The E&P industry is a highly technical and complex world which is inhabited by skilled professionals of many different specializations and backgrounds working all over the globe. In order for an organization to perform effectively, it is very helpful to have a shared view of that world and a common vocabulary to describe its artifacts, processes and challenges. Over the past two years, we have developed a multi-faceted taxonomy that describes the realm of technical services in the upstream E&P domain. It comprises the areas of E&P disciplines, application methods and environments, technical services, and problem diagnoses. This taxonomy is finding wide use within our technical communities and has been embodied into computer-based applications in the areas of collaboration (workspaces and wikis), knowledge capture, expertise identification, field technical support and "smart" enterprise search. This paper discusses our methodology in establishing and reviewing the E&P taxonomy within a large technical community and how we are applying it to solve real-world business problems.

Today's oil and gas industry relies increasingly on integrated multi-disciplinary services to provide effective risk management, wellbore and reservoir delivery while minimizing operating costs, cost of failure and non-productive time (NPT). New collaboration technologies enable the rapid storage, transfer and consumption of information and require robust but flexible knowledge management techniques to fulfill the requirements of a global learning organization. New tools need to be developed and successfully implemented tools need to be expanded to enable cross-disciplinary teams and communities the ability to capture, share and reuse validated knowledge efficiently. This paper presents how a single-domain lessons-learned system was extended to represent the entire spectrum of the upstream industry; assuring interdisciplinary information is reusable in multiple communities and market segments. The paper presents the challenges inherent in leveraging a common classification scheme; lessons-learned framework, enterprise platform, and search-and-retrieval systems with the goal of connecting people and making the collective knowledge seamlessly accessible across different business units, time zones and geographies. Also discussed is how building a common framework and incorporating the lessons-learned system into communities of practice, training and certification programs helps drive acceptance/implementation of the program. Finally, we showcase how the system has been used to deliver game-changing performance in time savings to locate relevant information and how re-use of stored knowledge enables performance improvements in wellbore delivery.

Onshore drilling in China is very diverse, ranging from wells drilled relatively straightforward in a matter of days to more complex geological environments where drilling can take several hundred days. Recently, this market has increasingly opened up to international operators and service companies, presenting opportunities to introduce new approaches to drilling performance optimization. To best capture the performance potential in any given application it is necessary to gain a detailed understanding of the complex drilling and production environment. This requires an understanding of many important variables, including: ○Macro components—Operators, geographic locations, organizational structure, decision makers, drilling activity, achievable market penetration.○External factors—Technology vendors, products, service organization, market strategies, organizational strengths and weaknesses○Drilling applications—Application breakdown, drilling issues, best practices and opportunities This enables an organization to optimize its technology and service portfolio in a holistic approach to develop system solutions that achieve its objectives and key performance indicators (KPIs), and assist operating companies to overcome drilling challenges, deliver reductions in non-productive time (NPT) and invisible lost time (ILT), and improve overall performance. This paper demonstrates how one organization in China used a proven Knowledge Management process and award-winning KM software to build a knowledge base of expertise in the main onshore China oilfields. The authors will detail the process of knowledge extraction and the methods used to document this experiential knowledge, allowing its communication and collaborative re-use in Communities of Practice across the organization. As a first step in a long-term strategy, the authors will demonstrate through two case-studies how this knowledgebase has been re-used delivering savings to an international operator with a 25% reduction in drill bit consumption. Furthermore, the knowledge base was applied for a domestic operator, realizing drilling time of 38 days less than planned, eliminating unnecessary trips and increasing the overall percentage of productive on- bottom drilling time.