The Methodological Research Of Reservoir Stochastic Modeling

How to evaluate the effect of modern technology of reservoir description in exploration and development, this mainly based on whether what we know about reservoir match what it is. Ten-year practice of reservoir description indicate: if we want to establish objective 3-dimension geological model of reservoir, the different reservoir type, the different exploration and development phase, the different data quantity and quality decide what technical route of reservoir description we should apply.Doing the deep discussion about the method of sequential indicator stochastic simulation and annealing stochastic simulation on the foundation of study of predecessor in this paper. More and more people applied the method of stochastic simulation to heterogeneous modeling of reservoir. And each method is different from others such as basal principle, extent of complex, applied condition and so on. They all have their own applicability, advantages and disadvantages.The method of sequential indicator stochastic simulation firstly make the geological information discretization code, normally two indicator variables of 0 and 1. Then make the Kriging theory act on the variables to get the Kriging estimation of indicator variables, namely estimation of probability distribution of the variables in a unknown position. Define a random route, which pass through all the grid node, on the condition of given n conditional datum, get a value on the first grid node from the conditional distribution of stochastic variable, Add the new value into the conditional datum as a new conditional data. On the condition of current n+1 conditional datum, get a new value from conditional distribution of stochastic variable on the next node again. Then continue until all the nodes gets own value. In the course of simulation, the model has no relation to Kriging method, it only use the matrix information of covariance or variogram. So it can conquer the disadvantage that Kriging method smooth the geological parameters, and fit the numerical simulation for the geological parameters such as permeability whose values change quickly and largely. It can estimate the distribution of extra high value and extra low value of permeability more perfectly and more accurately, which the geologist and field engineer mainly care for.Simulated annealing algorithm is a kind of heuristic Monte Carlo method. In the course of solve the optimum problem, it conquer the blindfold searching mechanism of normal Monte Carlo method, and based on a appointed theory to guides search, so it can ensure a successful search. In the course of searching the optimum solution, it can accept a value make objective function good, but also a bad one. In this way it will avoid falling into a local extremum and get a global optimum value. At the same time, it can almost fulfill any statistical request. Just about its advantages, try to solve the optimum problem of reservoir modeling by it to searching better solution.