Analyzing passive seismic attributes: A statistical strategy

Riahi, Nima; Birkelo, Brad; Saenger, Erik H.

doi:10.1190/1.3627528

Cited by 2 publications

(3 citation statements)

References 13 publications

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“…Therefore, it could not be directly inferred from passive seismic data [1,29]. The literature study signifies that the 20 observed tremor signals have been correlated with hydrocarbon reservoir for the supplying seismic-acoustic energy for filtering/mixing hydrocarbon impacts on reservoir subsurface [2,5,6,8,21,22,44,127]. However, others have expressed some doubts on underlying theory of the technique and its applicability to different geologies and its repeatability [24,29,41].…”

Section: Seismic Attributes Predicted Hydrocarbon Versus Drilledmentioning

confidence: 99%

“…The measurement of the tremor signals is demanding high resolution which is inversely affected by device noise. This can be explained by recalling the 24-bit modern standard digital output of seismic sensors [8]. Considering full scale of 80 mg, the minimum detectable acceleration would be 4.7 ng.…”

Section: Technology Gap Of Sensorsmentioning

confidence: 99%

“…Furthermore, the research study of seismic energy at subsurface identifies some independent spectral attributes [8]. These attributes help in computing the spectral ratio between horizontal and vertical components of formation.…”

Section: Introductionmentioning

confidence: 99%

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Accelerometer Sensor Specifications to Predict Hydrocarbon Using Passive Seismic Technique

2016

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The ambient seismic ground noise has been investigated in several surveys worldwide in the last 10 years to verify the correlation between observed seismic energy anomalies at the surface and the presence of hydrocarbon reserves beneath. This is due to the premise that anomalies provide information about the geology and potential presence of hydrocarbon. However a technology gap manifested in nonoptimal detection of seismic signals of interest is observed. This is due to the fact that available sensors are not designed on the basis of passive seismic signal attributes and mainly in terms of amplitude and bandwidth. This is because of that fact that passive seismic acquisition requires greater instrumentation sensitivity, noise immunity, and bandwidth, with active seismic acquisition, where vibratory or impulsive sources were utilized to receive reflections through geophones. Therefore, in the case of passive seismic acquisition, it is necessary to select the best monitoring equipment for its success or failure. Hence, concerning sensors performance, this paper highlights the technological gap and motivates developing dedicated sensors for optimal solution at lower frequencies. Thus, the improved passive seismic recording helps in oil and gas industry to perform better fracture mapping and identify more appropriate stratigraphy at low frequencies.

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