Stress Calibration from Drilling Data

Transcription

1 Stress Calibration from Drilling Data Possibilities and Limitations Stefan Wessling, Anne Bartetzko, Thomas Dahl October 6 th 2011 FKPE Workshop Hannover

2 Overview Introduction wellbore stability model & calibration Calibration sources in detail Summary 2

3 Wellbore Stability Pressure Window Pressure Pressure window Fracture gradient (FG) Mud weight / ESD ECD Pore pressure gradient (PPG) Collapse gradient (CG) Depth 3

4 Pressure Calibration Sources Pressure window Fracture gradient (FG) Mud weight / ESD ECD Connection gas Ballooning Depth Pore pressure gradient (PPG) Collapse gradient (CG) Differential sticking Formation pressure PPG SFG FG Leakoff Fracture Drilling-induced tensile fracture accidental intentional Pack-off Cavings Stuck pipe 4

5 Real-Time Wellbore Stability Procedure Alerts & advices Alert Traffic light No breakout observed, as expected Small breakout observed, small breakout expected Observed and expected breakout orientations coincide Control Small breakout expected but not observed Observed and expected breakout orientations do not coincide Large breakout observed, but not expected Acquisition Observed breakout width larger than expected Very large breakouts observed Processing Analysis Interpretation Telemetry Acquisition Processing Analysis Interpretation 5

6 Pressure Calibration Sources Pressure window Fracture gradient (FG) Mud weight / ESD ECD Connection gas Ballooning Depth Pore pressure gradient (PPG) Collapse gradient (CG) Differential sticking Formation pressure PPG SFG FG Leakoff Fracture Drilling-induced tensile fracture accidental intentional Pack-off Cavings Stuck pipe 6

7 Calibration: Formation Pressure Tests (FPT) Calibration of pore pressure Only possibility to measure pore pressure Only in permeable formations (e.g., sand) Shale Sand Depth Pore Pressure FPT Shale Pore pressure modeled Exponential vs Sand Pore pressure measured Linear Gradient controlled by pore fluid density Shale 7

8 Pressure Calibration Sources Pressure window Fracture gradient (FG) Mud weight / ESD ECD Connection gas Ballooning Depth Pore pressure gradient (PPG) Collapse gradient (CG) Differential sticking Formation pressure PPG SFG FG Leakoff Fracture Drilling-induced tensile fracture accidental intentional Pack-off Cavings Stuck pipe 8

9 Calibration: Drilling-Induced Tensile Fractures Observed in downhole electrical images Stress direction, magnitude En-echelon in deviated wells Memory (120 sectors) Real-time (32 sectors) Weng,

10 Image Interpretation Annular Pressure Uncertainty 10

11 Image Interpretation Annular Pressure Uncertainty Scenario1: ft Wireline image Scenario2: ft While-drlg image cf. Pei et al., Constraining in-situ stresses at BETA by analysis of borehole images and downhole pressure data. Paper IPTC presented at the International Petroleum Technology Conference held in Doha, Qatar, 7 9 December 2009.

12 Image Interpretation Annular Pressure Uncertainty Wireline While Drilling

13 Pressure Calibration: Drilling Fluid Pressure window Fracture gradient (FG) Mud weight / ESD ECD Pore pressure gradient (PPG) Collapse gradient (CG) Depth 13 cf. Wessling et al., Calibrating Fracture Gradients - An Example Demonstrating Possibilities and Limitations. Paper IPTC presented at the International Petroleum Technology Conference held in Doha, Qatar, 7 9 December 2009.

14 Calibration: Drilling Fluid 1. Detect losses (surface logging) 2. Locate thief zones (MPR) 3. Constrain ECD causing losses 4. Calibrate fracture gradient 14

15 Pressure Calibration Sources Pressure window Fracture gradient (FG) Mud weight / ESD ECD Connection gas Ballooning Depth Pore pressure gradient (PPG) Collapse gradient (CG) Differential sticking Formation pressure PPG SFG FG Leakoff Fracture Drilling-induced tensile fracture accidental intentional Pack-off Cavings Stuck pipe 15

16 Calibration: Uncertain parameter determination Reduction by automation Breakout width, degree # Intervals Intervals right Intervals left Sample Interval 1 Interval Sample Manual (geoscientist and non-scientist probands) automated 16 cf. Wessling et al., Challenges and Solutions for Automated Wellbore Status Monitoring - Breakout Detection as an Example. Paper SPE PP presented at SPE Digital Energy Conference and Exhibition, The Woodlands, Texas, USA, April 2011.

17 Summary Advanced technology: wellbore stability prediction and monitoring while drilling Calibration is essential; requires data / information from different sources Uncertainties Models and assumptions (pore pressure gradient) Location Data resolution (images) Time interval (ECD; time-depth analysis necessary) Interpretation () 17