Simulated annealing is a numerical algorithm that can be used to impose statistical structures on numerical grids representing heterogeneous rock or sediment. In this paper, we use the flexibility of simulated annealing to generate grids with Markov statistical structures. Our purpose is to transmit the rich geological information captured in Markov statistics into stochastic grids while maintaining the flexibility of annealing to honor field data. Performance issues that compromise annealing grids imbued with Markovian properties include scales of bedding or rock bodies relative to grid size, and the amount of geological complexity in the embedded Markov structures. The remedies to these issues include proper selection of grid size, careful choice of annealing type, and consideration of an alternative annealing stopping rule based on a chi-squared test statistic. If performance issues are overcome, complex stratal patterns such as higherorder dependency, cyclicity, and directionality can be replicated in grids by this method. In addition, accounting for variations in depositional rate allows for transference of Markov structures obtained from vertical boreholes to the horizontal dimension when other information is lacking. A field example using borehole data collected at the Gloucester special waste site near Ottawa, Canada, as well as synthetic examples, demonstrate the technique and performance issues.
The evaluation of well yields conventional timedrawdown methods is based on the assumption of infinite-acting radial flow (IARF) of groundwater to a well. However, long-term well yields are controlled by heterogeneities and, as suggested here, by the presence of linear features and aquitard leakage, and the subsequent departures from IARF. Accurate prediction of long-term well yields therefore requires an evaluation of aquifer heterogeneities. Derivative techniques combined with aquifer geology and conventional methods aid in the evaluation of long-term well yields in the heterogenous aquifers. Our case study involves the estimation of long-term well yields from relatively short-term aquifer tests in an aquifer near Calgary, Alberta. The wells are completed in a gravel-floored cahnnel incised into bedrock. On the regional scale, the floor gravels appear to form a continuous and homogeneous aquifer. Aquifer-test responses indicate internal heterogeneity at a scale below the resolution attainable with the available well control. Reliable estimates of aquifer parameters are obtained by applying a derivative technique to the analysis of timedrawdown data. Derivative analysis allows us to isolate test segments for which the assumption of IARF is valid. Characteristic timedrawdown and derivative curves are then integrated with geology to identify the nature of heterogeneities and assess their impact on long-term aquifer response to pumping. Key words: aquifer-test, derivative, heterogeneity, well yield, buried valley aquifer.
Ground‐water chemistry data from wells are cokriged with ground conductivity measurements to quantitatively describe ground‐water chemical quality at a site. The cokriged estimates are shown to be superior to both simple rescaling of ground conductivity by a linear regression model and to interpolation of ground‐water chemistry data from wells using ordinary kriging. By extending the use of geophysical measurements in this way, significant cost savings in site assessment can be realized and the geophysics will have more data “worth.”
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