Data Room Management for Mergers and Acquisitions in the Oil and Gas Industry

Data Room Management and Rapid Asset Evaluation - Theory and Case Studies in Oil and Gas, Volume 66 introduces frameworks and workflows that help streamline the data room process, highlight the essential data that must be assembled in the permitted time window, and accelerate the subsequent assessment of the opportunity. The book combines theory with case studies, some of which describe lessons learned directly by the author himself. Methodologies are presented that can be used immediately by those involved in the technical and commercial evaluation of oil and gas exploration and production ventures. The book is suitable for readers with a wide spectrum of experience, from those who are newcomers to the strange world of data rooms, to those diehards who may have spent too many hours in them. The purposes, strategies, and tactics of data rooms are explained, along with some suggestions on how to survive them, and how to get a fit-for-purpose evaluation in front of the decision makers in the shortest timeframe possible. Demonstrates what makes a good data room, including how vendors attract potential buyers to attend and how the latter can decide whether they should go or not Presents how to prepare for a data room, what needs to be done there, and how to evaluate the assets on offer as quickly as possible Covers which essential data should be gathered and questions to ask Suggests how to avoid common ‘banana skins’ when under pressure to provide a rapid but reasonable evaluation Data Room Management for Mergers and Acquisitions in the Oil and Gas Industry Dedication About the Author Acknowledgments Preface Due diligence, definitions, and doubt 1.1 What is due diligence? 1.2 Assessing volume and uncertainty alongside value and risk 1.2.1 Ranges of recoverable petroleum volumes 1.2.2 Potential value of produced petroleum 1.2.3 Risks associated with petroleum resource exploration and development 1.3 Systems for reporting petroleum resources 1.3.1 Why is a resource definition needed? 1.3.2 Definition of reserves 1.3.2.1 What volumes are not reserves? 1.3.3 Sources of risk and uncertainty 1.3.4 Deterministic and probabilistic terminologies for reserves estimation 1.4 How reliable is reporting of resources? 1.5 Requirement for doubt and skepticism 1.5.1 Overcoming bias to ensure data quality 1.5.2 What is reasonable certainty? 1.5.3 As many answers as there are auditors The data room 2.1 What is a data room? 2.1.1 Physical data room 2.1.2 Virtual data room 2.1.3 VDR and PDR combination 2.1.4 Virtual Physical data room 2.1.5 Designated VDR downloader 2.2 Why are data rooms important? Data room documentation 3.1 Need for a common language between sellers and buyers 3.2 The teaser 3.3 The confidentiality agreement 3.3.1 Definition of what is and what is not confidential information 3.3.2 Caveat emptor disclaimer 3.3.3 Mental impressions exclusion 3.3.4 Return or destruction of data 3.3.5 Time limit for CA 3.3.6 Breach of CA and choice of law 3.4 The information memorandum 3.4.1 The essence of an IM 3.4.2 Reading between the lines of an IM 3.4.2.1 Offering procedure 3.4.2.2 Importance notice 3.4.2.3 Executive summary 3.4.2.4 Confidential information 3.4.2.5 Country overview 3.4.2.6 Corporate organizational structure 3.4.2.7 Operational overview 3.4.2.8 Reserves summary 3.4.2.9 Future drilling schedule 3.4.2.10 Lifting costs 3.4.2.11 Decommissioning External help and advice 4.1 Selling the deal 4.2 DIY or get external help? 4.2.1 External adviser services 4.2.2 Choosing an external adviser 4.2.3 Fees for external help and advice 4.2.4 Caution with deal finders Before the data room 5.1 Management responsibilities 5.2 PDR team selection 5.3 Travel checklist 5.4 Data preparation 5.4.1 Data uploaded to the virtual data room 5.4.2 Data formats 5.5 Equipment for physical data rooms In the data room 6.1 Role of the seller in the data room 6.2 What to do in the data room 6.3 What not to do in a data room 6.4 Hierarchy of data requirements 6.5 Role of team leader 6.6 Role of the driller 6.6.1 Well planning 6.6.2 Drilling operations 6.6.3 Drilling logistics 6.6.4 Drilling environment and safety 6.7 Geoscientific roles 6.7.1 Role of the geologist 6.7.2 Role of the geophysicist 6.7.3 Role of the geomodeler 6.7.3.1 Reviewing the 3D geomodel workflows 6.7.3.2 Checking the 3D geomodel 6.7.4 Common errors of in-place volumes 6.8 Role of the petrophysicist 6.8.1 Shale volume 6.8.2 Porosity 6.8.3 Water saturation 6.8.4 Net-to-gross 6.8.5 Fluid contacts 6.8.6 Saturation height function 6.9 Role of the reservoir engineer 6.9.1 Water drive sufficiency 6.9.2 Compartmentalization 6.9.3 Reservoir fluids 6.9.4 Reservoir heterogeneity 6.9.5 Well and field performance 6.9.6 Initialization of the dynamic simulation model 6.9.7 History match and prediction from the dynamic simulation model 6.10 Role of the production engineer 6.10.1 Well productivity 6.10.2 Oil production operations 6.10.3 Gas production operations 6.11 Role of the facilities engineer 6.11.1 Field production and export facilities 6.11.2 Operating costs and production efficiency 6.11.3 Capital costs 6.11.4 Planning issues and governmental verification 6.11.5 Local suppliers and contractors 6.11.6 Infrastructure and refineries 6.12 Role of the economist 6.12.1 Petroleum price forecasts and sales contracts 6.12.2 Economic model 6.13 Role of the lawyer After the data room 7.1 What to do after the data room 7.1.1 Ongoing data management and evaluation 7.1.2 Knowledge capture post-PDR 7.1.3 Ongoing dialog between seller and buyers 7.2 Traffic light confidence check on due diligence 7.3 Submitting a bid or dropping out 7.4 Return or destruction of confidential data When things go pear shaped 8.1 VDR in Russian? не ланикуйте! 8.2 2P or not 2P, that is the question 8.3 Reality check seller's regional exploration performance 8.3.1 Creaming curve 8.3.2 ``Missing fields'' analysis 8.4 Fudging hydrocarbon charge risk 8.5 Assigning value to NGLs in an exploration farm-in 8.6 Send the right people to the PDR 8.7 Confirm the gas specification 8.8 Poor choice of analog 8.9 Beware restricted access to production data 8.10 Insist on well check shot data 8.11 Site visits are sometimes highly recommended 8.12 Time gentlemen please 8.13 Check fluid gradients all the way to the top 8.14 Caution with well test press releases 8.15 Reality check seller's exploration portfolio claims 8.16 Tendency to overestimate 2P EUR in the North Sea 8.17 Check PDR workstation capability with seller 8.18 Beware seller's dynamic simulation models without production history 8.19 Check ``automatic water shut-off'' option in seller's dynamic model 8.20 Drainage by older producers can affect future well recovery 8.21 Poor analog selection can lead to reserves write down 8.22 Verifying high CO2 content of a gas field when faced with limited conflicting data Tips for quicker focused evaluation 9.1 EMV as a straight line for rapid farming analysis 9.1.1 Definition of EMV 9.1.2 Farm-in analysis using straight line EMV 9.1.3 Farm-out analysis using straight line EMV 9.2 Pareto analysis for ranking assets 9.3 Tri-plot for ranking assets 9.4 Other EMV-based plots for ranking exploration portfolios 9.5 Risk cover 9.6 PVT checker 9.7 Probability distribution fitter 9.8 Analog checklist 9.8.1 Is the seller's chosen analog appropriate? 9.8.2 Has the seller demonstrated reservoir continuity? 9.8.3 Has the seller demonstrated economic producibility? 9.9 Analog selection tools 9.10 Back to the future with DCA 9.10.1 Composite field DCA is often optimistic 9.10.2 Using oil cut to identify interference between producing wells 9.11 Thiessen polygon mapping 9.12 Bubble maps to review reservoir drainage and sweep 9.13 Buyer's own simpler versions of seller's models Glossary QC of inputs to estimates of PIIP and TRV A1.1 Estimating in place conventional petroleum resource volumes A1.1.1 Stock tank oil initially in place A1.1.2 Associated gas A1.1.3 Gas initially in place A1.1.4 Associated condensate A1.2 Estimating PIIP input parameter ranges and distributions and common errors A1.2.1 Monte Carlo simulation and choosing parameter distributions A1.2.2 Gross rock volume A1.2.3 Reservoir pressure and temperature A1.2.4 Oil formation volume factor A1.2.5 Gas expansion factor A1.2.6 Porosity A1.2.7 Hydrocarbon saturation A1.2.8 Net-to-gross A1.3 Reservoir drive mechanisms and recovery factor in conventional reservoirs A1.3.1 Water drive A1.3.2 Solution gas drive A1.3.3 Gas cap drive A1.3.4 Identifying reservoir drive mechanisms A1.4 Factors influencing recovery of conventional petroleum resources BOE, a misleading unit A2.1 Where does the 6:1 rule of thumb come from? A2.2 Local rule, not global standard A2.3 Gas composition is important A2.4 The 50% rule to decide whether to report cfge or BOE Estimating exploration and development risks A3.1 Chance of discovery A3.1.1 Elements of the likelihood of geological success A3.2 Chance of development A3.2.1 Elements of the likelihood of commercial production A3.2.2 Example of estimating the chance of development A3.3 Avoid using chance of development to aggregate resources Resource reporting systems that meet international standards A4.1 Stock exchange requirements for resource reporting A4.2 PRMS Curiouser and curiouser A4.3 COGEH A4.3.1 Differences between COGEH and PRMS A4.4 NPD A4.4.1 Differences between NPD and PRMS A4.5 SEC A4.5.1 Differences between SEC and PRMS References Index A B C D E F G H I L M N O P Q R S T U V W