An Interactive 5-Day Training Course
Subsurface Data Types & Integration Workshop
Integrating Every Subsurface Data Type Together
Secure your spot now!
Duration
5 Days
Price
$ 3,000
Starting From
27 Sep 2027
Home Geology and Geoscience Subsurface Data Types & Integration Workshop
Subsurface Data Types & Integration Workshop
Have Questions ?
Subsurface Data Types & Integration Workshop - GG-DINT-PEA27
| Code | Date | Time | Duration | Location | Currency | Early Bird Fee Per Person |
|---|---|---|---|---|---|---|
| GG-DINT-PEA27 | 27 Sep - 01 Oct 2027 | 10 AM CST | 4 Hours Per Day |
Online |
USD |
3000 |
Need this for a group? We deliver the same course in-house — face-to-face at your location or online — tailored to your assets and team level. Contact info@peassociations.com
Boost your team's skills and your budget! Enjoy group discounts for collaborative learning. Send an inquiry to info@peassociations.com.
Subsurface Data Types & Integration Workshop
This workshop covers subsurface data types and their integration. It works through what each measurement actually measures, scale and volume of investigation, resolution limits, data quality and its assessment, reconciling measurements across scales, resolving conflicting data, building integrated interpretations, data gaps and their consequences, acquisition programme design and the documentation of an integrated data position.
Description
Subsurface interpretation combines measurements of entirely different kinds: a core plug measures a few cubic centimetres, a log reading averages a fraction of a cubic metre, a well test samples thousands of cubic metres and a seismic sample averages a volume larger still. When these disagree, which they routinely do, the disagreement is often not an error but a consequence of the different volumes each samples. Understanding this is the basis of data integration.
This workshop covers the data types and their reconciliation. What each measurement actually measures is established first, data type by data type, distinguishing the physical quantity measured from the property inferred from it. Scale and volume of investigation follow, covering the quantitative comparison across data types. Resolution limits are then developed. Data quality and its assessment follow. Reconciling measurements across scales is then addressed in detail, since this is the core skill. Resolving conflicting data follows. Building integrated interpretations is then developed. Data gaps and their consequences follow. Acquisition programme design is addressed. The workshop closes with documentation of the data position.
Core, log and well test permeability differ and all three can be right. A core plug measures the permeability of a few centimetres of rock, usually selected as intact and representative; a log derived permeability is an estimate from a correlation over a half-metre interval; a well test gives an effective permeability over a radius of tens to hundreds of metres, including any fractures, high permeability streaks and barriers within that volume. These are different quantities. A test permeability ten times the core value usually indicates a feature the core missed, which is information rather than error.
Each measurement infers a property rather than measuring it. A density log measures the attenuation of gamma rays and porosity is calculated from it using an assumed matrix density; a resistivity log measures electrical conductivity and saturation is calculated from it using an exponent and a water resistivity. The uncertainty in the inferred property therefore includes the uncertainty in the assumed parameters, which is frequently larger than the measurement uncertainty. Knowing which parameters a value depends on tells you how reliable it is.
Conflicting data is usually the most informative data in the set. When the pressure data says two sands are connected and the fluid chemistry says they are not, when the core says the rock is tight and the test says it flows, when the seismic amplitude indicates gas and the well found water, something specific is happening and finding out what it is advances the interpretation more than any amount of consistent data. The common response is to discard the inconvenient measurement, which discards the information.
Finally, acquisition programmes should be designed from the questions, and most are designed from habit. A logging suite run because it is the standard suite, a core cut because the interval is the reservoir, a test performed because the well is a discovery: each may be right and none has been justified against a question. Designing the programme from the decisions the data must inform, and stating what each measurement will establish, produces programmes that cost less and deliver more.
By the end of this workshop, participants will be able to:
- State what each subsurface measurement physically measures
- Identify the parameters each inferred property depends on
- Compare data types by scale and volume of investigation
- Assess resolution limits for each data type
- Assess data quality and reliability
- Reconcile measurements made at different scales
- Diagnose conflicting data and extract information from it
- Build integrated interpretations across data types
- Identify data gaps and their consequences
- Design acquisition programmes from the questions to be answered
The workshop works on field data sets containing genuine conflicts between data types. Participants reconcile core, log, test and seismic measurements, diagnose the causes of disagreement, and build integrated interpretations. Acquisition programmes are designed from stated decisions and critiqued. Scale comparisons are calculated rather than asserted.
Organisations sending participants to this workshop will:
- Reconcile data across scales rather than discarding conflicts
- Extract information from disagreeing measurements
- Assess data reliability including parameter dependence
- Build integrated interpretations systematically
- Design acquisition programmes from decisions
- Reduce acquisition spend that answers no question
Participants will:
- Know what each measurement measures
- Compare data across scales quantitatively
- Reconcile conflicting measurements
- Build integrated interpretations
- Assess data quality critically
- Design acquisition programmes
- Geoscientists working across data types
- Petrophysicists integrating core and log data
- Reservoir engineers using static data
- Geophysicists calibrating to well data
- Operations geologists specifying acquisition
- Graduate geoscientists building data understanding
- Technical staff reviewing integrated studies
Module 1 - What Each Measurement Measures
- Core measurements and their directness
- Gamma ray and natural radioactivity
- Density log and gamma attenuation
- Neutron log and hydrogen index
- Sonic log and travel time
- Resistivity and electrical conductivity
- Nuclear magnetic resonance measurement
- Spectroscopy and elemental measurement
- Pressure measurement
- Seismic reflection measurement
- Measured quantity against inferred property
- Parameters each inference depends on
Module 2 - Scale and Volume of Investigation
- Core plug volume
- Whole core volume
- Log depth of investigation by tool
- Vertical resolution by tool
- Volume averaged by a log reading
- Well test radius of investigation
- Test volume calculation
- Seismic resolution and volume
- Fresnel zone and lateral resolution
- Interference and tracer test volumes
- Quantitative comparison across types
- Scale as the explanation for disagreement
Module 3 - Resolution Limits
- Vertical resolution of logs
- Thin bed effects
- Shoulder bed effects
- Thin bed resolution methods
- Seismic vertical resolution
- Tuning thickness
- Seismic lateral resolution
- Core sampling resolution
- Sampling density and representativeness
- Features below resolution
- Consequences of unresolved features
- Stating resolution in interpretations
Module 4 - Data Quality Assessment
- Log quality indicators
- Hole condition effects
- Tool malfunction recognition
- Repeat section assessment
- Depth control between data types
- Core recovery and damage assessment
- Core analysis protocol effects
- Pressure measurement quality
- Test data quality and validity
- Seismic data quality assessment
- Processing effects on seismic
- Documenting quality assessments
Module 5 - Reconciling Across Scales
- Core to log calibration
- Depth matching core to logs
- Upscaling core measurements to log scale
- Log to test permeability reconciliation
- Permeability averaging across scales
- Identifying features the core missed
- Log to seismic upscaling
- Rock physics for scale bridging
- Blocking and averaging methods
- Which scale applies to which question
- Consistent property sets across scales
- Documenting scale reconciliation
Module 6 - Resolving Conflicting Data
- Conflict as information
- Pressure against fluid chemistry conflicts
- Core against test conflicts
- Seismic against well conflicts
- Log against core porosity conflicts
- Saturation conflicts between methods
- Systematic investigation of a conflict
- Checking for measurement error first
- Checking for scale explanation
- Geological explanations for conflict
- Carrying unresolved conflicts forward
- Avoiding discarding inconvenient data
Module 7 - Building Integrated Interpretations
- Integration sequence and dependencies
- Framework first integration
- Calibration chains
- Consistency requirements across products
- Single net definition across disciplines
- Facies and rock type reconciliation
- Property consistency
- Dynamic data as the arbiter
- Iterating the integration
- Documenting integration decisions
- Deliverables from an integrated study
- Reviewing an integration
Module 8 - Gaps and Acquisition Design
- Identifying data gaps
- Consequences of each gap
- Gaps that affect decisions
- Acquisition programme design from questions
- Logging suite specification
- Core programme specification
- Pressure and sampling specification
- Test specification
- Seismic acquisition specification
- Cost against value of each measurement
- Measurements that answer no question
- Documenting the data position for a study
Upon successful completion of this training course, delegates will be awarded an official Certificate of Completion issued by the Petroleum Engineers Association (PEA), an ISO 9001:2015 certified training organization. The certificate carries 10 Credits and formally records the total learning hours completed.
Each certificate is signed by the Course Facilitator and the CEO of the Petroleum Engineers Association, and serves as verifiable proof of professional training that delegates can present to employers and professional bodies worldwide.
Frequently Asked Questions
All course bookings made through PEA are strictly non-refundable. By registering for a course, you acknowledge and accept that all fees are payable in full and are not subject to refund under any circumstances, including changes in personal or professional commitments or partial attendance.
PEA reserves the right to make reasonable adjustments to course content, trainers, or schedules where necessary, without entitling delegates to a refund. Comprehensive details of each course — including objectives, target audience, and content — are clearly outlined before enrolment, and it is the responsibility of the delegate to ensure the course's suitability prior to booking.
For any inquiries related to cancellations or bookings, please contact our support team, who will be happy to assist you.
