H. Sadi Kuleli

Passive seismic tomography using induced seismicity at a petroleum field in Oman

A borehole network consisting of five monitoring wells monitored the induced seismicity at a producing petroleum field for about 11 months . Nearly 5400 microseismic events were analyzed and used to image the reservoir based on a new double-difference (DD) seismic tomography. The DD tomography method simultaneously solved for event locations and VP , VS , and VP ∕ VS models using absolute and differential P, S, and S-P arrival times. Microseismicity in the field was caused primarily by compaction of the reservoir in and above the gas-bearing formation and was distributed along the two major northeast-southwest faults in the field. The model resolution analysis based on the checkerboard test and the resolution matrix showed that the central part of the model was resolved relatively well for the depth range of 0.7 to 1.1 km . Clear velocity contrasts were imaged across most parts of the two northeast-southwest faults. The VP ∕ VS ratio estimates from the tomographic inversion were low (<1.75) in the shallow...

Full‐waveform based microseismic event detection and signal enhancement: An application of the subspace approach

Microseismic monitoring has proven invaluable for optimizing hydraulic fracturing stimulations and monitoring reservoir changes. The signal to noise ratio of the recorded microseismic data varies enormously from one dataset to another, and it can often be very low, especially for surface monitoring scenarios. Moreover, the data are often contaminated by correlated noises such as borehole waves in the downhole monitoring case. These issues pose a significant challenge for microseismic event detection. In addition, for downhole monitoring, the location of microseismic events relies on the accurate polarization analysis of the often weak P-wave to determine the event azimuth. Therefore, enhancing the microseismic signal, especially the low signal to noise ratio P-wave data, has become an important task. In this study, a statistical approach based on the binary hypothesis test is developed to detect the weak events embedded in high noise. The method constructs a vector space, known as the signal subspace, from previously detected events to represent similar, yet significantly variable microseismic signals from specific source regions. Empirical procedures are presented for building the signal subspace from clusters of events. The distribution of the detection statistics is analysed to determine the parameters of the subspace detector including the signal subspace dimension and detection threshold. The effect of correlated noise is corrected in the statistical analysis. The subspace design and detection approach is illustrated on a dual-array hydrofracture monitoring dataset. The comparison between the subspace approach, array correlation method, and array short-time average/long-time average detector is performed on the data from the far monitoring well. It is shown that, at the same expected false alarm rate, the subspace detector gives fewer false alarms than the array short-time average/long-time average detector and more event detections than the array correlation detector. The additionally detected events from the subspace detector are further validated using the data from the nearby monitoring well. The comparison demonstrates the potential benefit of using the subspace approach to improve the microseismic viewing distance. Following event detection, a novel method based on subspace projection is proposed to enhance weak microseismic signals. Examples on field data are presented, indicating the effectiveness of this subspace-projection-based signal enhancement procedure.

Eight Years of Passive Seismic Monitoring At a Petroleum Field In Oman: A Case Study

We present a case history of passive seismic monitoring with location and characterization of earthquakes induced by oil and gas production and water injection at a petroleum field in Oman. Locating induced seismic events with reasonable accuracy is key to the success of reservoir monitoring using this technology. To this end we present methods suitable for oil/gas field conditions and test and compare these with conventional methods using both synthetic and actual field data. We applied our methods to analyze and locate about 1500 seismic events, recorded by a near-surface seismic network in the field over the past 8 years. We used a detailed velocity model of the reservoir derived from well-logs, in conjunction with a location method developed in-house to locate these events. Location of these events suggests a strong correlation of induced seismicity with compaction of reservoir due to gas production, and reactivation of preexisting faults in the field.

Detection and Enhancement of Microseismic Signals with Correlation Operators: "Cross Product and Master Event" Methods

A class of more general polarization filters, referred to as rectilinear motion detectors (REMODE), is being developed in which the filter functions are based on the correlation functions for two components. Sometimes the correlation function is used between a selected signal describing a target seismic event and seismic data (Gibson and Ringdal 2006). In this study, two ―linear motion detector‖ type operators were applied to enhance the signal/noise ratio of the microseismic signal.

Microseimic Monitoring of the Yibal Oil Field

Yibal Oil and Gas field has a great deal of induced microseismic activity, which has been monitored extensively for more than 9 years through cooperation between the Petroleum Development of Oman (PDO), Massachusetts Institute of Technology (MIT) and Sultan Qaboos University (SQU). In this study, we investigate the location of the microseimic events using three earthquake location methods: (1) classical linearized hypocenter method (hypoinverse), (2) probabilistic earthquake location (NonLinLoc) and (3) full waveform inversion method. The data set consists of approximately 1500 selected good quality seismic events recorded by a near-surface seismic network over a 9-year period.