Showing posts with label OilGas. Show all posts
Showing posts with label OilGas. Show all posts

Thursday, February 6, 2014

Business Information Framework (BIF)



As CIO at E&P, since early 2007 the vision to develop a “Unified BIF” has lingered around. With time and compromises, it is getting confused and often misused (as content management) and soon to be abused. A simple internet search with this term fetched abundant content and images. None of them reasonably represented what was visualized at E&P.
This post will articulate the concept of BIF as envisioned.

Framework

Framework is a term that encompasses a wide kind of thoughts, methods and products. It lacks a single specific meaning or a specific context dependent use. A term sure to confuse and complicate understanding!

  1. In computer programming, the term framework is an abstraction to describe generic functionality in software. Quite often the term is used to describe the “LOW-LEVEL” standard functionality provided for development. E.g. Web Application Framework; Ajax framework; JavaScript framework etc. --> Standard set of building blocks
  2. An enterprise architecture framework (EA framework) defines how to create and use a practice for conducting enterprise analysis, design, planning and implementation. The term architecture and framework are used to connote the ‘building blocks’ and ‘inter-relations’ that address the expected performance.  EA is divided into 4 layersTechnology{ The word technology is often undermined in IT related documents to wrongly designate exclusively Information Technology}, Applications, Data & Business and they become “domains” of the specialization in work or administration autonomy during implementation.  --> Generalization
  3. Conceptual framework or logical framework provides basis of analysis in different scales the problem. They provide means to define atomic elements and their congregations to derive higher-order. --> Abstraction & Scale

This post will use the word FRAMEWORK to specific characteristics around ABSTRACTION, GENERALIZATION and SCALE.

Boundaries

Modern business, including E&P is driven by different technologies that create i) Digital content and ii) Marketable product.
Business performs through – i) Organization; ii) Processes & Workflows; iii) Resources; and iv) Technology. Together these create the “results” --> i) digital content and ii) product. The overall inter-related hierarchies are shown in the figure.
Digital content can be classified into data, databases and unstructured content. Further, they can also be classified into the business through – asset, context, process-element and organization-element which – i) created, ii) approved and iii) uses the content.
There is a very elegant multi-dimensional attribute that is attached to every digital content – which makes it assimilate with the business per-se. 

Digital Content

Use of computers is nearly complete in most business processes. Very little content is created outside the computer realm. These occur in many different forms in a business.
ALL OF THEM HAVE – i) CONTEXT; ii) belong to ASSET; iii) and attached with ROLE. Technology and Process steps essentially provide the context and can be made sub-categories within context. 

BIF

It is the organization model of all digital contents into business boundaries – at “necessary” and “sufficient” depth. Overdoing this content organization can become deterrent to successful implementation and usage.
BIF can integrate all digital contents to their relevance in business. The implementation shall be made with suitable “computer architecture framework” that assures – security, accessibility and operability. A variety of tools, technologies, frameworks and methodologies exist to design the implementation models and operate it on modern computers.
It is relatively simple and highly generic. It covers all databases, datasets, knowledge interactions, communications, records, files, processes and people. By incorporating ‘standards’ a lot of unstructured content can be made interpretable. Simple work discipline like using a “title” for all PPT slides will go a long-way into creating indexed presentation files. 


  1. This BIF model is ABSTRACT, GENERALIZED and SCALABLE.
  2. It can be developed in cyclic phases of increasing depth and maturity
  3. Practiced systematically, it can lead to Information Maturity at the business
  4. As it is product or technology-framework – agnostic, the model can be sustained for longer periods
  5. The approach overcomes the limitations of hierarchic content management and opens avenues of knowledge discovery, structured vocabulary and ontological inference.

BIF Approach Scheme

Agile Development is mandatory for implementing and maturing BIF. It is impossible to give a’priori full functional description or define the detailed architecture for development.

Maturity CONTEXTS à
ASSETS ↓
Acquire
Explore
Appraise
Develop
Produce
India-Block1





Australia-CBM





US-Shalegas





India-Offshore1






  
Maturity CONTEXTSà
ORG-UNIT/ ROLES↓
Acquire
Explore
Appraise
Develop
Produce
Business Strategy





Acquisition Team





Exploration






  1. Start with a faceted classification of the 3(or 5) main elements for BIF at appropriate depth. Note that there shall be hierarchy while going deeper and that needs to be broadly defined and used. Examples from E&P are at level-1: which is often not sufficient (need at level-3 for effectiveness).
  2.  Each unit in the multi-dimensional faceted classification scheme is given a UID – Classification-box-id. They become the logical owners of the digital content. Role-players access the content as per the LDAP security access control.
  3. Create a workflow system that traces ASSET-maturity and provide it to the personnel holding different roles in the Asset-team. Digital contents they create are automatically indexed and mapped to the place in the faceted classification. All CONTENTs have method to automatically detect and stay at the relevant slot in its classifications together. An email, meeting notes, short-note, technical report, model data, approval-note – all of them stay together in context|asset framework.
  4. CONTENTs are provided with metadata elements like – 1) Type classifiers {e.g. Note, Record, Report, etc.}; 2) Nature {e.g. Draft, Approved, Final}; and 3) Few other
  5. The classification is matured with hierarchic details, the incorporation of additional levels; more detailed asset hierarchy (Blockà Prospect à Field à Well à Reservoir à Sample à Analysis) is relatively easy.
  6. All other standard content management functions can be implemented upon the BIF.

Content: Collaboration

Learning Environment is the direction for creating successful organizations. Content: Collaboration is a mutual complementing need or scenario. The two must come together to form an integrated content and collaborative-learning environment. Content has become a PILE – millions of documents and datasets – SPACE {Volume of Disk}! Collaboration has become uncontrolled explosion: expender – TIME {consumes}. Learning and Knowledge are typically in 1:n {?10000} proportion embedded within this SPACE-TIME maze.
Wishful needs are: 1) Create compelling content, 2) Structure and protect it, 3) Ensure it’s easy to find and accessible, 4) Manage the content life cycle, 5) Leverage collaboration through social media for content production, distribution,  access and discovery (learning or knowledge creation).
BIF provides a model to manage and provides:
  1. Organization’s personnel to communicate short, specific, context relevant
  2. Integrate content (notes, reports etc.) with communication (emails, comment etc.) cogently and consistently
  3. Provide a natural way to integrate all digital content (see figure), manage and administer its life-cycle through clear and objective methods.
  4. Provide intuitive and easy to learn and adopt mechanism {conventionally, paper was organized in E&P into Assets and Contexts}
  5. Establish a generalized and highly scalable model – that is product and technology agnostic
  6. Pave way for new possibilities like automated knowledge discovery and encapsulation.
BIF is a vision for making information tie with Business.

Monday, January 13, 2014

Leveraging Information Technology – Petrotech 2014



Petrotech is India’s premier oil & gas convention. This note is built around the deliberations at the event on 10th Jan. 

I resist using the word IT, which had become a commodity skill and is often most misused and abused term in science or technology. IT has become such a wide and overarching term that ceases to have any specific meaning or context. 

Information Technology is aptly covered by various speakers narrating in  broad terms how the entire gamut of E&P is affected by and touched by this.  Global E&P enterprise with capital outlay running about $100B/y, is natural to be touched by computer based methods of working. Often seen as a “rich” industry, deploying Petaflops or Petabytes is akin to billionaire buying Ferrari!

IT companies like system manufacturers (IBM), service providers (Wipro), E&P IS players (Schlumberger, Konsberg), E&P companies (Cairn, ONGC, RIL) and Refineries (IOCL, BP) and Consultants (E&Y, PWC etc.) contributed to the events of the day.


  1. Clearly every facet of the business has opportunity to be optimized and made efficient using Information. However, with disparate technical systems and heterogeneous data – only incremental islands of improvements are being achieved.
  2. The 1960-2010+ growth story of the E&P identifies the expanding size and use of seismic data from early CDP gathers to current 4D/4C surveys. Surely, before 2020 real-time cross-borehole seismic will be deployed in modern fields (nD, 4C – n Dimensional, 4C).
  3. Data remains an evasive dimension. E&P holds Petabytes using Petaflops – yet, << 1% of its data volumes are in databases. About 100,000 world-wide workforce of E&P professionals mostly work disconnected and never collated into a single unified “innovation crowd”. Therefore, the available mind-flops (measure of human minds working together) are very small! There is considerable misplacement of the importance when “computer science” and “computing” are treated synonymous. This is already proving costly to innovation in E&P.
It came about – E&P is very Conservative!

      4.  Digital oil field is surmised into integrated operational framework driven by unified information interchange. Having implemented this at my current work place, I felt consoled that this achievement is prevalent and common metric for these i-fields! Questions remain:

1. Has this paved way for new insights in to high-frequency (DCS capture at milli-seconds), high-volume (>100,000 tags) phenomenon that drive the HC fields?

2. Are there new micro-reservoir modeling approaches in place?

3. Are there any measures to say what was possible and what is achieved?


     5.  Computer technology has gone around cycles from consolidation (main-frames) to distribution (cloud). Data-centric computing (driven by Hadoop) is the new development. Comments that “cloud” is not yet suitable to E&P HPC work is interesting considering JPL has used Amazon cloud for nearly same kind of work. The IBM Watson is important – not because it won Jeopardy, but because it used certain computer science methods that extract intelligence from different kinds of data structures (and unstructured data). There is pretty little in E&P space that deploys the core techniques of Watson. Prospector – was in 1980, the most successful rule-based “expert-system”. It never became a tool for E&P. Watson-Jeopardy is similarly a novel break-through – but trying to use it in E&P is amusing.


     Rich people buy new car models – whether they use, disuse or abuse. Rich E&P companies buy new HPC and data-technologies in the same parlance. Thanks to theory of “probability”, whether the god plays dice or not, Geoscientists are adept at doing it. Thanks to HPC, we now create 100s of millions of cells in 3D models of single well fields with 100 realizations – only to drill next appraisal well – DRY! There is little consciousness or measure of the Value of Information.  


I have to quote J.C.Davis (1982 book p10 – Statistics and Data Analysis in Geology, John Wiley). “The presentation of masses of numbers, all expressed to eight decimal places, overwhelms the minds of many people and numbs their natural skepticism. … output usually will bluff all but a few critiques, and those who understand and comment also do so in equally obtuse terms. … The greatest danger, is … led to the most ludicrous conclusions, totally blind to any reality beyond the computer ..”.  I never understood how doing 1000 realizations of a transformation based on a linear-relationship will reduce uncertainty. What was possible from a single carefully created “seismic inversion” study is now made into 100 realizations occupying a terabyte and giving the “same” GCOS (Geological Chance-of-Success) to the new well location!


     6. SMAC work was shown in integrated information system development at 2 of India’s largest refinery companies. The downstream has seen Specific, Measureable, Achieved, Challenging task of information integration with diverse systems and ERP. This is an important pointer to E&P companies. The clarity of top management driver in Downstream is a pointer to “engineering” –versus “geoscience” mindset that differentiates these two industries.

      7. An aspect that all E&P companies love to highlight is the “knowledge worker” and “ageing work-force”. The fact that in 2013, 100:1 ratio of applications were made to E&P professional positions, is a pointer of “plenty”. Quantity is never a substitute to Quality. If the systems that attract the students, the curriculum that moderates them and the evaluations that elevate them are weak – the 100:1 also cannot give you quality man-power. 
The moot question is what caliber can such weak systems produce in the industry?


That is what I dealt with at the workshop. (updated slide pack at http://www.slideshare.net/srikantg/the-reality-of-big-crew-change-in-ep). 
  • E&P is progressing far-too-slowly as a Scientific methodology or a Technology practice. 
  • There is an urgent need to reassess the approach with other high-performance sciences and industries AND take corrective action towards DISD.

E&P is changing slowly. Demand models of the Hydrocarbons and great prices are ensuring profitability. New fronts are opening in Deep-water and Shale-gas. None of these automatically imply that the data, method, analysis and inference are evolving at transformational rates. I firmly believe that this slow adaptation and change of E&P is moot cause for human resource crunch issue. The methodology developed 20-50 years ago remains "closed" with the "experienced" and remains "relevant"!

One may not agree with uncomfortable things.

  • IT is largely doing a service or commodity to E&P – NOT driving innovation
  • E&P is comfortable with the current efficiencies due to its special status
  • World at large doesn’t know how to question E&P as only 100,000 people know details clearly about it, among the 7.2 billion!

Mflops in smartphones and Gigabytes disk space on Google-Drive are driving for more resources. CIO is concerned that in similarly Petabytes and Petaflops are deployed and expanded in E&P.


It is Win-Win-Win. Computer companies can sell their ware; Service companies can sell proprietary black-boxes; Oil companies can sell oil at their demanded price.