HYdrocarbon Passive Infrasonic Seismic (HYPIS)®

(Low Frequency Seismic Direct Indication of Hydrocarbon Proposal in Gujrat area for ONGC India)


This technique was originally developed in the 80’s by scientists of the Russian Academy of Sciences. It was discovered that:   on top of an oil reservoir, the natural earth noise spectra show an increase of magnitude in the frequency range between 0 and 6 Hz. This increase is accompanied with the appearance of several spectral lines.

The origin of these low frequency signals (0.1-6Hz) can be attributed to the following 2 reasons:

1] The alteration of the existing natural macroseismic energy by the reservoir itself which acts as a scatter

2] Emitted by the reservoir

In the 1st case the reservoir, being a geological heterogeneity, alters (scatters or absorbs some high frequencies) the existing natural seismic wave field, and exhibits it as low-frequency seismic signals on the surface the spectra of which shows some characteristic resonant frequencies (Fig.1).

Fig.1 The recorded above a hydrocarbon reservoir microseismic field in many cases shows some characteristic spectral picks.

We can also consider that the reservoir distort the random microtremor low frequency wave field and some differences can be observed in relation with nearby non productive areas . Wave on the water surface could be considered as analog for surface low frequency seismic waves.

Fig.2. stones do not come out above the surface, but they distort the random wave field and we can conclude of their presence by these distortions.

Recent investigations show that the induced natural seismic wave field on the reservoir is altered by poroelastic effects and oscillations of various fluid phases which “absorb” higher frequencies An oil reservoir can be represented as a nonlinear system with low pass characteristics The basic assumption is that the reservoirs are partially saturated while the surrounding rocks are fully saturated.

In the 2nd case certain frequencies of natural seismic energy spectrum are trapped in the multiphase system of the reservoir which is in a metastable condition and generates (radiates) a deterministic microseismic noise (signal) of the deposit, which then is registered on the Earth surface.

Fig.3. The natural microseismic field excites the reservoir which emits the recorded low frequency signals.

According to results of numerical simulation, physical model test and petrological analysis, it was found that oil and gas reservoir (double phase medium) shows the characteristics of :

Low Frequency Resonating (LFR) and

High Frequency Attenuation (HFA)

The reason is the displacement between fluid and solid resulting in the redistribution of seismic wave energy

These slow waves have resonant frequencies ωf given by:

where  V, ρwave velocity and formation density in the reservoir

Vf , ρfwave velocity and density in the fluid

φ     – porosity of the reservoir

Ocean waves is the main source of microseisms with periods 1-5 sec (0.2-1Hz) The sources of microseisms with periods 3-20 sec (0.05-0.3Hz) are large atmospheric vortex formations passing over oceanic water areas. Number of researchers found that transmission of pressure variations occur via water mass to the ocean bottom. In order to register accurately these very low frequency signals we need special designed sensors and recording devices.


LandTech uses the broad band SM3 seismometer (Fig.4), designed by Prof. Basilov of the Russian Academy of Sciences particularly for reservoir related low frequency seismic signals and not off the self existing seismographs mainly used by seismological institutes to record earthquakes…. This unit has high sensitivity and extremely low level of ‘self’ noise.

Fig.4. (a) Internal and (b) view of the SM3 seismometer particularly designed for low frequency investigations.

LandTech has also designed and constructed a special 24-bit recording unit (LTSR-24) to register the low frequency signals in connection with the SM3 seismometer. This

  • Writes directly from the A/D converter to a Flash Card
  • True 24bit
  • No internal microprocessor PC, based on DSP
  • The lowest power consumption of all in the market
  • No hard disk, can stand down to -40 oC up to 60 oC

Since LandTech manufactures its own equipment can solve technical problems due to possible equipment malfunction on the spot by replacing electronic cards or the whole instrument from the vast amount of spares which keeps in the field.

Low frequency data acquisition – LandTech’s methodology

LandTech’s Low Frequency Seismic Technology uses a multisensor measuring array consisting of 4 SM3 seismometers at the corners of a square AND a 3-component Trillium sensor by Nanometrics at the centre of the square array if cultural nois is high (Fig.5).

The low frequency microtremor signals which will be detected is a composition of :

  • Natural earth noise (which is unstable for short periods)
  • Man made noise and
  • A non periodic response of the reservoir

For this reason to achieve a statistically reliable result the recording time has to be “as long as possible”, the required recording time at each station will be decided after analysing the characteristics of the microtremor wave field in the project location.

In order to correct for artificial variations or global changes of the microtremor field and select stable parts of the recorded signals we will install the required number of base (refernce) stations which will consist of SM3 seismometers.

Data processing methodology followed by LandTech

LandTech has developed an integrated data processing scheme in order to derive many parameters related with the presence of a hydrocarbon reservoirsuch as

  • Power spectrum density distribution
  • Microseismic power flow rate versus depth at each measuring point
  • Amplitude spectrum distribution
  • Moise distribution
  • Gross/net pay zone thickness

A description of the data processing flow which will be used is presented in the attached flow chart .

Data Processing Flow Chart used in HYPIS Methodology ®

LandTech’s methodology does not only give areal distribution of spectral amplitude factors (as other companies do) but also Microseismic power flow rate versus depth at each measuring point.

In the case that in the region there are productive and dry wells we “calibrate” our measurements by estimating the corresponding microseismic power rate per unit area at dry and productive wells and we choose the corresponding “threshold level” accordingly.

We calculate the total density of microseism flow power rate according to the formula:

                        P = ρ*c*v2 /2  

where ρ – density of the soil, с – velocity of wave front, v – velocity measured by the sensor.

We use all 5 recordings at each measuring site and we put certain constraints in order to remove artifacts and isolate signals related to the reservoir. A brief description of this methodology is given below

Raw data usually include strong perturbations (noise, artifacts) and discontinuities (data gaps). By examining the raw data in relation with the base station recordings, we “cut out” all intervals with strong interferences (Fig.6)

Fig,6. Selection of stable parts of the signal.

Surface noises produce double effect on result of measurements.

On one hand, they are capable to increase amplitudes of resonance phenomena that facilitates their registration

On the other hand, they increase “spurious resonances” and decrease reproducibility of results owing to their random nature.

The measurements in conditions of minimum surface noises (at night, in remote regions) increase reproducibility of measurement results, but frequently require increasing sensitivity of receiving equipment and increasing duration of measuring to extract weak resonance phenomena caused by low activity of the Earth’s crust.

Consequently, to optimize field works there is some optimal level of surface noise which ensures acceptable speed and quality of works.

Fig.7. Correction – levelling in relation to the base station recordings.

The plot of noise level at the recoding moment at all the points is given in the form of a noise map.

With this map it is possible to estimate the quality of the measurements all over the area.

Let us now consider that the exploration depth is H and that the sensor interval is D (Fig.8)

Fig.8 Measuring cone for power flow density rate calculation

For every point inside Δφ, ΔL=L2-L1 is given by:

Where Tharmonic=1/fharmonic ; Δφ>1o due to equipment response characteristics (7o)

To receive signals inside Δφ we chose all harmonics from the FFT spectra of S1,S2 recordings starting

simultaneously with almost equal amplitudes A1~A2 .

Phase difference between every pair of harmonics must be less than


LandTech has developed a special software (IGLASEIS®) based on the solution of diffusive-viscous wave equation with a model containing dry and saturated porous zones and calculates the microseismic flow power rate per depth

Benefits of HYPIS LandTech’s low frequency methodology

(Comparing HYPIS with other similar methodologies)

  • We use 4 – 5 seismometers per site instead of one
  • We design & construct our instruments fine-tuned for Low frequency surveys
  • We incorporate into our analysis and the Rayleigh wave components of the surface natural wave field for velocity assessment
  • We assign each spectra harmonic to the corresponding depth looking downwards
  • We assign spectral amplitude anomalies at various depths
  • We estimate seismic power flow rates at various depths
  • If the client wants we can combine passive low frequency and seismic tomography for superior results

Recent scientific investigations contacted by universities and oil industry R&D personnel have questioned the reliability of single sensor measurements (e.g. Broadhead 2010; Ali et al., 2010). This is the reason why LandTech uses 5 sensors at each measuring point.


Ref 1.. Michael K. Broadhead 2010: Oscillating oil drops, resonant frequencies, and low-frequency passive seismology.  . GEOPHYSICS,VOL. 75, NO. 1 _JANUARY-FEBRUARY2010_; P.O1–O8, 11 FIGS., 4TABLES.


Ref 2…. Mohammed Y. Ali, Karl A. Berteussen, James Small,* and Braham Barkat 2010: A Study of Ambient Noise over an Onshore Oil Field in Abu Dhabi, United Arab Emirates. Bulletin of the Seismological Society of America, Vol. 100, No. 1, pp. 392–401, February 2010