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W.l. Chenoweth - One of the best experts on this subject based on the ideXlab platform.
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The Uranium-Vanadium Production History of the Monument No. 2 Site Monument Valley, Apache County, Arizona
2011Co-Authors: W.l. ChenowethAbstract:The Monument No. 2 site consisted of a large open-pit mine, an upgrader, a concentrator and a heap leaching operation. Ore from the mine as well as products from other operations were shipped to mills for further processing and are included in the Production totals. Unpublished records of the U.S. Atomic Energy Commission (AEC) indicate the Monument No. 2 site produced more uranium during its procurement program (1947-1970) than any other mine in the State of Arizona. Production tonnage in published records ranged from 773,132 tons in Gregg and Evensen (1989) to 766,998 tons in Scarborough (1981). The purpose of this report is to give a summary of the Production History of the site and to present what is believed to be the correct total as the result of researching existing records.
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The Exploration and Production History of the Uranium-Vanadium Mines on Yazzie Mesa, Monument Valley, Apache County, Arizona
2011Co-Authors: W.l. ChenowethAbstract:Yazzie Mesa is a small mesa north of Vanadium Corporation of America's (YCA) 1943 Monument No.2 lease in northwestern Apache County, Arizona. This lease was originally mined for vanadium, but beginning in 1947 was mined for both uranium and vanadium. In 1950, two local Navajos, John M. Yazzie and Chester Tso obtained Navajo Tribal Mining Permits (MPs) on Yazzie Mesa on the northern trend of the Monument No.2 ore deposit. Mr. Tso's MP was never developed and it was dropped. Chee Nez later acquired that area. The report documents the Production History of the Yazzie and Nez mines. Yazzie Mesa, a name accepted by the U.S. Board of Geographic names, is shown on the Rooster Rock topographic quadrangle (USGS, 1988) north of the Monument No. 2 open at the center of the right-hand margin of the quadrangle. The Monument No.2 mine area is located in the extreme northwestern area of Apache County, Arizona (Figure 1). The mine is in the Cane Valley on the eastern flank of the Monument Uplift. Access to the mine area was via a 19-mile dirt road that headed south from U.S. Highway 163 one mile south of the bridge over the San Juan River at Mexican Hat, Utah. Another access road went from the mine, over Comb Ridge, and connected to U.S. Highway 160 near Mexican Water, Arizona.
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The Exploration and Production History of the Cato Sells Uranium-Vanadium Mines, Monument Valley, Apache County, Arizona
2011Co-Authors: W.l. ChenowethAbstract:In 1950, Cato Sells, a Navajo businessman, obtained three tracts (claims) adjacent to the Vanadium Corporation of America's (VCA) 1943 Monument No.2 lease in northeastern Apache County, Arizona. This lease was originally mined for vanadium and was now being mined for uranium and vanadium. Exploration drilling by the U.S. Atomic Energy Commission (AEC) located orebodies on Cato Sells' tracts. This report is to document the Production History of those tracts. Location The Monument No. 2 mine area is located in the extreme northwestern area of Apache County, Arizona (Figure 1). The mine is in the Cane Valley on the eastern flank of the Monument Uplift. Access to the mine area was via a 19-mile dirt road that headed south from U.S. Highway 163 one mile south of the bridge over the San Juan River at Mexican Hat, Utah. Another access road went from the mine, over Comb Ridge, and connected to U.S. Highway 160 near Mexican Water, Arizona. The Monument No.2 open pit mine is shown at the center of the right margin of Rooster Rock topographic quadrangle (USGA, 1988).
Xuri Huang - One of the best experts on this subject based on the ideXlab platform.
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Production Optimization Using Production History And Time-lapse Seismic Data
SEG Technical Program Expanded Abstracts 2006, 2006Co-Authors: Xuri Huang, Yun LinAbstract:This work proposes a method to use time-lapse seismic for Production optimization. The field in the study is mature with 15 years of Production History. Two legacy repeated seismic vintages are reprocessed to enhance the repeatability from the original data. The reprocessing is to eliminate the survey, source and noise differences. Due to the short inter-well distances, the use of time-lapse seismic becomes challenging. The proposed method uses the injector-producer relationship and the time-lapse seismic difference to calculate the inter-well ‘connectivity’ or injector-producer influence function. Experimental study shows that time-lapse seismic is able to improve the ‘connectivity’ representation so that a better History match can be achieved. Due to the linearized inter-well relationship based on the ‘connectivity’ function, the History matching processing is extremely efficient. Using the quantitative inter-well relationships, the method further optimizes the Production by perturbing the injection rate at each injector. It is found that the optimal injection configuration can increase oil Production. With a pilot implementation, it is shown that the new injection scheme can delay the oil Production decline.
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improving Production History matching using time lapse seismic data
Geophysics, 1998Co-Authors: Xuri Huang, Laurent J. Meister, Rick WorkmanAbstract:This paper presents a new approach to reservoir management by integrating time‐lapse seismic data with Production data. The basic steps involve combining the seismic data from the base survey with log and Production data to build an initial reservoir model which is run forward to the time of the repeat seismic survey. The output from this simulation was then converted to a synthetic monitor survey, using Gassmann’s equations and a simple convolutional approach. Finally, the differences between the synthetic and real seismic time‐lapse data are minimized using an optimization algorithm.
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Production History Matching With Time Lapse Seismic Data
SEG Technical Program Expanded Abstracts 1997, 1997Co-Authors: Xuri Huang, Laurent J. Meister, Rick WorkmanAbstract:Today geostatistical reservoir characterization from 3D seismic volumes provides most of the static descriptions for reservoir models. These models can be improved by integrating dynamic data in the reservoir description process. Recently 3D time-lapse seismic surveys have been proposed to relate time dependent changes in seismic attributes to the flow processes in the reservoir. This paper presents an improved approach to seismic reservoir monitoring by integrating reservoir simulation with the time-lapse seismic technique. A case study was conducted over a turbidite sheet sand reservoir in the Gulf of Mexico. The seismic data from the base survey were combined with log and Production data to build an initial simulator model which was run forward to the time of the monitor seismic survey. Dynamic History matching performed by a simulated annealing type of optimization further improved the simulator model. The output from the simulation was then converted to a synthetic monitor seismic survey using Gassmann’s equations and a simple convolutional approach. A quantitative seismic History matching methodology was then tested. It constrains the modeling process to match the Production History and minimize the error between the synthetic and measured 3D seismic time-lapse difference. This new systematic approach provides us with a quantitative time-lapse seismic analysis tool which has the potential to improve reservoir management.
Rick Workman - One of the best experts on this subject based on the ideXlab platform.
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improving Production History matching using time lapse seismic data
Geophysics, 1998Co-Authors: Xuri Huang, Laurent J. Meister, Rick WorkmanAbstract:This paper presents a new approach to reservoir management by integrating time‐lapse seismic data with Production data. The basic steps involve combining the seismic data from the base survey with log and Production data to build an initial reservoir model which is run forward to the time of the repeat seismic survey. The output from this simulation was then converted to a synthetic monitor survey, using Gassmann’s equations and a simple convolutional approach. Finally, the differences between the synthetic and real seismic time‐lapse data are minimized using an optimization algorithm.
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Production History Matching With Time Lapse Seismic Data
SEG Technical Program Expanded Abstracts 1997, 1997Co-Authors: Xuri Huang, Laurent J. Meister, Rick WorkmanAbstract:Today geostatistical reservoir characterization from 3D seismic volumes provides most of the static descriptions for reservoir models. These models can be improved by integrating dynamic data in the reservoir description process. Recently 3D time-lapse seismic surveys have been proposed to relate time dependent changes in seismic attributes to the flow processes in the reservoir. This paper presents an improved approach to seismic reservoir monitoring by integrating reservoir simulation with the time-lapse seismic technique. A case study was conducted over a turbidite sheet sand reservoir in the Gulf of Mexico. The seismic data from the base survey were combined with log and Production data to build an initial simulator model which was run forward to the time of the monitor seismic survey. Dynamic History matching performed by a simulated annealing type of optimization further improved the simulator model. The output from the simulation was then converted to a synthetic monitor seismic survey using Gassmann’s equations and a simple convolutional approach. A quantitative seismic History matching methodology was then tested. It constrains the modeling process to match the Production History and minimize the error between the synthetic and measured 3D seismic time-lapse difference. This new systematic approach provides us with a quantitative time-lapse seismic analysis tool which has the potential to improve reservoir management.
Claudio Virues - One of the best experts on this subject based on the ideXlab platform.
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Integrated Characterization of Hydraulically Fractured Shale-Gas Reservoirs—Production History Matching
SPE Reservoir Evaluation & Engineering, 2015Co-Authors: Siavash Nejadi, Juliana Y. Leung, Japan J. Trivedi, Claudio ViruesAbstract:Summary Advancements in horizontal-well drilling and multistage hydraulic fracturing have enabled economically viable gas Production from tight formations. Reservoir-simulation models play an important role in the Production forecasting and field-development planning. To enhance their predictive capabilities and to capture the uncertainties in model parameters, one should calibrate stochastic reservoir models to both geologic and flow observations. In this paper, a novel approach to characterization and History matching of hydrocarbon Production from a hydraulic-fractured shale is presented. This new methodology includes generating multiple discrete-fracture-network (DFN) models, upscaling the models for numerical multiphase-flow simulation, and updating the DFN-model parameters with dynamic-flow responses. First, measurements from hydraulic-fracture treatment, petrophysical interpretation, and in-situ stress data are used to estimate the initial probability distribution of hydraulic-fracture and induced-microfracture parameters, and multiple initial DFN models are generated. Next, the DFN models are upscaled into an equivalent continuum dual-porosity model with analytical techniques. The upscaled models are subjected to the flow simulation, and their Production performances are compared with the actual responses. Finally, an assisted-History-matching algorithm is implemented to assess the uncertainties of the DFN-model parameters. Hydraulic-fracture parameters including half-length and transmissivity are updated, and the length, transmissivity, intensity, and spatial distribution of the induced fractures are also estimated. The proposed methodology is applied to facilitate characterization of fracture parameters of a multifractured shale-gas well in the Horn River basin. Fracture parameters and stimulated reservoir volume (SRV) derived from the updated DFN models are in agreement with estimates from microseismic interpretation and rate-transient analysis. The key advantage of this integrated assisted-History-matching approach is that uncertainties in fracture parameters are represented by the multiple equally probable DFN models and their upscaled flow-simulation models, which honor the hard data and match the dynamic Production History. This work highlights the significance of uncertainties in SRV and hydraulic-fracture parameters. It also provides insight into the value of microseismic data when integrated into a rigorous Production-History-matching work flow.
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Integrated Characterization of Hydraulically Fractured Shale Gas Reservoirs Production History Matching
Day 3 Thu October 02 2014, 2014Co-Authors: Siavash Nejadi, Juliana Y. Leung, Claudio ViruesAbstract:Abstract Advancements in horizontal well drilling and multistage hydraulic fracturing have made gas Production from tight formations economically viable. Reservoir simulation models play an important role in the Production forecasting and field development planning. To enhance their predictive capabilities and capture the uncertainties in model parameters, stochastic reservoir models should be calibrated to both geologic and flow observations. In this paper, a novel approach to characterization and History matching of hydrocarbon Production from a hydraulic fractured shale gas is presented. This new methodology includes generating multiple discrete fracture network (DFN) models, upscaling the models for numerical multiphase flow simulation, and updating the DFN model parameters using dynamic flow responses. First, measurements from hydraulic fracture treatment, petrophysical interpretation, and in-situ stress data are used to estimate the initial probability distribution of hydraulic and induced micro fractures parameters, and multiple initial DFN models are generated. Next, the DFN models are upscaled into an equivalent continuum dual porosity model using either analytical (Oda) or flow-based techniques. The upscaled models are subjected to the flow simulation, and their Production performances are compared to the actual responses. Finally, an assisted History matching algorithm is implemented to assess the uncertainties of the DFN model parameters. Hydraulic fracture parameters including half-length, shape, and conductivity are updated together with the length, conductivity, intensity, and spatial distribution of the induced fractures are optimized in the algorithm. The proposed methodology is applied to facilitate characterization of fracture parameters of a multi-fractured shale gas well in the Horn River basin. Fracture parameters and stimulated reservoir volume (SRV) derived from the updated DFN models are in agreement with estimates from micro-seismic interpretation and rate transient analysis. The key advantage of this integrated assisted History matching approach is that uncertainties in fracture parameters are represented by the multiple equall-probable DFN models and their upscaled flow simulation models, which honor the hard data and match the dynamic Production History. This work highlights the significance of uncertainties in SRV and hydraulic fracture parameters. It also provides insight into the value of micro-seismic data when integrated in a rigorous Production History matching workflow.
Dominic John Miocevic - One of the best experts on this subject based on the ideXlab platform.
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An Improved Method to Obtain Reliable Production and EUR Prediction for Wells with Short Production History in Tight/Shale Reservoirs
Unconventional Resources Technology Conference Denver Colorado 12-14 August 2013, 2013Co-Authors: Shaoyong Yu, Dominic John MiocevicAbstract:Horizontal wells with multistage fracturing completion, a relatively mature technology, have been applied to the development of tight/shale reservoirs for years. However, it still remains an industry challenge to reasonably predict future Production profiles and expected ultimate recoveries (EURs) in very tight wells. Recently, a number of new methods, being either empirical or analytical, have been introduced to the industry. However, doubts have been raised for their suitability in wells having Production History less than 2 to 3 years. This paper presents an improved method based on Valko’s Stretch Exponential Production Decline (SEPD) by employing a new specialized plot to find all parameters that are essential to Production forecast. This newly developed method (also called the Modified SEPD Method or YM-SEPD Method) is much easier to use, and most importantly it will yield a more reliable Production forecast and EUR estimation in wells having very short Production History, compared to all other currently available methods. Hundreds of horizontal wells including both oil and gas wells, from various formations (Cadomin, Montney, Notikewin, Cardium, Barnett Shale etc.) and under different hydraulic fracturing conditions, have been analyzed using this YM-SEPD Method. Results have indicated that both EURs and Production forecasts can be easily predicted for wells having two to three years of Production History. For wells having less than 2 years of Production History, this YM-SEPD method will also be able to yield a reasonable Production prediction by coupling it with another empirical method. A close examination on characteristics of the Production decline curve, derived from this YM-SEPD method, has revealed the reasons of why this improved method can better predict Production performance and EUR in tight horizontal wells. Furthermore, this YM-SEPD method can also provide a very useful mean of identifying the PSS flow of horizontal wells in very tight reservoirs. Both real and synthetic oil & gas well examples are presented in the paper to illustrate the advantages of using this improved method.
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an improved method to obtain reliable Production and eur prediction for wells with short Production History in tight shale reservoirs
Unconventional Resources Technology Conference Denver Colorado 12-14 August 2013, 2013Co-Authors: Y U Shaoyong, Dominic John MiocevicAbstract:Horizontal wells with multistage fracturing completion, a relatively mature technology, have been applied to the development of tight/shale reservoirs for years. However, it still remains an industry challenge to reasonably predict future Production profiles and expected ultimate recoveries (EURs) in very tight wells. Recently, a number of new methods, being either empirical or analytical, have been introduced to the industry. However, doubts have been raised for their suitability in wells having Production History less than 2 to 3 years. This paper presents an improved method based on Valko’s Stretch Exponential Production Decline (SEPD) by employing a new specialized plot to find all parameters that are essential to Production forecast. This newly developed method (also called the Modified SEPD Method or YM-SEPD Method) is much easier to use, and most importantly it will yield a more reliable Production forecast and EUR estimation in wells having very short Production History, compared to all other currently available methods. Hundreds of horizontal wells including both oil and gas wells, from various formations (Cadomin, Montney, Notikewin, Cardium, Barnett Shale etc.) and under different hydraulic fracturing conditions, have been analyzed using this YM-SEPD Method. Results have indicated that both EURs and Production forecasts can be easily predicted for wells having two to three years of Production History. For wells having less than 2 years of Production History, this YM-SEPD method will also be able to yield a reasonable Production prediction by coupling it with another empirical method. A close examination on characteristics of the Production decline curve, derived from this YM-SEPD method, has revealed the reasons of why this improved method can better predict Production performance and EUR in tight horizontal wells. Furthermore, this YM-SEPD method can also provide a very useful mean of identifying the PSS flow of horizontal wells in very tight reservoirs. Both real and synthetic oil & gas well examples are presented in the paper to illustrate the advantages of using this improved method.
