Discretization, Simulation, and Swanson’s (Inaccurate) Mean
نویسنده
چکیده
Original SPE manuscript received for review 5 October 2010. Revised manuscript received for review 3 February 2011. Paper (SPE 148542) peer approved 15 March 2011. Summary Swanson’s mean (SM) is heavily used within the oil and gas industry to approximate continuous probability distributions such as the log-normal. In this paper, we document the errors induced by this practice, which, as we show, has no theoretical justification for any distribution other than the normal. In parallel, we review methods to discretize continuous distributions and compare these methods to Monte Carlo (MC) simulation. We demonstrate that the best discretization methods have an accuracy equivalent to that of tens of thousands of MC trials.
منابع مشابه
On the Reduction of Optimization Time in Simulation of Oil Reservoirs
Thermal recovery techniques including Fast-SAGD process increases the production efciency of heavy oil reservoirs. Effective parameters in this study included injection and production rates, height of the injection, production, and offset wells, production and injection cycles, and pressure of the offset wells. In this study, optimization studies were performed. The objective function was defned a...
متن کاملA Thermobaric Instability of Lagrangian Vertical Coordinate Ocean Models
Lagrangian(and isopycnic-) vertical coordinate ocean models are subject to an exponentially growing numerical instability in weakly stratified regions when thermobaricity is not accurately compensated. Inaccurate compensation for compressibility in the pressure gradient terms leads to pressure gradient truncation errors (due to the vertical discretization) that can drive the Lagrangian coordina...
متن کاملError Bounds in Parameter Estimation Under Mismatch
In this paper we develop a new upper bound for the mean square estimation error of a parameter that takes values on a bounded interval. The bound is based on the discretization of the region into a finite number of points, and the determination of the estimate by a maximum likelihood procedure. It is assumed that inaccurate versions of the true spectra are utilized in the implementation of the ...
متن کاملSwanson’s non-Hermitian Hamiltonian and su(1,1): a way towards generalizations
The family of metric operators, constructed by Musumbu et al (2007 J. Phys. A: Math. Theor. 40 F75), for Swanson’s PT -symmetric Hamiltonian, is re-examined in the light of an su(1,1) approach. An alternative derivation, only relying on properties of su(1,1) generators, is proposed. Being independent of the realization considered for the latter, it opens the way towards the construction of gene...
متن کاملA Hybrid Vector Wiener Filter Approach to Translational Super-Resolution
We address the problem of purely-translational super-resolution (SR) for signals in arbitrary dimensions. We show that discretization, a key step in many SR algorithms, inevitably leads to inaccurate modeling. Instead, we treat the problem entirely in the continuous domain by modeling the signal as a continuous-space random process and deriving its linear minimum mean-squared error (LMMSE) esti...
متن کامل