储层重力密度反演后验约束正则化方法

本文针对蒸汽辅助重力泄油(SAGD)生产中开发监测问题, 发展了综合应用地震及重力数据反演储层密度的联合反演算法.通过测井数据建立纵波阻抗与密度的直接关系, 并推导出这种关系下重力与纵波阻抗数据联合反演的计算方法, 从而计算出蒸汽腔体密度分布规律.文中应用密度反演后验约束正则化方法, 采用Tikhonov正则化模型, 通过波阻抗数据作为约束进行联合反演, 在算法上提高了稳定性, 同时得到较高的反演精度.文中对SAGD生产中的理论模型进行了方法试算, 并分析了算法的误差, 最终应用于SAGD生产的实际数据中, 通过最终反演结果分析, 该方法取得了很好的应用效果.

The posterior constrained regularization method for reservoir density inversion

We present the result of a seismic and gravity joint reservoir density inversion algorithm applied to monitoring the process of steam assisted gravity drainage (SAGD). The method can be used to analyze the density distribution of steam chambers in SAGD in the case of combination of the single well with horizontal wells.Gravimetric density and seismic impedance are combined as a posteriori constraint to formulate the Tikhonov regularization model. Minimization of the Tikhonov regularization model can yield a reasonable inversion result of the density distribution of steam chambers in SAGD. First, a regression model of the seismic impedance and the density through well logging data is built, which can be used to calculate the density constraint data through the seismic P wave data and gives the density constraint. Then, an optimization model based on L2 norm is established. In solving the minimization model, Euler equations along with proper choice of the regularization parameter are simultaneously solved. Utilizing the micro-gravimetric Bouguer gravity anomaly data, the joint inversion scheme based on seismic impedance data and gravimetric data is performed, which yields the density distribution of the reservoir. By analyzing properties of the reservoir density, the density distribution of steam chambers in SAGD can be drawn.Faced with the problem of development and monitoring during SAGD production, this paper investigates the joint inversion method based on the seismic and gravimetric data. The results obtained are as follows: (1) applying the P wave data as a constraint to invert the gravimetric density is proposed; (2) a posteriori regularization method is utilized to calculate the density, in particular, a posteriori choice of the regularization parameter is performed; (3) a quadratic regression model is built for the seismic impedance and the density, theoretical and field data applications reveal that the joint inversion algorithm is stable and can yield high precision of inversion results; (4) it is shown from the field data applications using our joint inversion method that the inverted low density distribution area coincides well with the known well gas injection position, and the connectivity of the low density area is similar to the forward model, hence proves the feasibility of the joint inversion algorithm in practice. We also remark that the joint inversion method relies on the proper initial model and high SNR data; this may be a requirement for practical usage of the joint inversion method.For the development and monitoring problem of SAGD production, we develop a joint inversion method based on the seismic data and gravimetric data. Using a posteriori choice of the regularization parameter and a quadratic regression model for the seismic impedance and the density, an inversion procedure is performed by solving an Euler equation. The inversion results can well explain and draw the density distribution of steam chambers in SAGD.