The application of remote sensing to Canadian petroleum exploration: promising and yet unexploited

Abstract This paper reviews some of the successful applications of digital remote sensing to petroleum exploration in different parts of the world. They include the updating of existing geologic maps, the location of anomalies related to hydrocarbon seepage, and the integration of the digital imagery into geologic databases to assess hydrocarbon potential on a given scale. Although most of these techniques are useful potentially in the Canadian environment, there seems to be some reticence in this country towards the use of remotely sensed data. Based on discussions with a number of industry and research personnel, an analysis is made of the reasons why Canadian geoscientists have not yet taken advantage of this readily available tool. Some explanations include: (1) the poor resolution of sensors such as the LANDSAT MSS, (2) the till and vegetation overlying parts of the country, and (3) the fact that some areas of the country are so well mapped that it is felt that a system such as LANDSAT could add no relevant information. Conversely, several considerations would seem to favor widespread usage of remotely sensed data in Canada now that the spectral and spatial resolutions of operational sensors are constantly improving. It is possible to map geologic features such as faults from remotely sensed imagery even if they are buried beneath deep till. The vegetation which covers so much of the land surface can provide both structural and geochemical information. There remain large expanses of the country that are relatively unexplored. Finally, considerable expertise exists in Canada in geoscience data integration and image processing, much of it related to mineral-resource work; this expertise may be directed towards petroleum-resource evaluation. Some procedures are recommended for Canadian petroleum geologists in order that they may derive maximum benefits from remotely sensed data.

[1]  T. M. Lillesand,et al.  Remote Sensing and Image Interpretation , 1980 .

[2]  Andrea G. Fabbri,et al.  GIAPP: Geological image-analysis program package for estimating geometrical probabilities , 1980 .

[3]  Ronald J. P. Lyon,et al.  Simultaneous use of geological, geophysical, and LANDSAT digital data in uranium exploration , 1979 .

[4]  A regionalized multivariate approach to target selection in geochemical exploration , 1978 .

[5]  B. N. Koopmans Side‐looking radar, a tool for geological surveys , 1983 .

[6]  J. P. Ford,et al.  Seasat Orbital Radar Imagery for Geologic Mapping: Tennessee-Kentucky-Virginia , 1980 .

[7]  G. F. Bonham-Carter,et al.  Integration of mineral resource data for Kasmere Lake area, Northwest Manitoba, with emphasis on uranium , 1983 .

[8]  Ronald J. Staskowski,et al.  The Leelanau Benzie And Grand Traverse, Michigan Anomalies - Structural And Geobotanical Indicators Of Hydrocarbon Microseepage , 1984, Other Conferences.

[9]  A. Goetz,et al.  Geologic remote sensing. , 1981, Science.

[10]  R. Duda,et al.  Recognition of a Hidden Mineral Deposit by an Artificial Intelligence Program , 1982, Science.

[11]  V. Slaney,et al.  Landsat images of Canada : a geological appraisal , 1981 .

[12]  Chang-Jo F. Chung,et al.  SIMSAG: Integrated computer system for use in evaluation of mineral and energy resources , 1983 .

[13]  Computer image processing: Geologic applications , 1978 .

[14]  Lowell E. Bogart,et al.  Synergistic Value Of Interpreting Imagery Of Various Scales For Oil And Mineral Exploration , 1984, Other Conferences.

[15]  Richard B. McCammon,et al.  Characteristic analysis of geochemical exploration data , 1977 .

[16]  Robert N. Colwell,et al.  Manual of remote sensing , 1983 .

[17]  F. Sabins Remote Sensing: Principles and Interpretation , 1987 .

[18]  R. O. Duda,et al.  PROSPECTOR—A computer-based consultation system for mineral exploration , 1978 .

[19]  M. T. Halbouty,et al.  Geologic Significance of Landsat Data for 15 Giant Oil and Gas Fields , 1980 .

[20]  Charles Elachi Radar Images of the Earth from Space , 1982 .

[21]  J. Taranik Principles of computer processing of Landsat data for geologic applications , 1978 .

[22]  G. Bonham-Carter Statistical Association of Gold Occurrences with Landsat-Derived Lineaments, Timmins-Kirkland Lake Area, Ontario , 1985 .

[23]  Andrea G. Fabbri,et al.  Image processing of geological data , 1984 .

[24]  P. Molnar,et al.  Cenozoic Tectonics of Asia: Effects of a Continental Collision: Features of recent continental tectonics in Asia can be interpreted as results of the India-Eurasia collision. , 1975, Science.

[25]  T. Kasvand Computerized vision for the geologist , 1983 .

[26]  Alexander F. H. Goetz,et al.  Remote sensing for exploration; an overview , 1983 .

[27]  R. Crippen,et al.  Detection of subsurface features in Seasat radar images of Means Valley, Mojave Desert, California , 1984 .

[28]  Donald A. Waterman,et al.  A Guide to Expert Systems , 1986 .

[29]  D. Lueder Aerial photographic interpretation : principles and applications , 1959 .

[30]  F P Agterberg,et al.  Preliminary geomathematical analysis of geological, mineral occurrence and geophysical data, southern District of Keewatin, Northwest Territories , 1981 .

[31]  Richard B. McCammon,et al.  Characteristic analysis—1981: Final program and a possible discovery , 1983 .

[32]  M. D. Matthews,et al.  Remote Sensing And Surface Hydrocarbon Leakage , 1984, Other Conferences.