This paper presents a method to eliminate production loss due to liquid-loading in tight gas wells. Cyclic shut-in control is a simple production strategy that particularly benefits lower-permeability stimulated wells, including but not limited to shale gas wells. Comparison is made between a gas well producing (1) in a "ideal" situation where 100% of liquids entering from the reservoir or condensing in the tubing are continuously removed (without shut-ins), (2) in a meta-stable liquid-loading condition with low gas rate, typical of most wells today, and (3) by the proposed strategy of cyclic shut-in control. We show that cyclic shutin control of stimulated low-permeability vertical wells to ultra-low-permeability horizontal multi-fraced wells can produce without ever experiencing liquid loading, and with little-to-no delay of ultimate recovery. Cyclic shut-in control can be applied to all stimulated, lower-permeability gas wells, from the onset of gas rates that result in liquid-loading. The strategy can also be used for wells which already have experienced a period of liquid-loading, but the expected performance improvement may be less because of near-well formation damage caused by historic liquid-loading – e.g. fresh-water backflow and liquid-bank accumulation. In historically liquid-loading wells, an initial period of liquid removal and/or light stimulation may be needed prior to initiating cyclic shut-in control. We show that the shut-in period should optimally be as short as operationally possible. Cyclic shut-in control is shown to work equally well for layered no-crossflow systems with significant differential depletion at the onset of liquid loading. Minimizing rate and recovery loss of liquid-loading gas wells is of international interest. We believe that cyclic shut-in control will become an industry standard practice for shale gas wells, and should lead to a significant ultimate increase in worldwide gas reserves. The method is extremely simple and requires only a rate-controlled wellhead shut-in device.
Different computerized algorithms are used to assist the layout planner in generating alternate layout. CRAFT (Computerized Relative Allocation of Facilities Technique) has been developed to improve an existing layout, while ALDEP (Automated Layout Design Program) is a construction layout. The improvement given by ALDEP over CRAFT technique was found to reduce annual material handling cost by 23% [1]. This study hypothesize that better result could be gained by combined two algorithms rather than their independent application. The hypothesis is verified by taking layout problems of CV Aji Jaya Mandiri. The objective of the study is to get the optimal layout of CV Aji Jaya Mandiri using ALDEP and followed by improving it with CRAFT. ALDEP based on the value of proximity (total closeness rating). The layout resulted from ALDEP is improved by exchanging machines positions. The newly layout obtained by ALDEP is compared with the result layout improved by CRAFT. There are two criteria for comparing the layout: material handling cost taken from MHES (material handling evaluation sheet), and the manufacturing lead time or processing time using Promodel simulation. The material handling cost of the layout resulted by CRAFT was decreased by 6,24%, that is mean that CRAFT was improved the layout effectively. The result of simulation showed the manufacturing lead time of the improved layout decreased 23 minutes. Layout evaluation using Adjacency Based Scoring for the CRAFT layout increase 15% compare with the initial layout so it was selected as the best layout. This study concluded that combined use of computerized layout design algorithms provides better result,
Integrated modeling of multi-field assets, from subsurface to market, is challenging due to the complexity of the problem. This paper is an extension of the SPE 121252, model based integration and optimization gas cycling benchmark [Juell, et al., 2009], extending two gas-condensate fields to two full-field multi-well models. Additionally, a full-field model is added to the Juell benchmark, introducing an oil field undergoing miscible WAG injection, where most data are taken from the SPE 5 Reservoir Simulation Comparative Project. All reservoir models are compositional, but using different EOS representations. A base case scenario is defined with fixed numbers and locations of producers and injectors. A common field-wide surface processing facility is modeled with emphasis on water handling, NGL extraction, sales-gas spec, and gas reinjection. The surface process model interacts with the three reservoir models through two main mechanisms-(1) water-and gas-handling constraints, and (2) distribution of available produced gas for reinjection into the three reservoirs. The field asset model provides long-term production forecasts of gas, oil, and NGL revenue. Cost functions are introduced for all major control variables (number of wells, surface facility selection and operating conditions, injection gas composition). Net present value is used as the target objective function. This paper will evaluate optimal production strategies for the base case benchmark problem, using several key control variables and field operational constraints. Optimization performance will be tested with a few solver algorithms. The benchmark will be provided to the industry through application data files, network infrastructure, and results from our integrated optimization model.
Safety and security are a priority in an aviation industry that is very mindful because it is crucial. In order to achieve that virtue, there are some things that must be noticed by the airline in supporting safety and security is the maintenance system which pays attention to the profanation of an aircraft to operate and A pilot simulator to prepare physical and mental pilot readiness in all natural situations and conditions while minimizing the risk of falling planes, two factors affecting the pilot’s performance in operating the aircraft Will reduce the accident rate significantly and can improve the pilot’s ability to deal with problems in the field through certain simulations related to these problems. This research aims to study flight readiness in terms of feasibility control by maintenance system and pilot readiness in the face of emergencies and decision making in crucial situation. This research uses a regression method whereby the data retrieval technique uses the questionnaire with the target of the pilot respondent of the airline Garuda Indonesia. The result of analysis Acquired linear equation multiple regression Y = 0.754+0.383X1+0.398X2, R is obtained at 0.518.
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