Structures Imaging By Microseismic Scattered Waves

Hydraulic fracturing is an engineering tool to efficiently recover oil/gas from unconventional hydrocarbon reservoirs.By creating fractures in target reservoirs to improve low-permeability reservoirs,oil and gas can be more efficiently recovered from the reservoir.In the hydraulic fracturing process,high-pressure fluid is injected into the reservoir through fracturing wells,and the stress state in the subsurface changes,which in turn induces microseismic events.They may be recorded at seismic stations in the surface or along monitoring wells.The detected microseismic events are located and,based on their distribution,can be used to assess the development of induced fractures and the stimulated reservoir volume.It is generally believed that with more complete event detections and more accurate microsiesmic event locations,it is more accurate to assess the development of the fracture network and to estimate the stimulated reservoir volume.However,due to weak microseismic signal,it is difficult to detect microseismic events completely.In some cases,the occurrence of fractures may not be accompanied by the generation of microseismic events.Therefore,it is biased to describe the fracture distribution caused by hydraulic fracturing if only based on the distribution of microseismic events.For fractures generated by hydraulic fracturing,they act as a strong scatterer for incident seismic waves.Based on this,this paper proposes a new method to characterize the fracture distribution by applying the scattered waves in the microseismic waveforms to reverse-time migration.For a multi-stage hydraulic fracturing system,the fractures induced in the previous fracturing stages can serve as strong scatterers for the subsequent fracturing stages to generate the microseismic wavefield.As a result,the waveform of the microseismic event induced by the subsequent fracturing stages may include the scattered waves caused by the fractures belonging to previous stages.Therefore,by applying reverse-time migration method to microseismic waveforms,it is possible to describe the fracturing-induced fractures belong to previous stages and natural fractures.Based on a downhole microseismic monitoring system,a downhole microseismic reverse-time migration algorithm based on the acoustic wave equation was developed and the algorithm was tested based on the model.The imaging results from microseismic reverse-time migration may not only be affected by the microseismic monitoring system,but also may be interfered by the surrounding structures.For this reason,the target fracture zones may not be illuminated properly.To mitigate this issue,this paper proposes a target-oriented microseismic reverse-time migration method based on staining algorithm.By staining the target imaging area,it is possible to create an imaginary wavefield that is only related to themarked underground structure and its surrounding structure,so as to obtain an imaging result related only to the marked structure and its surrounding structure.Thus,this method improves the imaging illumination of the target fracture zones.The above-mentioned microseismic migration imaging methods are based on the acoustic wave equation,and it is required to back propagate the receiver wavefield and forward propagate the source wavefield and then cross correlate them to produce the imaging result.The imaging of underground structures is therefore affected by the source function and the radiation pattern.In order to eliminate the impact of seismic sources on imaging results,this paper further developed a microseismic reverse-time imaging algorithm based on the elastic wave equation.It only propagates the waveforms recorded on the stations along the opposite direction of time and applys the imaging condition to the separated P and S wave fields.This reverse-time imaging algorithm does not need to know the source location,source signature,and focal mechanism of the event,and can determine the source location and structures.In order to improve the resolution of imaging,this paper proposes a new imaging condition by dividing stations into groups to improve the energy focus of imaging.Compared with the auto-correlation/cross-correlation imaging conditions,the grouping imaging condition can better suppress the imaging noise caused by the lack of spatial sampling,and can better tolerate the sparse station distribution.Compared with the geometric-mean imaging condition,grouping imaging condition has lower requirements for data and does not easily generate unstable imaging results,and thus are more suitable for actual seismic data processing.Based on the synthetic and actual data,the paper tests the algorithm and finds the microseismic imaging algorithm based on the grouping imaging conditions can be used to locate the microseismic event and image the structure.