Pre-drill Reservoir Evaluation Using Passive Seismic Imaging

Sicking, Charles; Vermilye, Jan; Yaner, Ashley

doi:10.15530/urtec-2016-2460524

Cited by 5 publications

(9 citation statements)

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“…The filtering and depth migration methods used for fracture seismic are based on typical reflection seismic signal processing algorithms, but are modified to deal with one-way travel times from the fracture seismic sources to the receivers. Success in using fracture seismic recordings for mapping fractures requires having high-quality non-resonant signal analysis and suppression (Sicking et al, 2016(Sicking et al, , 2017 [21,25].…”

Section: Fracture Seismic: Signal Processingmentioning

confidence: 99%

“…This type of noise is common in industrial areas and transportation corridors and appears as noise background added to the consistent, slowly changing, harmonic character of fracture seismic signals. This long duration of noise can overwhelm fracture seismic signals, but the noise can be separated from the fracture seismic signals with cepstral filtering (Sicking, 2016) [21]. The cepstral filtering processes each fracture seismic trace independently by transforming the trace into the Cepstral domain, applying a bandpass in that domain, and inverse transforming back to time.…”

Section: Fracture Seismic: Signal Processingmentioning

confidence: 99%

“…Spectrogram analysis facilitates the efficient identification of time windows for use in computation of fracture seismic intensity volumes. Time periods with the strongest resonances are selected from the spectrograms and used in the depth migration method to map their spatial locations (Sicking et al, 2016(Sicking et al, , 2017 [21,25].…”

Section: Identification Of Resonance and Turbulent Flow In Fracture Smentioning

confidence: 99%

“…The end-to-end system for applying the fracture seismic method has been in practice since 2010 (Sicking et al, 2012) [20]. The main mapping step is a time-progressing depth migration of the fracture seismic resonance episodes, a process that we call streaming depth imaging (SDI; Sicking et al, 2016) [21]. Two examples of fracture information that can be computed using SDI are shown in Figure 2.…”

Section: Introductionmentioning

confidence: 99%

“…Recent research on the source of fracture seismic signals has put the fracture seismic method on a solid theoretical and practical base (e.g., Tary et al, 2014 [3]; Liang et al, 2017) [22]. It has now been applied to dozens of field projects and the examples presented here come from those projects (e.g., Sicking et al, 2014;2016; [21,[23][24][25], Geiser et al, 2012 [26], Lacazette et al, 2013 [27]).…”

Section: Introductionmentioning

confidence: 99%

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Fracture Seismic: Mapping Subsurface Connectivity

Sicking

Malin²

2019

Geosciences

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Fracture seismic is the method for recording and analyzing passive seismic data for mapping the fractures in the subsurface. Fracture seismic is able to map the fractures because of two types of mechanical actions in the fractures. First, in cohesive rock, fractures can emit short duration energy pulses when growing at their tips through opening and shearing. The industrial practice of recording and analyzing these short duration events is commonly called micro-seismic. Second, coupled rock–fracture–fluid interactions take place during earth deformations and this generates signals unique to the fracture’s physical characteristics. This signal appears as harmonic resonance of the entire, fluid-filled fracture. These signals can be initiated by both external and internal changes in local pressure, e.g., a passing seismic wave, tectonic deformations, and injection during a hydraulic well treatment. Fracture seismic is used to map the location, spatial extent, and physical characteristics of fractures. The strongest fracture seismic signals come from connected fluid-pathways. Fracture seismic observations recorded before, during, and after hydraulic stimulations show that such treatments primarily open pre-existing fractures and weak zones in the rocks. Time-lapse fracture seismic methods map the flow of fluids in the rocks and reveal how the reservoir connectivity changes over time. We present examples that support these findings and suggest that the fracture seismic method should become an important exploration, reservoir management, production, and civil safety tool for the subsurface energy industry.

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Section: Fracture Seismic: Signal Processingmentioning

confidence: 99%

Section: Fracture Seismic: Signal Processingmentioning

confidence: 99%

Section: Identification Of Resonance and Turbulent Flow In Fracture Smentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fracture Seismic: Mapping Subsurface Connectivity

Sicking

Malin²

2019

Geosciences

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Forecasting reservoir performance by mapping seismic emissions

Sicking¹,

Vermilye²,

Yaner³

2017

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Streaming depth imaging (SDI) is a modified version of Kirchhoff migration that images the intensity and distribution of weak seismic waves emitted from rocks at depth. These images reveal the locations of the fractures and fracture networks in the reservoir. SDI allows for more informed forecasts for drilling, hydraulic fracturing, and reservoir management than is provided by traditional microearthquake mapping methods. Using passive data from surface and near-surface geophone grids, SDI integrates the seismic emissions over time to form the fracture activity volume. The fracture systems and the active production volume (APV) of the reservoir are calculated from this activity volume. In situ wellbore measurements indicate that the preexisting fracture systems in the reservoir rocks have substantial impact on the placement of the fluids during the hydraulic fracture treatment. They also strongly influence the locations of maximum oil and gas production and the decline rates of resource production. Mapping the fracture systems in the reservoir before drilling provides a strong forecasting value for optimal production sites for well placement. SDI can forecast hydraulic fracturing performance and improve the estimates of resource production volumes. Mapping the activity volumes during hydraulic fracturing shows the placement of the fluids during the treatment. SDI helps forecast the locations along the well that will have the best production. Time lapse mapping of the APV periodically during production shows the zones that are producing fluids and how they change over time. Our case histories indicate that this new seismic method has great promise for improved management of unconventional resources.

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