http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Pressure transient testing and productivity analysis for horizontal wells
This work studied the productivity evaluation and well test analysis of horizontal wells. The major components of this work consist of a 3D coupled reservoir/wellbore model, a productivity evaluation, a deconvolution technique, and a nonlinear regression technique improving horizontal well test interpretation. A 3D coupled reservoir/wellbore model was developed using the boundary element method for realistic description of the performance behavior of horizontal wells. The model is able to flexibly handle multiple types of inner and outer boundary conditions, and can accurately simulate transient tests and long-term production of horizontal wells. Thus, it can serve as a powerful tool in productivity evaluation and analysis of well tests for horizontal wells. Uncertainty of productivity prediction was preliminarily explored. It was demonstrated that the productivity estimates can be distributed in a broad range because of the uncertainties of reservoir/well parameters. A new deconvolution method based on a fast-Fourier-transform algorithm is presented. This new technique can denoise "noisy" pressure and rate data, and can deconvolve pressure drawdown and buildup test data distorted by wellbore storage. For cases with no rate measurements, a "blind" deconvolution method was developed to restore the pressure response free of wellbore storage distortion, and to detect the afterflow/unloading rate function using Fourier analysis of the observed pressure data. This new deconvolution method can unveil the early time behavior of a reservoir system masked by variable-wellbore-storage distortion, and thus provides a powerful tool to improve pressure transient test interpretation. The applicability of the method is demonstrated with a variety of synthetic and actual field cases for both oil and gas wells. A practical nonlinear regression technique for analysis of horizontal well testing is presented. This technique can provide accurate and reliable estimation of well-reservoir parameters if the downhole flow rate data are available. In the situation without flow rate measurement, reasonably reliable parameter estimation can be achieved by using the detected flow rate from blind deconvolution. It has the advantages of eliminating the need for estimation of the wellbore storage coefficient and providing reasonable estimates of effective wellbore length. This technique provides a practical tool for enhancement of horizontal well test interpretation, and its practical significance is illustrated by synthetic and actual field cases.
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nonlinear regression for well test analysis