Low-frequency hydrocarbon microtremors: Case studies around the world Robert M. Habiger (Spectraseis AG, Zürich), Erik Saenger (Geologisches Institut, Switzerland), Stefan Schmalholz (Geologisches Institut, Switzerland)

Survey operations: on land Spectraseis is operating in diverse locations around the world Shown here: field operations on four continents Put list down side of all places we have acquired and/or processed data; or perhaps some statistics on how much data we have acquired or processed

Outline Project workflow Project examples Summary and Conclusions Acquisition Processing & Analysis Interpretation Project examples Objectives Enviornments and operatonal challenges Processing & Analysis issues Results Summary and Conclusions Acknowledgements ttktjkjt

Spectraseis surveys around the world ___ surveys have been acquired aournd the world in 7 countries I will be talking talking about operations and data from the 4 shown by the red dots

Outline Project workflow Project examples Summary and Conclusions Acquisition Processing & Analysis Interpretation Project examples Objectives Enviornments and operatonal challenges Processing & Analysis issues Results Summary and Conclusions Acknowledgements ttktjkjt

Acquisition: field operations (site preparation) Tripod N Sensors are buried to reduce environmental noise. An aluminum tripod system allows for quick orientation & leveling. Leveling

Acquisition: field operations (equipment) Broadband seismometers are used for sensitivity, noise floor, and bandwidth Sensor Handheld control Batteries Güralp Seismometer Freq. Range: 0.03 – 50 Hz Sampling rate: 100Hz Sensitivity: 1500 V/m/s Weight: 15 kg

Acquisition: field operations (installed station) GPS antenna Position Marker Completed field setup at measurement point (station). All equipment is buried for nominally 24hrs - except GPS antenna.

Acquisition: survey design Possible survey designs include: 3D grids dense lines staggered synchronized swaths combinations reference stations

Processing & Analysis Workflow Raw Data Characterization & QC Reference Stations Spectral Analysis Noise Amplitude vs. Time Synchrogram Earthquakes Time Stability Spectrogram Weather Prepare clean, comparable data Data Conditioning and Processing The workflow supports a systematic analysis. It has taken us several years to develop this workflow and the tools needed to carry it out. It remains active research and development. Range Setting Parameter setting Spectra/Attributes Reservoir Localization PSD-IZ V/H Time Reverse Modeling PSD-IN Soil Effects PSD-IE Polarization Analysis & Interpretation

Data from northern Africa Different colors are data acquired on different days. This is daytime data. The main observations: The data is complex The data is variable Calculated PSD for synchronized lines 4, 5 and 6 taken in Block 186 using “day” data range. There has been no range setting. Each color represents a different line, acquired on a different day. The multiple lines for a given color represent different time intervals.

Data from northern Africa Night data 1st minimum shifts anthropogenic noise is less anomaly band is better defined Calculated PSD for synchronized lines 4, 5 and 6 taken in Block 186 using “night” data range. There has been no range setting. Each color represents a different line, acquired on a different day. The multiple lines for a given color represent different time intervals.

Processing & Analysis (statistical spectral analysis) Deep gas example of weak anomaly

Processing & Analysis (synchrograms) 26.06.2007 27.06.2007 Observations regional events local events night/day variation Synchrogram for all points on the line A and PS-01, recording period on 26-27th June with a common local time axis. Day/night signal variations are clearly visible. Note strong perturbing broadband noises (first at 0.20AM and event at 3.10AM). LF anomaly at around 3Hz is visible. PS-01 (at the bottom of the picture) recorded a lot of noise, which differs in character from the rest of the data.

Data cleaning and signal conditioning The top row of composite spectra are raw data The bottom row is “range set” data : SDA plots for each point on Line B (Z component on full raw dataset, 24 hours, no ranges applied). Note the strong bimodal signal distribution due to day/night variation SDA plots for all points on Line B (Z component on night data: 07.00PM-04.00AM local time subset, ranges applied). Note that spectra for all points are quieter and better defined at night time compare to day time.

Outline Project workflow Project examples Summary and Conclusions Acquisition Processing & Analysis Interpretation Project examples Objectives Enviornments and operatonal challenges Processing & Analysis issues Results Summary and Conclusions Acknowledgements ttktjkjt

North American case study The technology was confirmed over an existing field and then extended into an exploration area

North America case study A very good correlation over a known reservoir and hydrocarbon potential map

South American case study A limited test for the first application to heavy oil Mapa de Tierras – Cinturón de crudo pesado – Campo Rubiales

South American case study Two major attributes provided a consistent relationship with the expected reservoir for this limited study

Outline Project workflow Project examples Summary and Conclusions Acquisition Processing & Analysis Interpretation Project examples Objectives Enviornments and operatonal challenges Processing & Analysis issues Results Summary and Conclusions Acknowledgements ttktjkjt

Conclusion Off the shelf sensors provide good qualitydata A rich set of workflow processing & anlaysis tools are needed for data conditioning and attribute calculation LF passive seismic technology has been applied to ___ survey in ___ different locations Remaining challenges Theory relating to the mechanisms causing the LF micro tremors Noise analysis and mitigation

Acknowledgements Permission to show data StatoilHydro EniRepSa Pemex Ecopetrol Spectraseis staff in acquisition, processing and analysis

Instruments used during the survey First raw data QC in FO Block 186 Preliminary QC of raw data in Field Office