PetroSPIRE: a multimodal content-based retrieval system for petroleum applications

In this paper we present a novel content-based search application for petroleum exploration and production. The target application is specification of and search for geologically significant features to be extracted from 2D imagery acquired from oil well bores, in conjunction with 1D parameter traces. The PetroSPIRE system permits a user to define rock strata using image examples in conjunction with parameter constraints. Similarity retrieval is based multimodal search, an relies on texture-matching techniques using pre-extracted texture features, employing high- dimensional indexing and nearest neighbor search. Special- purpose visualization techniques allow a user to evalute object definitions, which can then be iteratively refined by supplying multiple positive and negative image examples as well as multiple parameter constraints. Higher-level semantic constructs can be created from simpler entities by specifying sets of inter-object constraints. A delta-lobe riverbed, for examples, might be specified as layer of siltstone which is above and within 10 feet of a layer of sandstone, with an intervening layer of shale. These 'compound objects', along with simple objects, from a library of searchable entities that can be used in an operational setting. Both object definition and search are accomplished using a web-based Java client, supporting image and parameter browsing, drag-and-drop query specification, and thumbnail viewing of query results. Initial results from this search engine have been deemed encouraging by oil- industry E and P researchers. A more ambitious pilot is underway to evaluate the efficacy of this approach on a large database from a North Sea drilling site.