We evaluated the effect of various error sources in fishery harvest/effort data on the maximum sustainable yield （MSY） and corresponding fishing effort （EMsv） using Monte Carlo simulation analyses. A high coeffici...We evaluated the effect of various error sources in fishery harvest/effort data on the maximum sustainable yield （MSY） and corresponding fishing effort （EMsv） using Monte Carlo simulation analyses. A high coefficient of variation （CV） of the catch and effort values biased the estimates of MSY and EMsv. Thus, the state of the fisheries resource and its exploitation was overestimated. We compared the effect using three surplus production models, Hilborn-Waters （H-W）, Schnute, and Prager models. The estimates generated using the H-W model were significantly affected by the CV. The Schnute model was least affected by errors in the underlying data. The CVof the catch data had a greater impact on the assessment than the CV of the fishing effort. Similarly, the changes in CV had a greater impact on the estimated maximum sustainable yield （MSY） than on the corresponding estimate of fishing effort （EMsY）. We discuss the likely effect of these biases on management efforts and provide suggestions for the improvement of fishery evaluations.展开更多
Nine targets which stand both for the static characteristic of produced formations and the dynamic parameter of wells including the average permeability,variation coefficient of permeability,moving capability,remainin...Nine targets which stand both for the static characteristic of produced formations and the dynamic parameter of wells including the average permeability,variation coefficient of permeability,moving capability,remaining recoverable reserves,coefficient of flooding,daily oil production,increasing rate of water cut,cumulative liquid production per unit meter and efficiency index of oil production are selected as the evaluation indexes,a novel model to evaluate the porous formations in long-term waterflooding sand reservoir was established by using the support vector machine and clustering analysis. Data of 57 wells from Shentuo 21 block Shengli oilfield was analyzed by using the model. Four kinds of formation groups were gained. According to the analysis result,different adjustment solutions were put forward to develop the relevant formations. The Monthly oil production increased 7.6 % and the water cut decreased 8.9 % after the adjusted solutions. Good results indicate that the learning from this method gained will be valuable adding to other long-term waterflooding sand reservoirs in Shengli oilfield and other similar reservoirs worldwide.展开更多
基金Supported by the National Natural Science Foundation for Young Scientists of China (No. 40801225)the Natural Science Foundation of Zhejiang Province (No. Y3090038)
文摘We evaluated the effect of various error sources in fishery harvest/effort data on the maximum sustainable yield （MSY） and corresponding fishing effort （EMsv） using Monte Carlo simulation analyses. A high coefficient of variation （CV） of the catch and effort values biased the estimates of MSY and EMsv. Thus, the state of the fisheries resource and its exploitation was overestimated. We compared the effect using three surplus production models, Hilborn-Waters （H-W）, Schnute, and Prager models. The estimates generated using the H-W model were significantly affected by the CV. The Schnute model was least affected by errors in the underlying data. The CVof the catch data had a greater impact on the assessment than the CV of the fishing effort. Similarly, the changes in CV had a greater impact on the estimated maximum sustainable yield （MSY） than on the corresponding estimate of fishing effort （EMsY）. We discuss the likely effect of these biases on management efforts and provide suggestions for the improvement of fishery evaluations.
基金supported by funds from the Key Pro-ject of Chinese National Programs for Fundamental Research and Development (863 Program) under thenumber 2007AA090701the Young and Mid-dle-aged Researchers Innovation and Technology Foun-dation of CNPC under the number 04E7029
文摘Nine targets which stand both for the static characteristic of produced formations and the dynamic parameter of wells including the average permeability,variation coefficient of permeability,moving capability,remaining recoverable reserves,coefficient of flooding,daily oil production,increasing rate of water cut,cumulative liquid production per unit meter and efficiency index of oil production are selected as the evaluation indexes,a novel model to evaluate the porous formations in long-term waterflooding sand reservoir was established by using the support vector machine and clustering analysis. Data of 57 wells from Shentuo 21 block Shengli oilfield was analyzed by using the model. Four kinds of formation groups were gained. According to the analysis result,different adjustment solutions were put forward to develop the relevant formations. The Monthly oil production increased 7.6 % and the water cut decreased 8.9 % after the adjusted solutions. Good results indicate that the learning from this method gained will be valuable adding to other long-term waterflooding sand reservoirs in Shengli oilfield and other similar reservoirs worldwide.
