Standards and Enabling Knowledge, Information and Data Management in E&P

Agustin Diz

Energistics 2nd Annual Standards Summit 2007 , November 6, 2007

Data, Information, Knowledge.

Data: A collection of facts from which conclusions may be drawn. (Princeton Wordnet)

Information:Information is the result of processing, manipulating and organizing data in a way that adds to the knowledge of the person receiving it.

Knowledge:Knowledge is the awareness and understanding of facts, truths or information gained in the form of experience or learning (a posteriori), or through introspection (a priori).(Wikipedia)

Knowledge is an appreciation of interconnected details which, in isolation, are of lesser value.

Knowledge is a human trait and it is experiential

Effective and key Knowledge flows in human networks.

Introduction

Standards:

• BSI: "a published specification that establishes a common language, and contains a technical specification or other precise criteria and is designed to be used consistently, as a rule, a guideline, or a definition".

• Standards enable a common basis of understanding to exist, promoting efficiency and reliability. It can bring major competitive advantage to business.

• ISO says that standards "contribute to making life simpler, and to increasing the reliability and effectiveness of the goods and services we use".

Which is why they should be open.

Should we try to standardize everything?

Business Process Networks

• Three (broad) kinds of Network response in Processes:

• Customized (Innovation, or problems and solutions ambiguous)

• Modular (Complex: components of the problem are known, not sequence)

• Routine (Standardized work: Call Centers, insurance claims)

• How information and knowledge flow differs:

• Permeable decision boundaries, decentralized decision and info access

• Semi-permeable boundaries, role-based decision making and info access

• Defined boundaries and embedded decision and info access.

(R. Cross, J. Liedtka and L Weiss Harvard Business Review, March 2005)

Additional information:

P. Evans, B. Wolf, Harvard Business Review, July-August 2005

Business Process E&P

• Where do our processes in E&P sit (in broad terms):

• Customized (Exploration)

• Modular (Reservoir development)

• Routine (Mature field: drilling, maintenance, water injection, etc.)

• How information and knowledge flows differ:

• Exploration: Need access to people both in and out of the company, allow for new techniques and ideas for interpretation of data and information, let the technical interpreters self-organize. Validate outputs against strict checks and peer reviews.

• Reservoir: Roles in development, leadership rotates according to response based needs. Constellations of expertise. Validate integration at point of delivery.

• MF Drilling, etc.: Focus on efficiency and reliability of delivery. (output is known)

Data and Information Management today

• In general (exceptions exist) our DM and IM efforts are behind our current business needs.

• Efforts on data and information preservation are often dissociated from how it is used. Changing business needs (DOFF, e-Fields, iFields) put attention on short term.

• Data volumes, especially in seismic, production and drilling are an order of magnitude greater than they were just 10 years ago, yet in many cases we still manage or use them in the same way.

• IM and DM are still viewed, in many cases as something external to the productive business process, rather than integrated into it. (An afterthought)

Knowledge and People Management today

• We are viewed by the younger generations as an eco-unfriendly, “mature” industry.

• We tend to hold back on changing how we work. Even when introducing new technologies, these are not necessarily understood outside the “innovative inner-circle”.

• We need to set up better networking adjusted to our work needs, so as to ensure faster informal access to the knowledge and experiences of others.

• We need to help our technicians embrace change in how they use technology, data and information, but not to lose rigor (our billion dollar projects cannot be done effectively without rigorous gated processes as no single individual sees the full picture).

Taxonomies

Taxonomy: A set of controlled vocabulary terms, usually hierarchical. Once created, it can help inform navigation and search systems.

(Victor Lombardi Glossary Blog: http://www.noisebetweenstations.com/personal/essays/metadata_glossary/metadata_glossary .html)

Living Organisms Geographical

World

Country

…

Continent

E&P Geological Taxonomy?•What makes sense for our G&G&E specialists and projects?

•At what level can Projects share useful interpretation methodology? Can these be Guidelines?

Kingdom

Subphylum

…

Phylum

Ontologies

Ontology: A description of the concepts and relationships that can exist for an agent or a community of agents.

(Tom Gruber, Stanford University KSL: http://www-ksl.stanford.edu/kst/what-is-an-ontology.html )

Ontologies generally describe:

• Individuals: the basic or "ground level" objects

• Classes: sets, collections, or types of objects

• Attributes: properties, features, characteristics, or parameters that objects can have and share

• Relations: ways that objects can be related to one another (This defines the semantics)

• Events: the changing of attributes or relations

Ontologies, because they are machine-readable, allow applications to be standardized while the domain-specific information can be customized over time.

(Victor Lombardi Glossary Blog: http://www.noisebetweenstations.com/personal/essays/metadata_glossary/metadata_glossary .html

Deborah L. McGuinness, Stanford University KSL, http://www.ksl.stanford.edu/people/dlm/papers/ontologies-come-of-age-mit-press-(with-citation).htm)

Ontologies – Example

Ontologies – Example

Webs 1-2-3…Semantic (in simple terms?)

Web 1.0: One user writes. Another reads. The Web is the shared environment where reader meets writer, but they don’t interact.

Web 2.0: Writer can receive feedback from reader. Thus both read and write. Web is now a shared web space. Author and reader becomes blurred as viewpoints are exchanged. Users interact.

(Blogs, Flickr, MySpace, FaceBook,…)

Web 3.0 (?): Human interaction is supplemented by data and information flows which are machine detected and fed for decision making.

Semantic Web: A common framework that allows data to be shared and reused across application, enterprise, and community boundaries. (W3C.Org)

Some thoughts

Thinking in terms of Technical data – Decision flows

1. Interpretation systems should “push” relevant studies performed

in the company with similar geology

• Define appropriate taxonomy

• Load projects with information (interpreters, taxonomy, etc.)

2. Use integration frameworks to enable fuller workflow integration of technical and decision spaces

• Modular workflow tools and forms within them to capture decisions based on technical data and interpretations which can be seen from the tool with appropriate viewers.

• Integrate in workflow tools access to people with role-based expertise which may be found in Expert Databases.

Some thoughts

3. Our work processing tools (e.g. interpretations) do not

automatically capture key results into integrated DM/IM tools

• Quarterly working evaluation of reserves

• We still manage by “Powerpoint” rather than through integrated and drillable scorecards

How should we think about this? What do we store?

4. Asset teams have become more widespread, but we need to further connect different asset teams

• The asset team concept is the first attempt to break multidisciplinary walls leading to better networking.

• Further networking is more difficult to handle because of difficulties associated to assigning priorities outside the asset.

Some thoughts

5. This leads to the issue of training people to work in more networked environments and further integrate real time to human networks.

• Find ways to strengthen our networks (ONA as a tool, associated with Strategy and Results).

• Younger generations are getting more exposed to networking in their studies and through the Web 2.0. Build on this!

• There is work being advanced on Web 3.0 and Semantic Webs. I challenge us to think if we can:

• Define a first simple Taxonomy for G&G

• Define a first E&P Ontology and link it to our Operational events and information tools

• Define and monitor events to link our People Networks more thoroughly through our information/communication interfaces (Exploration Drilling)

• Think in terms of events-monitoring and resolution, as well as more effective processes.

Conclusions – Food for discussion

• Define a program to connect human networks with operation and interpretation events to enable more productivity. (Are we considering the strategic human-technology implications in work such as DOFF?)

• Objectives should be clear, and focused, with

• Long-term goals sitting on short-term (<1-yr) productive releases (Linux-like model?).

• A clear roadmap with concrete value added in yearly increments.

• The whole industry needs to work together (Producers, Service Companies) to create a strong underpinning vision and strategy to bring added value to the whole industry.

Conclusions – Food for discussion

• Discuss further:

• Interpretation: work on open G&G&E Taxonomy v1.0

• Implement/adapt current interpretation tools to have this taxonomy

• Identify at what level it becomes useful to users to develop workflows.

• Operations: work on E&P Ontology 1.0.

• Adapt it to RTO and DOFF/eField/iField events as first step

• Working on extended networking and KID needs for this

• Future: Which events need to drive change in network response?

Thank you!