The Study And Application Of Smart Well Pattern Optimization

Nowadays, more and more attentions have been paid to well pattern optimizationconsidering the decisive effect a proper well pattern may bring. The well pattern designalways occupies the top position during oil-field development process. Inappropriate designof well pattern could result in uncounted loss to the oil field, considering the amount ofmoney a well could cost, and the well design is not a new but always a challenging project.For a long time, people count partly on human experience and partly on numericalsimulations when they decide the well location. Usually, many development plans areproposed and simulated, and then a preferred program is chosen for reservoir development.However, this kind of methods can’t provide the suitable optimal well pattern layout fordifferent geological reservoirs. In recent years, well placement theories combiningoptimization algorithm with reservoir simulations are put forward frequently. These theoriesare mostly applied in a situation with a small amount of wells. For numerous wells in alarge-scale reservoir, it is of great importance to pursue the optimal well pattern in order toobtain maximum economic benefits.In this paper, the objective is aiming at solving the problem of optimization of regularwell pattern for large-scale reservoir development. It is divided into constrained andunconstrained well pattern optimization according to whether there are drilled wells in thereservoir. Firstly, as for the unconstrained well pattern optimization, based on the definition ofwell pattern by Onwunalu, a new construction form and computing solution is proposed forwell pattern,6variables (length, width, rotation angle, shearing angle, horizontal-shifting,vertical-shifting) are developed to describe the well pattern units. These variables are able torealize the rotating, scaling, shifting and shearing regardless of the well pattern for ms.Furthermore, optimal well pattern depends on not only the unit form but also the productioncontrol which is reflected in a new variable-total injection-production rate. Secondly, when it comes to constrained well pattern optimization, by taking full advantage of the properties ofDelaunay Triangulation, the construction of triangular adaptive well pattern under theconstraints of boundaries, faults and existing wells can be easily obtained and the number ofcontrol variables is greatly decreased in the optimization process. Finally, several detailedoptimization results are presented for homogeneous and heterogeneous reservoir cases usingthe above well generating method respectively which confirm the validity of the two wellpattern construction methods. Meanwhile, the whole well pattern optimization method is alsoproved to be efficient and reliable.