Good quality data is the most important part for a successful geophysical project. The processing and analysis of the data must be carefully executed to obtain acceptable results. Good quality data is the most important part for a successful geophysical project. The processing and analysis of the data must be carefully executed to obtain the best possible results . At Geophysics HM Ltd the processing and analysis methodology is given highest priority after field data collection.
We use inhouse developed and commercial available geophysical platforms and software such as Geosoft Oasis Montaj ™, RockWorks, ReflexW, Radan7 as our main processing platforms. With this we offer a wide range of tools and capabilities in database operations, mapping, grid and visualization, 3D modeling, geo-referencing and access to public data.
Our staff is proficient in a wide range of geophysical data processing techniques, including Ground Penetrating Radar, Induced Polarization, Ground Magnetics, Time Domain Electromagnetics, Frequency Domain Electromagnetics, Refraction Seismics and MASW. Typical data processing at Geophysics HM Ltd include Raw Data, Synthetic Modeling and Historic Datasets. At Geophysics HM Ltd the processing and analysis methodology is given highest priority after field data collection.
Geophysical data processing begins by importing the instrument collected data into our processing platforms. Geospatial information in local and real world coordinates is verified and raw data integrity is confirmed. Depending on the objective of the given survey, various filters and math expressions may be applied to remove irrelevant features in the data. When the data set is ready and the quality of the observations is acceptable, the gridding and model inversion is performed using either minimum curvature, bi-directional, or kriging methods.
Relevant information such as line locations, stations numbers, contours, and relevant topography are also added to highlight important features. Additional information may also be added including geology or geochemical information, regional data, or additional cultural features. Client data can be added to any map to help correlate different data types.
Our staff is proficient in a wide range of geophysical data processing techniques, including Ground Penetrating Radar, Induced Polarization, Ground Magnetics, Time Domain Electromagnetics, Frequency Domain Electromagnetics, Refraction Seismics and MASW. Accurate GPS data is critical for ensuring that all other data are referenced properly and that anomalies can be identified in their correct location. GPS data is acquired on every job and is used to create all other plan maps. Locations for local features such as points of interest, roads, power lines, or drillholes can also be captured and plotted on maps.
The processing of the Induced Polarization Time Series in the time or frequency domain is carried out to obtain the chargeability and resistivity parameters of the minerals and fluids hosted in the forming rocks and soils. In the majority of the cases it is necessary to reduce or eliminate the effect of the natural occurring, man-made and cultural noise in the acquired raw data. Examples of noise sources in the IP data are tellurics, spherics, power lines, transmitters, subsurface and buried cables and structures.
Several decay curves are extracted and stacked from the raw time series and fit to computerized Cole-Cole decay models. The calculated Cole-Cole parameters are directly related to the electrical properties of the subsurface rocks, fluids and minerals. The final processed data is presented in the form of Electric Resistivity and Chargeability Pseudo Sections .
MAG data is one of the most common types of geophysical data. Raw data can be geo-referenced and filtered to emphasize shallow or deep features. Additional filtering such as Reduction to the Pole, Upward Continuation, or first vertical derivatives can also be performed. Finally, data is gridded and presented as a plan map. Ground Magnetic data can also be integrated into other types of maps.
Anomaly Enhancement: Aeromagnetic maps generally comprise a set of superposed anomalies of many different spatial wavelengths. The amplitude of magnetic anomalies attenuates with increasing distance from the magnetic source and short-wavelength anomalies attenuate more severely with increasing distance relative to longer-wavelength anomalies. In general, the shortest-wavelength anomalies are caused by magnetic bodies at or close to the surface, whereas longer-wavelength anomalies typically reflect deeper magnetic source bodies.
Reduction to Pole: Magnetic anomalies produced by rocks containing magnetic minerals as a result of induction by the Earth’s main magnetic field are generally asymmetric, even when the bodies are symmetrical. The asymmetry is caused by the nonvertical main magnetic field and thus is a function of magnetic latitude. The magnetic anomalies over symmetrical, vertical tabular magnetic bodies display magnetic lows on their north sides with the deepest lows just north of the north edges of the bodies and magnetic highs on their south sides, with the strongest highs just north of the south edges of the bodies. A reduction to the pole (Baranov and Naudy, 1964) transforms observed anomalies into those that would have been measured at the magnetic pole where the main field is vertical.
Induction Decay Analysis: Typical Time Domain Electromagnetic data processing include multiple time gates analysis for target parameter characterization. Data from multiple time gates are plotted in composite profiles and contour grid maps to provide target selection, discrimination and description of the target decay responses. Earlier time gates analysis will be beneficial for shallow small target identification and mid-late range time gates analysis for large deep buried objects characterization. The target decay response over a buried metal object will have a well defined peak facilitating quick and accurate determination of location of the object. The detection depth is dependent on the surface area and orientation of the target
Quadrature & Phase Signal Components: Two components of the electromagnetic field (Quadrature and Inphase) are measured over the survey profiles. The measurement units of the system are “milli-Siemens per meter” (mS/m) for the Quadrature component and “parts per thousand” (ppt) for the In-Phase component of the measured electromagnetic field. Electromagnetics profile data are often combined onto maps to allow for an integrated interpretation. Profiles are plotted along line paths in order to identify quadrature and phase shifts derived from different materials quickly. Profiles corresponding to different frequencies can be plotted simultaneously to further interpretation.
GPR Radagrams: Compared to seismic data, relatively little processing is generally done to GPR data. A gain function is usually applied to the data to emphasize the weaker responses. There are a number of gain functions that can be applied depending of the data quality and the profile elements that you want to emphasize (e.g., automatic gain control (AGC), spherical and exponentially compensation (SEC) gain, user defined gain function). An example of the effects of different gain functions are displayed in Moorman & Michel (1997).
Filtering and Fourier Analysis: Temporal filtering involves filtering along the time axis of each trace. This can involve high-pass, low-pass filters or frequency filters such as Fourier analysis. These filters involve reduction or elimination of certain unwanted responses along each trace.
Spatial filtering is employed to remove unwanted spatial variations. One technique is to perform a running mean of data points at the same time across traces. This type of trace to trace running mean is used to emphasize horizontal reflections while de-emphasizing sloping returns.
Seismic Velocity Model Calculation: The processing of the seismic refraction data includes importing the raw seismic traces or time series onto the processing platforms (e.g. ReflexW, Sonde, SeisImager), picking the first breaks, assembling the hodographs and performing the model velocity inversions. Seismic signal data processing methodology uses various mathematical methods to eliminate natural and artificial noise, subsurface velocity models generation, bedrock topography profiling, stratigraphic interpretation and soil physical properties characterization.
Dispersion Model Estimation: MASW data processing is done for generating the subsurface soil and bedrock shear-wave velocity distribution. The mathematical models analyses the dispersion properties of the fundamental-mode Rayleigh waves that propagates along near surface from the energy source usually a strike on surface or traffic noise to the geophone receiver. The MASW inversion models are used for IBC Seismic Site Classification (Vs30), bedrock profiling, stiffness estimation, stratigraphic mapping and liquefaction potential analysis.