In 2002 Input/Output commercialized its full-wave digital sensor system known as VectorSeis™. Since the initiation of field testing in 1999 more than 65 surveys have been acquired worldwide with these MEMS (micro electro-mechanical systems) based sensors. Of these, 38 have been commercial seismic surveys in Western Canada. Observations by interpretation staff indicate that the majority of these surveys have exhibited improved P-wave data. This article will postulate that this improvement in the P-wave is due at least in part to the vector fidelity improvements inherent in the VectorSeis design.

Full-wave recording entails using a multicomponent sensor to accurately represent the three dimensional particle motion of the seismic signal. Recent advances in sensor technology means this can now be achieved in a direct digital manner thereby minimizing any possibility of signal corruption. Classical P-wave recording preserves only one axis, the vertical component of the wavefield. Having discarded the others, it is often difficult to solve simple problems later. Other aspects of the wavefield (i.e. shear waves) will have tremendous value as tools continue to develop.

Fig. 01
Figure 1. Vector Fidelity — cause and effect. Output vector is misplaced due to sensitivity and orthogonality errors in the sensing system.

During the design of the VectorSeis sensor system the requirements for good vector fidelity were studied closely. With time it became clear that there are four key design elements required to achieve a high degree of vector fidelity:

1. Sensitivity:

  1. Tested by exciting a sensor in its working axis and monitoring the output.
  2. Axis to axis differences in sensor sensitivity must be minimal, -45dB or better.
  3. Errors will preferentially distort vector magnitude and direction (Fig 1).

2. Cross axis rejection:

  1. Tested by exciting individual sensors and systems both in the working axis and orthogonal to that axis and measuring the output.
  2. The ratio must be very low, -60 to -80dB for individual sensor elements, -45dB or better for system of 3 sensors.
  3. Poor cross-axis response in a sensor will create output where none should exist.

3. Orthogonality:

  1. Axes must be highly orthogonal to one another.
  2. Errors in orthogonality will distort vector direction and magnitude (Fig 1).

4. Tilt at Deployment

  1. If a conventional sensor is deployed with an unknown tilt, it is difficult to determine the vertical component with any certainty. Hence the need to level them during deployment (a labour intensive task).
  2. By employing a MEMS sensor which is referenced to gravity all tilt ambiguity is removed and field deployment is dramatically simplified.
  3. Such a system only works effectively if the sensor is force balanced against gravity (Fig 2).

These parameters combine to ensure that when the vertical data are extracted from the wavefield recorded by a digital full-wave sensor, it is done with a minimum of distortion (Fig. 3).

Fig. 02
Figure 2. Dynamic Range vs Tilt Angle. Sensor A (VectorSeis) displays constant output regardless of sensor orientation. Sensor B (10Hz geophone) output falls off moderately with increasing tilt angle. Sensor C is a MEMS based system with no gravity compensation.

Historically full-wave sensor systems either lacked any high degree of vector fidelity or were operationally inefficient to deploy. Recent advances in MEMS based sensor technology have achieved full-wave sensor systems with excellent vector fidelity in a package that simplifies deployment. Because of these advances we are recording P-wave data of unprecedented quality. This is achieved by acquiring the full wave signal with the sensor in any arbitrary orientation, the sensor automatically reports its inclination relative to the earth’s gravitational field. Data are projected into a conventional Cartesian system during in-field pre-processing, using gravity as the reference. The extracted vertical component is a far more precise measure than conventional techniques (Fig. 3).

Fig. 03
Figure 3. Full-Wave data before and after referencing to gravity. Data on left are in field orientation, Data on right are after rotation to vertical. Note the improvement as shear energy is moved off the vertical axis.

It is worthwhile taking the time to question the assumption most geophysicists make whenever they use data recorded using classical techniques — that their P-waves are propagating vertically. This is probably a reasonable assumption at near zero offsets. As offsets become larger emergent angles begin to grow. Thanks to the velocity contrast in the overburden and Snell’s law it may still be a valid assumption. At far offsets it is possible but it is by no means a requirement. If the wavefield is emerging in a non vertical manner then the classical P-wave sensor system will, by definition, only record the cosine of the energy. In addition, other source related wave types can have significant expression in the vertical domain. These would include phenomena such as:

  • Ground roll
  • Air blast
  • Shear waves
  • Back scattered energy

Because the full particle motion has been ignored during classical P-wave recording, geophysicists often resort to elaborate signal processing techniques in an attempt to improve the S/N ratio of their data. These techniques are often less than satisfactory because too much information has been lost in the conversion from full-wave to P-wave only.

Full-wave recording offers new possibilities for suppressing these less desirable wave forms. Using advanced techniques based on characterizing signal and noise in multiple planes, algorithms such as adaptive vector filtering are demonstrating impressive results (Fig. 4). They are currently being used to suppress ground roll on P-P and P-S data, and also have application in suppressing undesirable body waves (i.e. non vertical P-P and P-S waves which leak into the orthogonal projection thereby lowering the S/N). Future algorithms will explore the potential of more sophisticated techniques such as polarization filters.

Fig. 04
Figure 4. Adaptive Vector Filter Example. Left is before application, center is after application, right is the difference. Data were acquired with VectorSeis and without the benefit of field arrays.

Of course, these techniques rely upon the sensor system having not compromised the vector fidelity of the wavefield. In retrospect, a number of the early disappointments in multicomponent acquisition and processing can be traced back to poor vector fidelity in the sensor systems.

Looking into the future, full-wave digital recording offers several unique opportunities to improve on classical P-wave data. Early examples are very positive. Vector fidelity is proving to be the important element in overall data quality. A number of unique tools have already been developed and more are expected. As processing and interpretation tools become available for shear waves, they will make an increasing impact on seismic solutions.



About the Author(s)

Jon Tessman is currently the Chief Geophysicist for Input/Output and is based at the company’s headquarters in Stafford, Texas. Mr. Tessman has held a wide variety of exploration related positions in the Oil & Gas industry over the past 25 years. Those include various exploration and production positions with Mobil Oil, Dome Petroleum, Norcen Energy Resources (now Anadarko), and most recently Enron Oil and Gas International. In addition, he has served in various capacities at both Western Geophysical and Geco-Prakla. His experience covers all aspects of seismic acquisition, processing and interpretation. Mr. Tessman is currently engaged in many aspects of both mode converted (3C) and full wavefield (9C) seismology as they relate to the verification of VectorSeis performance. Mr. Tessman spends most of his time working with various multi-disciplinary E&P teams throughout the world helping them design, process and interpret the multicomponent data they acquire with VectorSeis.

Peter W. Maxwell is Commercialization Manager for the Input/Output, Inc. VectorSeis Product Line. During his twenty-four years of experience in the seismic industry, Pete has spent twelve years at Sensor Nederland bv, in Holland before moving to I/O, Houston in 1998. Prior to his time with I/O he worked for six years in the geophysics group of British Coal in the United Kingdom. He began his career in 1976 as a wireline logging engineer. Pete has been involved in the engineering, technical sales and customer services aspects of the business, during his career, specializing in seismic receiver technology. He earned his Bachelor of Science degree in Physics with honours in Geophysics from Liverpool University , UK, in 1976.


Suggested Reading:

Mueller, M. C., Barkved, O. I. and Thomsen, L., 1999, A strategy for vector interpretation of multicomponent ocean bottom seismic data, 61st Mtg.: Eur. Assn. Geosci. Eng., Session:P067.

Stephen, R., Gannon, J., Cain, B., Faber, K., Kappius, R., Maxwell, P., Roche, S., and Tessman, J., 1999, Quantifying Vector Fidelity: Internal Input/Output publication.

Brzostowski, M., Zhu, X., Altan, S., Thomsen, L., Barkved, O. and Rosland, B., 1999, 3D converted — wave processing over the Valhall field, 61st Mtg.: Eur. Assn. Geosci. Eng., Session:6043.

Barkved, O. I., Mueller, M. C. and Thomsen, L., 1999, Vector interpretation of the Valhall 3D/4C OBS dataset, 61st Mtg.: Eur. Assn. Geosci. Eng., Session:6042.

Reid, F. and MacBeth, C., 2000, Tests of vector fidelity in permanently installed multicomponent sensors, 70th Ann. Internat. Mtg: Soc. of Expl. Geophys., 1213-1216.

Maxwell, P., Tessman, D. J., Reichert, B. [2001], Design through to production of a MEMS digital accelerometer for seismic acquisition. First Break, 19 (03), 141 — 144.

Tessman, J., Reichert, B., Marsh, J., Gannon, J. and Goldberg, H., 2001, MEMS for geophysicists, 71st Ann. Internat. Mtg: Soc. of Expl. Geophys., 21-24.

Goodway, W., Tessman, J. [2002], Blackfoot 3C/3D test makes the point for VectorSeis. First Break, 20 (02).

Goldberg, H., Gannon, J., Marsh, J., Reichert, B., and Zavaleta, M., An Extremely Low-Noise MST Accelerometer Using Custom ASIC Circuitry, Proceedings Sensor Expo Fall 2000, 479-482.

Kappius, R., Crews, G., 2001, Adaptive Vector Filters for Ground Roll Reduction, CSEG Annual Convention Expanded Abstracts.

Faber, C.A.M. and Laroo, H.A., 2001, The Effect of Geophone Specifications on Vector Fidelity, 63rd Mtg.: Eur. Assn. Geosci. Eng., Session: P179.

Byerley, G., Clausen, C. K., Tessman, D. J., Ekofisk 2003, VectorSeis Test — Improvements in Vector Fidelity of 4C Seismic Data, CSEG Annual Convention Expanded Abstracts.

Tessman, D. J., Gruszczyk, E. Trzesnioswki, Z., Misiaczek, P., Brettwood, P. (2003). Chalupki Debnianskie Field: Improving Drilling Success in Shallow Gas Reservoirs with VectorSeis. First Break 21(2).


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