The Why, What and How (WWH) of a drilling operation

The Why, What and How (WWH) of a drilling operation

This page is a business case describing a case study or a pilot project involving one or several industry partners

Average: 5 (1 vote)

1 users have rated this content. We would love to have your vote as well. Log in and rate!


After a drilling accident, the investigation often points at poor management and problems in the organization. While everyone in the team may literally depend on each other for their lives, they still fail to gather and share insights about the situation. There's a lack of what we call collective learning. The Why-What-How (WWH) approach points to the three learning dimensions of the screening method developed that has been coined the 4xE (Ends, Effectiveness, Efficiency and Efficacy) method which measure this aspect of the organization and highlight areas of improvement. At ConocoPhillips, we had the opportunity to further develop the 4xE method showing how it can be applied to improve collective learning, sensemaking, quality assurance and safety management. In practice collective learning in fact improves both safety and performance and the apparent struggle between the two is perhaps more a symptom of weak organizational capabilities in the industry.

Facilitating sensemaking for safer and efficient drilling


We want to show how to improve safety performance in drilling using the argument that learning is an essential prerequisite for change and improvement including efficient decision making. The cognitive processes involved in both are intertwined. In our research with ConocoPhillips (CopNo) we have found some criteria for how to achieve Collective learning by addressing the building and sharing of insight for a group of individuals who are somehow mutually dependent on each other in order to perform well together. Organizational learning is included here. We initially argue that collective learning must be reinforced in the oil and gas industry to improve the human factors associated with safety.  A collection of literature on major accidents in the industry has been studied, not least the recent reports addressing the Macondo disaster.  Human factors associated with poor leadership, organizational weaknesses and cognitive limitations of the individual have played an important part in such accidents. We have observed that these shortcomings are pronounced causes in a number of instances and that they are recurrent beyond the oil and gas domain. This suggests that there exists a fundamental flaw in our ways to deal with them. We further argue that a systematic approach to collective learning addresses the root of the causes identified. We show that the 4XE method (4xE stands for Ends, Effectiveness, Efficiency and Efficacy ) with the WWH (Why-What and How) learning charts can be used to identify issues associated with these causes as a standard approach to guard against future incidents.  We further show how this can be incorporated in a capability concept in order to create an instrument for safe and continuous improvement. 


Figur 1: Collective learning illustrated as a capability


In doing so we have addressed some of the drilling practices in ConocoPhillips. This exercise has revealed a performance oriented approach that is truly based on a collective learning approach similar to the ones that underpins the theoretical work that we have one in the past.  However, we also note that the safety aspects related to management, organization and individual is not an explicit and integral part of this approach. By applying WWH-learning some issues have been identified with the CopNo approach that can be systematically eliminated. We propose a way to deal with this and show how this can be included in CopNos intendend performance dash board.  Gages that monitor the human factors that we have addressed in our work are proposed. These could be able to determine such issues related situational awareness capabilities, reduced collective cognition, suppression of safety focus, reduction in front line workers involvement and problems with intra communication.  It is our intention to elaborate on how such sensors can be developed in the future.


The language of management dashboards


During our stay with CoPNo we learned of their resolve to combine daily drilling reports, well documentation, cost reports and other information sources into a "big picture" display of the drilling operation. Such displays are often termed "management dashboards" and aim to rapidly give management the information they need to make their decisions. The "dashboard" is an analogy with the instrument panel of a car, presenting the most salient information needed for the one in charge to steer the car, or the organization. But while such a display may tell the manager about the ongoing drilling operation, it's also telling a different story. The dashboard implies that what is reported is important, what is omitted is not. The design of the dashboard reveals what the organization expects the day-to-day priorities of a manager to be.


During our stay, the CoPNo dashboard was yet to be finalized, but it was already becoming apparent that productivity would feature prominently on the dashboard. The reporting breaks down time spent into productive and non-productive time. The productive time is defined as the sum of the "best composite well time" which is the shortest possible duration and "lost time". If a driller becomes concerned about safety and decides to slow down or temporarily stop the operation, this will be recorded as "lost time", something to get rid of. Would the drilling operation be judged differently if this time had been added into "best composite" or even recorded not as lost time but "gained safety"? While the proposed dashboard was to gather information from many sources, the project risk sheet was so far absent from the proposal. How much of the non-productive time is actually time spent fulfilling the stated safety objectives of the operation? Continuing the car analogy, it was as if the dashboard had only a speedometer and no warning light telling you if the engine was overheating.

Other key information

207 results
Below, you will find related content (content tagged with same topic(s) as this business case)
Content type: Publication

Conditions for Resilient Operations of Complex Systems Undergoing Technological Alterations

Emergence of risk in IO and resilience perspective for emergency handling

Content type: Publication

Construction of risk images in the oil and gas production industry

Three categories of risk images: 1) traditional risk images, 2) technological optimism and 3) reconfigured risk images.

Content type: Publication

CRIOP: A Human Factors Verification and Validation Methodology That Works in an Industrial Setting

Methodology to verify and validate safe and efficient operations in control centers

Content type: Publication

Cross Cultural Collaboration

Masteroppgave - Ledelse av teknologi

Content type: Topic page

Daily production optimization

Determine the optimal production strategy in day to day operations.

Content type: Presentation page for handbook
Content type: Publication

Daily Production Optimization for Subsea Production Systems

Methods based on mathematical programming and surrogate modelling

Content type: Presentation

Decision Support Framework for Well Location at Martin Linge Oil Field (IO13 poster)

Optimization of Well Placement Using Derivative-Free Methods

Content type: Report

Decision Support Tool for Dynamic Barrier Management for Erosion Integrity

Applicability of barrier management methods to support critical decisions to help prevent and mitigate the occurrence of major accidents.



Center for research-based innovation, NTNU, Sintef, IFE