[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Guillot et al., 2024 - Google Patents

Machine Learning Prediction of the Lost Circulation Events at the Well Planning Stage

Guillot et al., 2024

Document ID
17876562740519087205
Author
Guillot V
Ruzhnikov A
Corona M
Karpfinger F
Publication year
Publication venue
Offshore Technology Conference Asia

External Links

Snippet

Well construction process is often accomplished by multiple challenges, where lost circulation is one of the having most sifnificant impact. The downhole losses, partial or total, in many cases associated with karst, fractures, caverns or large voids, which cannot be …
Continue reading at onepetro.org (other versions)

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/40—Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging
    • G01V1/44—Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging using generators and receivers in the same well
    • G01V1/48—Processing data
    • G01V1/50—Analysing data
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B47/00—Survey of boreholes or wells
    • E21B47/10—Locating fluid leaks, intrusions or movements
    • E21B47/1015—Locating fluid leaks, intrusions or movements using tracers: using radioactivity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V5/00—Prospecting or detecting by the use of nuclear radiation, e.g. of natural or induced radioactivity
    • G01V5/04—Prospecting or detecting by the use of nuclear radiation, e.g. of natural or induced radioactivity specially adapted for well-logging
    • G01V5/08—Prospecting or detecting by the use of nuclear radiation, e.g. of natural or induced radioactivity specially adapted for well-logging using primary nuclear radiation sources or X-rays
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B49/00—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
    • E21B49/08—Obtaining fluid samples or testing fluids, in boreholes or wells
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B43/00—Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells
    • E21B43/25—Methods for stimulating production
    • E21B43/26—Methods for stimulating production by forming crevices or fractures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B25/00—Apparatus for obtaining or removing undisturbed cores, e.g. core barrels, core extractors
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V99/00—Subject matter not provided for in other groups of this subclass
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V11/00—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS prospecting or detecting by methods combining techniques covered by two or more of main groups G01V1/00 - G01V9/00
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V2210/00—Details of seismic processing or analysis
    • G01V2210/60—Analysis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation

Similar Documents

Publication Publication Date Title
Khan et al. Fracture Height Prediction Model Utilizing Openhole Logs, Mechanical Models, and Temperature Cooldown Analysis with Machine Learning Algorithms
Koolivand-Salooki et al. Application of genetic programing technique for predicting uniaxial compressive strength using reservoir formation properties
Abdulmalek et al. Pore pressure prediction while drilling using fuzzy logic
Ouladmansour et al. Integrating drilling parameters and machine learning tools to improve real-time porosity prediction of multi-zone reservoirs. Case study: Rhourd Chegga oilfield, Algeria
Kristensen et al. Formation Fluid Sampling Simulation: The Key to Successful Job Design and Post-Job Performance Evaluation
Srivastava et al. Recovery factor prediction for deepwater Gulf of Mexico oilfields by integration of dimensionless numbers with data mining techniques
Burns et al. The challenges of shale gas exploration and appraisal in Europe and North Africa
Ganiev et al. Pressure Maintains System Optimization Recommendations by Integrated Analysis of Well-Tests, Logs and Pulse-Code Interference Tests
Lam Tran et al. Machine learning workflow to identify brittle, fracable and producible rock in horizontal wells using surface drilling data
Guillot et al. Machine Learning Prediction of the Lost Circulation Events at the Well Planning Stage
Farooq et al. Characterization of karst development using an integrated workflow in an Upper Cretaceous carbonate reservoir from onshore field, United Arab Emirates
Ali et al. Integrating 4D seismic data with production related effects at Enfield, North West Shelf, Australia
Mousavi Mirkalaei et al. Numerical simulation modelling of well tests for a frac-pack completion well in a shallow sand reservoir
Buechler et al. Root cause analysis of drilling lost returns in injectite reservoirs
Zulkipli et al. The Guiding Principle of Well Placement to Maximise Hydrocarbon Recovery through Enhanced Reservoir Characterisation and Prolific Seismic-Driven Approaches
Pinous et al. Application of an integrated approach for the characterization of a naturally fractured reservoir in the West Siberian basement (example of Maloichskoe Field)
Afifi et al. Real-Time Compressional Sonic Log Prediction from Drilling and Mud Gas Data Using Machine Learning
Freeman et al. A New Facies Classification Scheme Using Gamma Ray and Bulk Density Logs, With Multiple Practical Applications in North Kuwait Heavy Oil Fields
McPhee et al. Sand Management in Bongkot Field, Gulf of Thailand: An Integrated Approach
Fondyga et al. Extending the Range of Multidetector Pulsed Neutron Logging and Nuclear Modelling Applications for Reservoir Surveillance in the Columbus Basin
Isemin et al. Utilization of big data analytics and advanced formation modelling for detection of kicks in drilling operations
Bounoua et al. Applied Natural fracture characterization using combination of imagery and transient information: Case studies from Cambro-Ordovician tight sandstones of Algeria
McGeer et al. Dynamically Conditioned Modeling to Address Development Challenges in a Highly Complex Fractured Basement Reservoir, Yemen
Khan et al. Integration of Formation and Drilling Parameters to Generate a Deterministic ROP Model
Cedillo et al. Maximizing Recovery in Deep-Water Gulf of Mexico Assets. Surveillance in Complex Subsalt Reservoirs