Geotechnology for low-permeability gas reservoirs, 1995

The permeability, and thus the economics, of tight reservoirs are largely dependent on natural fractures, and on the in situ stresses that both originated fractures and control subsequent fracture permeability. Natural fracture permeability ultimately determines the gas (or oil) producibility from the rock matrix. Therefore, it is desirable to be able to predict, both prior to drilling and during reservoir production, (1) the natural fracture characteristics, (2) the mechanical and transport properties of fractures and the surrounding rock matrix, and (3) the present in situ stress magnitudes and orientations. The combination of activities described in this report extends the earlier work to other Rocky Mountain gas reservoirs. Additionally, it extends the fracture characterizations to attempts of crosswell geophysical fracture detection using shear wave birefringence and to obtaining detailed quantitative models of natural fracture systems for use in improved numerical reservoir simulations. Finally, the project continues collaborative efforts to evaluate and advance cost-effective methods for in situ stress measurements on core

Local contrast and Pavlovian induction

Two experiments examined the effects of number and similarity of stimuli on local contrast. In the first experiment, local contrast effects differed in magnitude as a function of the similarity among stimuli; greater positive local contrast appeared when stimuli were less similar, though this effect sometimes reversed for very dissimilar stimuli. In the second experiment, both positive and negative local contrast appeared transiently during the course of training a discrimination including two quite dissimilar stimuli. When two new stimuli were added, both effects reappeared in several cases. The effects remained when the discrimination was rendered more difficult by substituting a new stimulus very similar to one of the original pair. These and other data suggest that local contrast depends on the same factors that produce Pavlovian induction; in the absence of an alternative account, Pavlov's interpretation may be useful in suggesting further research that will help identify the mechanisms involved in both classical and operant discrimination learning

Behavior of humans in variable-interval schedules of reinforcement

During Phase I, human subjects pressed a button for monetary reinforcement in five variable-interval schedules, each of which specified a different frequency of reinforcement. The rate of responding was an increasing, negatively accelerated function of reinforcement frequency; the data conformed closely to Herrnstein's equation. During Phase II, the same five schedules were in operation, but in addition a concurrent variable-interval schedule (B) was introduced, responses on which were always reinforced at the same frequency. Response rate in component A increased while the response rate in B decreased, as a function of the reinforcement frequency in component A. Relative response rates in the two component schedules matched the relative frequencies of reinforcement. Comparing the absolute response rates in component A during Phase I and Phase II it was found that introduction of the concurrent schedule did not affect the value of the theoretical maximum response rate, but did increase the value of the reinforcement frequency needed to obtain any particular submaximal response rate