii. 116. NewYork,N. Y.*......Feb.. '18..59 xvii 117. Colorado.....:........Sept.,'18. .60 vii. 118. Milwaukee, Wis........Oct.. '18. .60 x:!: 119. NewYork,N. Y.*......Feb., '19..61 xi. 120. Chicago...............Sept.,' l9.. 62 VII. 121. New York, N. T.*......Feb., '20..63 ix. 122. Lake Superior District. .Aug., '20.. 66 ix. 123. New York, N. Y.*......Feb., '21. .66 xiii. 124. Wilkes-Barre, Pa...... Sept.. : 21.. 66 xix. 125. New York, N. Y.*......Feb., 22. .67 ix. 126. San Francisco. Cal......Sept.,:22. .68 xxix. 127. New York, N.Y.*.....Feb., 23. .69 xxix 128. Canada...............Aug., '23. .69 xxxv! 128.129. New York, N. Y.*......Feb., ;24. .70 xxxi. 130. Birmingham, Ala.......Oct. 24. .71 xxxiii 131. NewYork.N Y.*......Feb.: '25.. 71 xxxviii. 132. 131.Salt Lake City, Utah .. .Sept., '25. .73 xvi 133. New York, N. Y.*......Feb., '26. .73 xxii. 134. Pittsburgh Pa ....... Oct.. '26. .74 xv. 135. New York,' N. Y.*............Feb., '27. .75 x::: 135.136. NewYork,N. Y.*......Feb., '28..76 104 137 NewYork.N. Y.*......Feb., '29. .291 116 138.San FranciscoYork,N.Y. Cal..........Oct. 29..308 406 139. New York, N. Y.*...Feb., '30..30H 1321

Jan 1, 1930

By G. E. Perry, R. D. Seba

The steam soak process is the most widely applied and most successful thermal supplemental recovery process in use today. This process, which consists of injection of steam in various quantities into a well that is subsequently used as a producer, can be repeatedly applied to the same well. The treatment, if successful, will increase the production rate of the well for a given period. For this reason, the steam soak process should be considered primarily as an acceleration method rather than as a method for producing oil that could not be recovered by primary means. However, application of this process to reservoirs containing viscous crude may produce oil that otherwise would have zero present value or would be produced at such low rates by primary methods that it would not be profitable. A major necessity for the successful application of the steam soak process is a source of natural energy. This source of energy may exist in one or more of the following forms: expansion of fluids, compaction, gravity drainage. This study was undertaken to determine the effect of gravity drainage on steam soak production and recovery and to develop a method for predicting production rates, ultimate recovery, and heat requirements when applying this process to a reservoir in which the primary driving mechanism is gravity drainage. (For additional discussion of some of the factors that affect recovery of viscous oils by the steam soak process, see Ref. 5.) Model The model developed for analyzing the performance of the steam soak process in gravity drainage reservoirs is a modified form of that developed by Matthews and Lefkovits.1,2 The model used in this study consists of two concentric cylindrical volumes of productive formation with cap and base rock of impermeable material. The inner cylinder, extending from the radius of the wellbore to some predetermined radius, is referred to as the hot zone; and the outer cylinder extending from the exterior boundary of the hot zone to the outer drainage boundary will be referred to as the partially heated zone. Fig. 1 is a schematic cross-section of the model, indicating its thermal properties. Horizontally the reservoir is divided into two regions, the upper region having a high gas saturation and residual liquid saturation, and the lower region containing a high liquid saturation. The boundary between these two regions is referred to as the free surface, which drops and changes shape as fluid is produced from the reservoir. The model was used to analyze the steam soak process by applying the following assumptions: 1. The horizontal formation is composed of one or more homogeneous noninterconnected layers containing incompressible fluids. Each layer is treated separately. 2. The hot zone is heated by the initial soak and is maintained at the steam temperature corresponding to atmospheric pressure by resoaking. 3. The height of the free surface at the producing well is at all times zero (producing well is pumped off). 4. The position of the free surface at the start of

Jan 1, 1970