No abstract

No abstract

Objective: The purpose of this thesis was to investigate the inter-rater reliability of the McKenzie System of Mechanical Diagnosis and Therapy (MDT) when classifying patients with musculoskeletal knee pain using clinical vignettes. Methods: This study was divided into two phases. First, ten clinicians experienced in the use of MDT were randomly recruited to write a total of 60 clinical vignettes based upon the initial assessment of past patients with knee pain. Second, six different MDT raters were recruited to rate 53 selected vignettes and reliability was determined using Fleiss Kappa. Results: There was "substantial agreement" among six MDT raters classifying the clinical vignettes into one of four categories (kappa=0.72). There was no statistically significant difference between therapists with different levels of training. Significance: These findings indicate that the McKenzie System of MDT is a reliable method of classifying patients presenting with musculoskeletal knee pain when using clinical vignettes.

It is widely accepted that unconventional resources hold enormous reserve potential. However, complex fluid flow physics and completion/stimulation practices pose a unique challenge in estimating reserves or making long-term production forecast for these unconventional reservoirs, as traditional methods are most often not applicable. This paper proposes the application of a probabilistic reservoir simulation workflow to provide realistic range of production forecasts with successful application in the Bakken unconventional tight oil reservoir. First, geomodels are constructed and ranked. Then, key static and dynamic uncertainty parameters are identified for the subsequent history-matching study (with each of the geomodel realizations) that provides not only production forecast for individual wells but also parameter ranges for experimental design (DoE) for field-level prediction. Then, DoE simulations are conducted to construct proxy equations that are used in Monte-Carlo simulations to generate Low-BTE-High response S-curves for the field-level models. Finally, based on these S-curve results, Low-BTE-High deterministic reservoir simulation models are constructed to generate corresponding long-term production forecast profiles for full-field development and optimization.

No abstract