TESTING GEOLOGIC HYPOTHESES THROUGH MULTIPLE WORKING CONSTRAINTS

Geologic sciences and technologies have long borne particularly difficult burdens in validating conceptual models and theories. Karl Popper proposed that the distinction between science and non-science is the ability to design experiments that have the potential to falsify a hypothesis. Truth can never be demonstrated in the absolute, but one gains confidence through varied experiments that fail to falsify the hypothesis. Unfortunately, the experiments that would potentially falsify many geologic hypotheses may not exist due to the scale of space and time that would be necessary. This weakness in geology as compared with other sciences is particularly acute when critical public issues, such as radioactive waste disposal, involve geologic hypotheses that are very difficult to test.

Increasingly, the testing of geologic hypotheses is coming to rely on numerical experimentation. This is particularly true for groundwater models. Often the hypothesis test, or validation, relies on the matching of simulation results to field measurements. Using examples from well testing, this presentation will show how multiple geometric and parametric models can be fitted equally well to same data sets. Although some well test responses are associated with porous media or fracture flow, or with specific geometries or processes such as dual porosity, the models are highly non-unique. Choosing among the possible hypotheses or conceptual models requires additional constraints from geologic, geochemical, or geophysical sources. Just as geologists in the past came to rely on multiple working hypotheses, geologic hypothesis testing through numerical simulation may come to rely on multiple working constraints from independent lines of evidence.