The Membrane‐Interface Probe and Hydraulic Profiling Tool (MiHpt) is a direct push probe that includes both the membrane interface probe (MIP) and hydraulic profiling tool (HPT) sensors. These direct push logging tools were previously operated as separate logging systems for subsurface investigation in unconsolidated formations. By combining these two probes into one logging system the field operator obtains useful data about the distribution of both volatile organic contaminants (VOCs) and relative formation permeability in a single boring. MiHpt logging was conducted at a chlorinated VOC contaminated site in Skuldelev, Denmark, to evaluate performance of the system. Formation cores and discrete interval slug tests are used to assess use of the HPT and electrical conductivity (EC) logs for lithologic and hydrostratigraphic interpretation. Results of soil and groundwater sample analyses are compared to the adjacent MiHpt halogen specific detector (XSD) logs to evaluate performance of the system to define contaminant distribution and relative concentrations for the observed VOCs. Groundwater profile results at moderate to highly contaminated locations were found to correlate well with the MiHpt‐XSD detector responses. In general, soil sample results corresponded with detector responses. However, the analyses of saturated coarse‐grained soils at the site proved to be unreliable as demonstrated by high RPDs for duplicate samples. The authors believe that this is due to pore water drainage observed from these cores during sampling. Additionally, a cross section of HPT pressure and MiHpt‐XSD detector logs provides insight into local hydrostratigraphy and formation control on contaminant migration.

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KEYWORDS: O&D revenue management, seat inventory control, multistage stochastic programming, scenario tree generation Origin and destination (O&D) revenue management (RM), either leg-based or PNR based, has become a standard in the airline industry. This paper presents a new approach to O&D RM which does not make any assumptions on demand distributions or on the correlations of the booking process. Protection levels are determined for all origin-destination itineraries, fare classes, points of sale and data collection points (DCPs), and for a variety of demand patterns over the complete booking period. This approach to the seat inventory problem is modelled as a multistage stochastic program, where its stages correspond to the DCPs of the booking horizon. The stochastic passenger demand process is approximated by a scenario tree generated from historical data by a recursive scenario reduction procedure. The stochastic program represents a specially structured large scale linear program (LP) that may be solved by standard LP software (eg CPLEX). Preliminary numerical experience is reported.

Airline revenue management, Seat inventory control, Multistage stochastic programming, Scenario tree generation,