Gravity and Magnetic Methods for Oil & Gas and Mineral Exploration and Production

Course Description

Gravity and magnetic data are among the oldest geophysical data acquired for the purpose of resource exploration and exploitation. They currently also have the widest areal coverage on the Earth, span a great range of scales and play important roles in mineral, energy and groundwater arenas. The interpretation methods have evolved from data map-based visual inspection, various map enhancements and depth estimation, to quantitative interpretations based on inversions and integrated modeling.

In particular, 3D inversion techniques have emerged as a major component in this evolution. The availability of 3D inversion techniques has advanced potential-field interpretation from ‘anomaly bump hunting’ to 3D imaging of the subsurface by reconstructing the distribution of density or magnetic properties in various geological units and, thereby, have shifted interpretations from the data domain to the model domain.

Similarly, inversion techniques are also poised to make major contributions to integrated modeling and interpretation, as well as to differentiating and characterizing geology, geological processes and reservoir dynamics. This course will focus on the methodology, numerical computation, solution strategy and applications of 3D physical property inversions of gravity and magnetic data sets.

The course is designed to have two tracks in order to meet the different needs of the EAGE community in mineral exploration and in oil & gas exploration and production. We achieve this by dividing the course into two parts: methodologies common in potential-field methods in Part I and discussion of tools and applications specific to mineral exploration or oil & gas reservoir monitoring in Part II.

Course Outline

Part I: Common concepts and methodologies

  1. Fundamentals of potential-field data observed in gravity, gravity gradiometry, and magnetic surveys.
  2. Data processing methods based on equivalent source technique and inverse formulation.
  3. 3D gravity and magnetic inversions and the practical strategies for their efficient solution and applications to large-scale problems.
  4. Binary inversion potential-field data in 3D.
  5. Gravity gradiometry.

(option) Part II: Mineral exploration track

  1. Inversion and interpretation of magnetic data affected by remanent magnetization.
  2. Case histories from mineral exploration.

(option) Part II: Oil & gas track

  1. Time-lapse monitoring of oil and gas reservoirs.
  2. Inversion of time-lapse gravity data for reservoir properties.

Participants’ Profile

Participants are expected to have a basic background in applied geophysics and some knowledge of potential-field methods. We anticipate the geoscientists in the following areas will benefit from the course:

  • Potential-field methods
  • Mineral exploration
  • Integrate interpretation
  • Reservoir monitoring
  • Groundwater hydrology

About the Instructor

Yaoguo Li received his B.Sc. in geophysics from the Wuhan College of Geology (currently China University of Geosciences) in 1983, and a Ph.D. in geophysics from the University of British Columbia in 1992. He worked with the UBC-Geophysical Inversion Facility at UBC from 1992 to 1999, first as a Post-doctoral Fellow and then as a Research Associate. He is currently an Associate Professor of Geophysics at the Colorado School of Mines and leads the Center for Gravity, Electrical, and Magnetic Studies (CGEM) and the Gravity and Magnetics Research Consortium (GMRC). He is a co-recipient of the 1999 Gerald W. Hohmann Award, SERDP 2007 Project of the Year Award, and 2010 ASEG-PESA Laric Hawkins Award.

His research interests include inverse theory; inversion of gravity, magnetic, and electrical & EM data arising from applied geophysics; and their application to resource exploration, environmental, and geotechnical problems. He has been doing research in these areas and has developed or co-developed a number of program libraries for inverting different types of geophysical data. These include DCIP2D, DCIP3D, GRAV3D, MAG3D, GG3D, BININV3D, and AMP3D.