Method of controlling well bore pressure based on model prediction control theory and systems theory

摘要

A method for controlling well bore pressure based on model prediction control theory and systems theory, includes: detecting a well bottom pressure, a stand pipe pressure, a casing pressure, an injection flow rate and an outlet flow rate during the drilling operation process and determining the presence of overflow or leakage; if there is no overflow or leakage, then fine-adjusting the wellhead casing pressure according to the slight fluctuations of the well bottom pressure, the stand pipe pressure or the casing pressure; if there is overflow or leakage, simulating and calculating the overflow or leakage position and starting time of the overflow or leakage, predicting the variation over a future time period of the well bore pressure in the well drilling process, and utilizing an optimization algorithm to calculate the control parameter under a minimum of an actual well bottom pressure difference during the future period.

主权项

1. A method implemented with a controller coupled with memory devices having instructions code stored thereon for controlling well bore pressure, the controller including a computer equipped with capability for processing algorithms, evaluating polynomials and computing mathematical equations included with the stored instructions, wherein the instructions when executed by the computer, implement the method steps, comprising:
detecting a well bottom pressure, a stand pipe pressure, a vertical casing pressure, an injection flow rate and an outlet flow rate during construction process; determining presence of overflow or leakage; if there is no overflow or leakage, then fine-adjusting the wellhead casing pressure according to a difference values between the well bottom pressure, the stand pipe pressure, the casing pressure and target pressures thereof, or the slight fluctuations of the well bottom pressure, the stand pipe pressure, or the casing pressure, so as to ensure that the well bottom pressure, the stand pipe pressure, or the casing pressure are at set values, wherein adjusting amount is optimized according to a conventional model prediction control algorithm, so as to calculate a control objective parameter of a next moment; if there is overflow or leakage, then using a well bore single-phase or multi-phase flow dynamic model to simulate and calculate the overflow or leakage position and starting time of the overflow or leakage, predicting the variation over a future time period of the well bore pressure in the well drilling process, and utilizing an optimization algorithm to calculate the control parameter under a minimum of an actual well bottom pressure difference during a future period; and repeating the optimization process for the next time period after a first control parameter is selected and set; (1) wherein a prediction control equation of the single-phase or multi-phase flow dynamic model is expressed by the following formula:{x→=fR⁡[x→⁡(t),u⁡(t),Δ⁢⁢QKL]y⁡(t)=gR⁡[x→⁡(t)]+ey,(1) wherein fR[•], gR[•] respectively represent well bore pressure system, a computing model thereof is calculated by theoretical formula of hydraulic single-phase flow and multi-phase flow; {right arrow over (x)}(t) represents a state vector at a moment of t, including the casing pressure; u(t) represents the casing pressure at the moment of t; y(t) represents the well bottom pressure at the moment of t; and ey represents an error of the well bottom pressure; (2) wherein an error between an actual measurement casing pressure and a prediction calculation casing pressure is a prediction error e(k+i),
wherein e(k+i)=yp(k)−yM(k)  (3) wherein yM(k) is an output value of a moment k; yp(k) is an actual measurement value of the moment k; (3) wherein a predicted value e(k+i) at a moment n+i in the future is estimated by a polynomial error fitting method based on values at a given moment, wherein the predicted value e(k+i) comprises an error at a moment k and a revised error, wherein during this process (L>l2>1), and when L=l2e⁡(k+i)=⁢e⁡(k)+∑i=1l2⁢el⁡(n)⁢il=⁢yp⁡(k)-yM⁡(k)+∑i=1l2⁢βl⁡(n)⁢il(4)(i=1,2,3,…⁢,L) wherein e(k) is an error at the moment k; β1(k) is a coefficient of a fitting polynomial; l2 is expanded orders of the fitting polynomial.