LAPLACE TRANSFORM DECONVOLUTION AND ITS APPLICATION TO WELL TEST DATA ANALYSIS

The primary objective of this project is to extend the conveniences of
deconvolution to non-linear problems of fluid flow in porous media. Unlike
conventional approaches, which are based on an approximate linearization of the
problem, here the solution of the non-linear problem is linearized by a perturbation
approach, which permits term-by-term application of deconvolution. Because the
proposed perturbation solution is more conveniently evaluated in the Laplacetransform domain and the standard deconvolution algorithms are in the time-domain,
an efficient deconvolution procedure in the Laplace domain is a prerequisite.
For this research objective, a new algorithm is introduced which uses inverse
mirroring at the points of discontinuity and adaptive cubic splines to approximate rate
or pressure versus time data. This algorithm accurately transforms sampled data into
Laplace space and eliminates the Numerical inversion instabilities at discontinuities
or boundary points commonly encountered with the piece-wise linear approximations
of the data.
Applying the algorithm to the field data obtained from published works, we can
unveil the early-time behavior of a reservoir system masked by wellbore-storage
effects. The wellbore-storage coefficient can be variable in the general case. The new
method thus provides a powerful tool to improve pressure-transient-test
interpretation.
Practical use of the algorithm presented in this research has applications in a
variety of Pressure Transient Analysis (PTA) and Rate Transient Analysis (RTA)
problems. A renewed interest in this procedure is inspired from the need to evaluate
production performances of wells in unconventional reservoirs. With this approach, we could significantly reduce the complicating effects of rate variations or shut-ins
encountered in well-performance data