DECLINE CURVES LIE (SOMETIMES) Interpreting Production Beyond the Spreadsheet The curve fits. The forecast looks reasonable. The EUR justifies the investment. Then the wells underperform, the plateau breaks earlier than predicted, and the capital program built on optimistic projections delivers disappointing returns. You have seen this pattern before. Decline Curves Lie (Sometimes) is not another textbook on Arps equations or a manual for curve-fitting software. It is a systematic examination of why production forecasts built on well-fitted decline curves so often turn out to be wrong—and what to do about it. Drawing on field case studies, technical post-mortems, and seventeen years of cross-discipline experience, Andi reveals the hidden mechanisms that distort decline curve interpretation: • Artificial lift changes misread as reservoir recovery • Compression additions creating phantom b-factors • Choke management policies that look like depletion • Water breakthrough inflating hyperbolic parameters • Organizational pressures that systematically favor optimism • Field aggregation that hides individual well physics • Economic constraints masquerading as physical limits Each chapter examines a specific distortion mechanism in depth—not through mathematical derivation, but through the operational, physical, and organizational context that the decline curve cannot see but that determines what the curve actually means. The book provides: ✓ Detailed anonymized case studies showing how interpretive errors translate into capital allocation failures ✓ Diagnostic frameworks for identifying when a curve is contaminated by non-reservoir factors ✓ Structured checklists for operational review before conducting decline analysis ✓ Practical guidance on communicating interpretive uncertainty to decision-makers ✓ Appendices providing reference material on bias patterns, surface-production interactions, and economic constraints This book is for technical professionals who: • Conduct production decline analyses and want to avoid systematic interpretive errors • Review forecasts and need tools to challenge optimistic projections • Make capital decisions based on production forecasts and need to understand their limitations • Certify reserves and require diagnostic frameworks for identifying organizational bias • Manage asset portfolios and have watched too many forecasts fail in predictable ways