Ensemble Kalman filter dynamic reservoir history matching method based on hyper-sphere transformation
A Kalman filter and history matching technology, applied in the field of oil field development, can solve problems such as difficulty and uncertainty, large model freedom, time-consuming and labor-intensive problems, and achieve the effects of rapid absorption, improved accuracy, and shortened calculation cycle
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[0013] The ensemble Kalman filter reservoir dynamic history fitting method based on hypersphere transformation of the present invention includes:
[0014] Step S1: Initialize the set of reservoir models.
[0015] The set of reservoir models formed by initialization is:
[0016]
[0017] where x n,j means at time t n The jth set element of the state vector of . m s and m d are static parameters and dynamic parameters respectively; among them, the static parameters include the permeability and porosity of each grid of the reservoir model, and the dynamic parameters include the water saturation and pressure of each grid of the reservoir model; d is the production data of the oil well, Including bottom hole pressure, well oil production and oil well water production.
[0018] Static parameters, dynamic parameters and oil well production data constitute state variables, the vectors composed of state variables are state vectors, and the matrix composed of all state vectors ...
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