A forward modeling approach for interpreting impeller flow logs.

IF 2.2
Ground water Pub Date : 2010-01-01 Epub Date: 2009-07-24 DOI:10.1111/j.1745-6584.2009.00600.x
Alison H Parker, L Jared West, Noelle E Odling, Richard T Bown
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引用次数: 20

Abstract

A rigorous and practical approach for interpretation of impeller flow log data to determine vertical variations in hydraulic conductivity is presented and applied to two well logs from a Chalk aquifer in England. Impeller flow logging involves measuring vertical flow speed in a pumped well and using changes in flow with depth to infer the locations and magnitudes of inflows into the well. However, the measured flow logs are typically noisy, which leads to spurious hydraulic conductivity values where simplistic interpretation approaches are applied. In this study, a new method for interpretation is presented, which first defines a series of physical models for hydraulic conductivity variation with depth and then fits the models to the data, using a regression technique. Some of the models will be rejected as they are physically unrealistic. The best model is then selected from the remaining models using a maximum likelihood approach. This balances model complexity against fit, for example, using Akaike's Information Criterion.

一种解释叶轮流动测井曲线的正演建模方法。
提出了一种严谨实用的方法来解释叶轮流动测井数据,以确定水力导电性的垂直变化,并将其应用于英国白垩含水层的两口井测井。叶轮流量测井包括测量泵井中的垂直流速,并利用流量随深度的变化来推断流入井中的位置和大小。然而,测量的流量测井数据通常是有噪声的,当采用简单的解释方法时,会导致虚假的水力导电性值。本文提出了一种新的解释方法,首先定义了一系列的水导率随深度变化的物理模型,然后利用回归技术将模型拟合到数据中。一些模型将被拒绝,因为它们在物理上是不现实的。然后使用最大似然方法从剩余的模型中选择最佳模型。这平衡了模型的复杂性和拟合,例如,使用赤池的信息标准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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