Seismic Reservoir Modeling. Dario Grana

Читать онлайн книгу.

Seismic Reservoir Modeling - Dario Grana


Скачать книгу
X, whose value is uncertain. In statistics, such a variable is called a random variable, or a stochastic variable. A random variable is a variable whose value is subject to variations and cannot be deterministically assessed. In other words, the specific value cannot be predicted with certainty before an experiment. Random variables can take discrete or continuous values. In geophysics, a number of subsurface properties, such as facies types, porosity, or P‐wave velocity, are considered random variables, because they cannot be exactly measured. Direct measurements are also uncertain, and the measurements should be treated as random variables with a distribution that captures the measurement uncertainty.

      

      1.3.1 Univariate Distributions

      Although the outcome of a discrete random variable is uncertain, we can generally assess the probability of each outcome. In other words, we can define the probability of a discrete random variable X by introducing a function pX : N → [0, 1], where the probability P(x) of an outcome x is given by the value of the function pX, i.e. P(x) = pX(X = x). The uppercase symbol generally represents the random variable, whereas the lowercase symbol represents the specific outcome. The function pX is called probability mass function and it has the following properties:

      for all outcomes xN; and

      In the continuous case, the probability of a continuous random variable X is defined by introducing a non‐negative integrable function fX : → [0, +∞]. The function fX is called probability density function (PDF) and must satisfy the following properties:

      (1.13)

      The PDF fX(x) is then used to define the probability of a subset of values of the random variable X. We define the probability of the outcome x being in the interval (a, b] as the definite integral of the PDF in the interval (a, b]:

      Example 1.2

      In this example, we illustrate the calculation of the probability of the random variable X to belong to the interval (2, 3], assuming that X is distributed according to the triangular PDF


Скачать книгу