PetroSPIRE: A multi-modal content-based retrieval system for petroleum applications

Abstract

In this paper we present a novel content-based search application for petroleum exploration and production (E&P). The target application is specification of and search for geologically significant features to be extracted from 2-dimensional imagery acquired from oil well bores, in conjunction with 1-dimensional 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 evaluate 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 example, might be specified as a 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, form 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&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.