A 3D fracture network reconstruction method based on microseismic events
LIU Xing1, JIN Yan1, LIN Botao1, XIANG Jianhua2, ZHONG Hua2
1. College of Petroleum Engineering, China University of Petroleum(Beijing), Beijing 102200, China; 2. Southwest Oil & Gas Field Company, PetroChina, Chengdu, Sichuan 610065, China
Abstract：Previous research mainly focused on building 2D fracture models from the point view of qualitative and macroscopic.Microseismic events were often used to deprive some critic parameters to calibrate random discrete fracture model based on certain assumptions.As a result,there is a lack of robust methods to build 3D fracture network after fracturing.To solve this problem,we firstly apply the random sample consensus (RANSAC) method to detect fracture planes according to the geometric correlation between microseismic events and real fracture networks.After that,we develop a computing algorithm called robust 3D fracture reconstruction (RFM3D) to reconstruct 3D fracture network on the basis of building realistic single fracture geometric model.To verify the robustness and effectiveness of the algorithm,we put forward average distance index (ADI) to evaluate the similarity between two fracture networks.Also,analog events generated by Monte Carlo simulation added in noise points of different proportions are used to test the algorithm.The results show that:①Convex polygons can be used to describe real fracture geometric shape after fracturing experiments; ②RFM3D is easy to adapt different complex geometric models.It can eliminate effects of 10% noise and give a relatively accurate reconstruction of 3D fracture network under normal circumstances.Therefore,it has good robustness; ③The fracture network similarity index (ADI) increase with noise ratio in a logistic pattern and critical ADI value decreased with increase of noise ratio.Accordingly,it is necessary to eliminate noise in events under 10% to obtain an accurate and robust fracture network reconstruction.
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