New Curve Fitting Method for Petroleum Engineering Applications - Mohd Rosli, Muhammad Aizuddin (Universiti Teknologi PETRONAS, 2014)
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.