Time-lapse Seismic Processing Research Articles

Detection of Dynamic Phenomena Associated with Underground Nuclear Explosion Using Multiple Seismic Surveys and Machine Learning

The application of an active seismic method for detecting the source location of an underground nuclear explosion (UNE) is an ongoing field of research. The objective of active seismic in On-Site Inspection (OSI) is to detect the static signatures such as the cavity created by the UNE. Along with characteristic static signatures, UNEs produce dynamic phenomena such as groundwater mounding, which gradually revert to pre-test conditions. These dynamic phenomena are observable for an extended period, even up to several decades. The magnitude of these phenomena is prominent near the source origin and results from the redistribution of residual energy, such as pressure, temperature, and saturation. These dynamic changes in sub-surface rock and fluid properties will affect the seismic property of the rock, resulting in changes of P-wave velocity. These changes can be detected by using an active seismic survey. This study highlights the potential of using time-lapse seismic to identify ground zero by monitoring post-explosion variation in the seismic signature. Time-lapse seismic, also known as 4D seismic, is a well-known technology, used in the oil and gas industry for several decades for petroleum production monitoring and management. It involves taking more than one 2D/3D survey at different calendar times over the same reservoir and studying the difference in seismic attributes. This study investigates the characteristic dynamic phenomena associated with the UNE and their impact on the emplacement rock’s seismic property. Groundwater mounding (GWM) is one of the phenomena with a high gradient of dissipation during the initial days immediately after the explosion. We look at the impact of GWM variation on seismic P-wave velocity and discuss the potential of using time-lapse seismic for its detection. The challenges of implementing time-lapse seismic, such as non-repeatability, seasonal variations and time constraints, are discussed. A frequent seismic monitoring survey method (time-lapse seismic) is proposed to monitor rock and fluid properties changes due to the post-UNE dynamic phenomena. Due to the time constraint for the OSI activity, conventional time-lapse seismic processing would not be suitable. Therefore, a machine learning-based 4D detection workflow is presented. The near-real-time 4D detection workflow using machine learning can be implemented during the OSI to identify the source location or ground zero.

Processing and Interpretation of Time-Lapse Seismic Data at Gao 89 CO2-EOR Area

CO2-EOR greatly recovered oil production in Gao 89-1 block in Sinopec Shengli Oil Company. However, CO2-EOR efficiency was high in some wells but some production wells had little effect. In order to study CO2 sweep efficiency and CO2 distribution, 3D seismic monitoring acquisition was conducted in December, 2010. It is the unique time-lapse 3D seismic datasets to monitor CO2 distribution in China. But the geometry of baseline and monitor is different. Moreover, the depth of reservoir is about 3200 m and effective thickness of reservoir is only 10 m. In addition, the injection volume of CO2 was small and around 50,000 t. If time-lapse 3D seismic technique could discriminate CO2 distribution has been a controversial question. In this paper, we studied the problems during CO2 flooding and estimated the net CO2 storage volume. Then we proposed a time-lapse seismic processing method that improved the conventional geometry degradation and made a better seismic image from vantages of seismic monitoring. In order to calibrate monitoring seismic datasets by using the well log data measured before CO2 injection, P- and S- wave velocity logs versus pressure change method is proposed and verified by making synthetic seismograms. Our study proved that the time-lapse seismic difference mainly caused by the change of pore pressure during CO2 injection in this area. Finally, time-lapse seismic difference calibration method is proposed that assuming the caprock seismic attributes were consistent before and after CO2 injection. The time-lapse difference matched the oil production and CO2 injection well.

Time-lapse surface seismic processing for Stage 2C of CO2CRC Otway Project

Stage 2C of the Otway project aims to detect a small injection of CO2-rich mixture into a saline aquifer, verify stabilisation of the injection and evaluate the detectability threshold of CO2 achievable by surface seismic. Over the past three years, we have produced five vintages of high-quality 4D seismic data showing the evolution of the 15,000 tonnes of injected scCO2/CH4 gas mixture into the saline aquifer at 1500 m depth. The time-lapse seismic processing workflow was built based on the findings from a synthetic feasibility study and processing of the baseline dataset. Through this workflow we processed the time-lapse data which allowed monitoring of small incremental injections (about 5 000 tonnes each). Here we elaborate on effect of various processing routines on the quality of 4D image, namely, amplitude restoration, prestack cross-equalization and imaging. We aim at preservation and restoration of time-lapse signal and suppression of time-lapse noise. We evaluate the results of the processing efforts in post-stack domain through estimates of 4D signal-to-noise ratio in vicinity of the injection interval. The usefulness of individual processing routines for improvement of time-lapse signal cannot be established independently from other routines in the same workflow. Surprisingly, images with pre-stack AGC applied have consistently higher time-lapse signal-to-noise ratio compared to images produced without it. Improvement of the resolution and appearance of 3D images does not guarantee increase of time-lapse signal-to-noise ratio.

Time-lapse inverse theory with applications

Compaction in the reservoir overburden can impact production facilities and lead to a significant risk of well-bore failures. Prevalent practices of time-lapse seismic processing of 4D data above compacting reservoirs rely on picking time displacements and converting them into estimated velocity changes and subsurface deformation. This approach relies on prior data equalization and requires a significant amount of manual interpretation and quality control. We have developed methods for automatic detection of production-induced subsurface velocity changes from seismic data. We have evaluated a time-lapse inversion technique based on a simultaneous regularized full-waveform inversion (FWI) of multiple surveys. In our approach, baseline and monitor surveys are inverted simultaneously with a model-difference regularization penalizing nonphysical differences in the inverted models that are due to survey or computational repeatability issues. The primary focus of our work was the inversion of long-wavelength “blocky” changes in the subsurface model, and this was achieved using a phase-only FWI with a total-variation model-difference regularization. However, we have developed a multiscale extension of our method for recovering long- and short-wavelength production effects. We have developed a theoretical foundation of our method and analyzed its sensitivity to a realistic 1%–2% velocity deformation. The method was applied in a study of overburden dilation above the Gulf of Mexico Genesis field and recovered blocky negative-velocity anomalies above compacting reservoirs.

The time-lapse AVO difference inversion for changes in reservoir parameters

The result of conventional time-lapse seismic processing is the difference between the amplitude and the post-stack seismic data. Although stack processing can improve the signal-to-noise ratio (SNR) of seismic data, it also causes a considerable loss of important information about the amplitude changes and only gives the qualitative interpretation. To predict the changes in reservoir fluid more precisely and accurately, we also need the quantitative information of the reservoir. To achieve this aim, we develop the method of time-lapse AVO (amplitude versus offset) difference inversion. For the inversion of reservoir changes in elastic parameters, we apply the Gardner equation as the constraint and convert the three-parameter inversion of elastic parameter changes into a two-parameter inversion to make the inversion more stable. For the inversion of variations in the reservoir parameters, we infer the relation between the difference of the reflection coefficient and variations in the reservoir parameters, and then invert reservoir parameter changes directly. The results of the theoretical modeling computation and practical application show that our method can estimate the relative variations in reservoir density, P-wave and S-wave velocity, calculate reservoir changes in water saturation and effective pressure accurately, and then provide reference for the rational exploitation of the reservoir.

Value creation by a long-term time-lapse seismic processing approach on the Heidrun field

Value creation by a long-term time-lapse seismic processing approach on the Heidrun field

Purposeless repeated acquisition time-lapse seismic data processing

In China, most oil fields are continental sedimentation with strong heterogeneity, which on one side makes the reservoir prospecting and development more difficult, but on the other side provides more space for searching residual oil in matured fields. Time-lapse seismic reservoir monitoring technique is one of most important techniques to define residual oil distribution. According to the demand for and development of time-lapse seismic reservoir monitoring in China, purposeless repeated acquisition time-lapse seismic data processing was studied. The four key steps in purposeless repeated acquisition time-lapse seismic data processing, including amplitude-preserved processing with relative consistency, rebinning, match filtering and difference calculation, were analyzed by combining theory and real seismic data processing. Meanwhile, quality control during real time-lapse seismic processing was emphasized.