New Curve Fitting Method for Petroleum Engineering Applications

Data collected in petroleum engineering industry may come in a non-distribution
form. Usually the data is really important for the approximation and future prediction
purposes. It may lead to the increasing of time and cost if wrong prediction happened.
So, to avoid the problems that may occurred, the best fit is needed to represent the data.
Curve fitting is the process of creating a curve or mathematical function that will
produce the best fit to a series of data points. It usually uses to design and control the
shape of complex curves and surfaces. There are several of methods of approximat ion
has been introduced such are Polynomial, Gaussian, Sine, Fourier Series and Smoothing
Spline but unfortunately not yet meet the high expectations. For example, Polynomial
approach in the algorithm which contains strongly oscillating properties and huge
number of arithmetical operations for computations. Unsuitable type of curve fitting
may destroy the original feature of the data. This research is about the invention of new
curve fitting method that combined two interpolation method which are Cubic Spline
and Piecewise Cubic Hermite Interpolation Polynomial (PCHIP) with the reduction of
data method. This research will show the comparison between the new curve fitting
method and the existing method by applying it to several sets of petroleum engineering
data.