Seismic Guided Drilling: Near Real Time 3D Updating of Subsurface Images and Pore Pressure Model

Similar documents
Geohazards have a direct impact on the drilling and

C031 Quantifying Structural Uncertainty in Anisotropic Depth Imaging - Gulf of Mexico Case Study

Optimizing Drilling Performance by Wellbore Stability and Pore-Pressure Evaluation in Deepwater Exploration T. Klimentos, Schlumberger

2010 SEG SEG Denver 2010 Annual Meeting

Syn-drill Seismic Imaging through Seismic Guided Drilling A Case history from East coast India deep water example

IPTC PP Challenges in Shallow Water CSEM Surveying: A Case History from Southeast Asia

Summary. Tomography with geological constraints

SPE These in turn can be used to estimate mechanical properties.

Reducing Uncertainty Ahead of the Bit

OTC OTC PP. Abstract

Th D Interpolation and Extrapolation of Sparse Well Data Using Rock Physics Principles - Applications to Anisotropic VMB

URTeC: Summary

Abstract. 1. Introduction. Geophysics Engineer-Schlumberger 2. M.Sc. Petroleum-PEMEX 3,4 Geologists-PEMEX

Drillworks. DecisionSpace Geomechanics DATA SHEET

NOTICE CONCERNING COPYRIGHT RESTRICTIONS

Advances in Geosteering

So I have a Seismic Image, But what is in that Image?

URTeC: Abstract

P-326. Summary. Introduction

Imaging complex structure with crosswell seismic in Jianghan oil field

Anisotropic Depth Migration and High-Resolution Tomography in Gulf of Mexico: A Case History

Analysis of stress variations with depth in the Permian Basin Spraberry/Dean/Wolfcamp Shale

Corporate Houston, TX... (713)

Wellsite Consulting Services Diversified Well Logging LLC. All Rights Reserved.

3D VTI traveltime tomography for near-surface imaging Lina Zhang*, Jie Zhang, Wei Zhang, University of Science and Technology of China (USTC)

B033 Improving Subsalt Imaging by Incorporating MT Data in a 3D Earth Model Building Workflow - A Case Study in Gulf of Mexico

Stochastic rock physics modeling for seismic anisotropy

P Edward Knight 1, James Raffle 2, Sian Davies 2, Henna Selby 2, Emma Evans 2, Mark Johnson 1. Abstract

This paper was prepared for presentation at the Unconventional Resources Technology Conference held in Denver, Colorado, USA, August 2014.

SPE Uncertainty in rock and fluid properties.

Pressure Regimes in Deep Water Areas: Cost and Exploration Significance Richard Swarbrick and Colleagues Ikon GeoPressure, Durham, England

An Open Air Museum. Success breeds Success. Depth Imaging; Microseismics; Dip analysis. The King of Giant Fields WESTERN NEWFOUNDLAND:

Depth Imaging for Unconventional Reservoir Characterization: Canadian Plains Case Study

Quantitative Interpretation

X,800. X,850 ft. X,900 ft. X,950 ft. X,000 ft. GeoSphere. Reservoir Mapping-While-Drilling Service

Microseismicity applications in hydraulic fracturing monitoring

Petroleum Exploration

I. INTRODUCTION 1.1. Background and Problem Statement

SPE A Pseudo-Black-Oil Method for Simulating Gas Condensate Reservoirs S.-W. Wang, SPE, and I. Harmawan, SPE, Unocal Indonesia Co.

Velocity Update Using High Resolution Tomography in Santos Basin, Brazil Lingli Hu and Jianhang Zhou, CGGVeritas

Effects of VTI Anisotropy in Shale-Gas Reservoir Characterization

SEG Houston 2009 International Exposition and Annual Meeting

Best practices predicting unconventional reservoir quality

Reservoir properties inversion from AVO attributes

H005 Pre-salt Depth Imaging of the Deepwater Santos Basin, Brazil

Seismic Velocities for Pore-Pressure Prediction. Some Case Histories.

Chapter 1. Introduction EARTH MODEL BUILDING

Real Time Monitoring of Pore Pressure using an Effective Basin Model Approach

region includes nine states and four provinces, covering over 1.4 million square miles. The PCOR Partnership

QUANTITATIVE INTERPRETATION

Anisotropic tomography for TTI and VTI media Yang He* and Jun Cai, TGS

MITIGATE RISK, ENHANCE RECOVERY Seismically-Constrained Multivariate Analysis Optimizes Development, Increases EUR in Unconventional Plays

Predicting Gas Hydrates Using Prestack Seismic Data in Deepwater Gulf of Mexico (JIP Projects)

Realtime Geopressure and Wellbore Stability Monitoring while Drilling. Eamonn Doyle VP Real-time Operations

Summary. Introduction

G002 An Integrated Regional Framework for Seismic Depth Imaging in the Deepwater Gulf of Mexico

The SPE Foundation through member donations and a contribution from Offshore Europe

Pluto 1.5 2D ELASTIC MODEL FOR WAVEFIELD INVESTIGATIONS OF SUBSALT OBJECTIVES, DEEP WATER GULF OF MEXICO*

Characterization of Fractures from Borehole Images. Sandeep Mukherjee- Halliburton

Tu N Fault Shadow Removal over Timor Trough Using Broadband Seismic, FWI and Fault Constrained Tomography

Log Ties Seismic to Ground Truth

Reprinted From. Volume 03 Issue 03-JulY 2010

Demo Schedule and Abstracts

Information From Walk-Away VSP and Cross-Hole DataUsing Various Wave Modes: Tower Colliery, South Sydney Basin

Use of prestack depth migration for improving the accuracy of horizontal drilling in unconventional reservoirs

Heterogeneity Type Porosity. Connected Conductive Spot. Fracture Connected. Conductive Spot. Isolated Conductive Spot. Matrix.

SeisLink Velocity. Key Technologies. Time-to-Depth Conversion

Seismic Driven Pore Pressure Prediction

J.V. Herwanger* (Ikon Science), A. Bottrill (Ikon Science) & P. Popov (Ikon Science)

Petrophysical Data Acquisition Basics. Coring Operations Basics

Summary. Introduction

NAPE 2011 Lagos, Nigeria 28 November-2 December 2011 Extended Abstract

Summary. Introduction

SPE MS. Abstract

FRACMAN Reservoir Edition FRED. Success in Fractured Reservoirs FRACMAN TECHNOLOGY GROUP

The elastic properties such as velocity, density, impedance,

Downloaded 09/09/15 to Redistribution subject to SEG license or copyright; see Terms of Use at

Calibration of anisotropic velocity models using sonic and Walkaway VSP measurements

Isotropic and anisotropic velocity model building for subsalt seismic imaging

MUDLOGGING, CORING, AND CASED HOLE LOGGING BASICS COPYRIGHT. Coring Operations Basics. By the end of this lesson, you will be able to:

Downloaded 10/25/16 to Redistribution subject to SEG license or copyright; see Terms of Use at

Integrating rock physics and full elastic modeling for reservoir characterization Mosab Nasser and John B. Sinton*, Maersk Oil Houston Inc.

Applying Stimulation Technology to Improve Production in Mature Assets. Society of Petroleum Engineers

June 2014 RELINQUISHMENT REPORT LICENCE P1454

Towed Streamer EM data from Barents Sea, Norway

Modeling Optimizes Asset Performance By Chad Baillie

Abstracts ESG Solutions

Pore Pressure Estimation A Drillers Point of View and Application to Basin Models*

Overpressure detection using shear-wave velocity data: a case study from the Kimmeridge Clay Formation, UK Central North Sea

Interpretation and Reservoir Properties Estimation Using Dual-Sensor Streamer Seismic Without the Use of Well

We A10 12 Common Reflection Angle Migration Revealing the Complex Deformation Structure beneath Forearc Basin in the Nankai Trough

Anisotropic Seismic Imaging and Inversion for Subsurface Characterization at the Blue Mountain Geothermal Field in Nevada

Constrained Fault Construction

Implementation of geomechanical model to identify total loss zones

Fr Reservoir Monitoring in Oil Sands Using a Permanent Cross-well System: Status and Results after 18 Months of Production

Mapping Faults With Lightning, Natural-Sourced Electromagnetics (NSEM) Louis J. Berent Dynamic Measurement, LLC

Improved Interpretability via Dual-sensor Towed Streamer 3D Seismic - A Case Study from East China Sea

MicroScope. Resistivity- and imagingwhile-drilling

Integration of seismic and fluid-flow data: a two-way road linked by rock physics

AADE 01-NC-HO-43. result in uncertainties in predictions of the collapse and fracture pressures.

Transcription:

IPTC 16575 Seismic Guided Drilling: Near Real Time 3D Updating of Subsurface Images and Pore Pressure Model Chuck Peng, John Dai and Sherman Yang, Schlumberger WesternGeco Copyright 2013, International Petroleum Technology Conference This paper was prepared for presentation at the International Petroleum Technology Conference held in Beijing, China, 26 28 March 2013. This paper was selected for presentation by an IPTC Programme Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the International Petroleum Technology Conference and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the International Petroleum Technology Conference, its officers, or members. Papers presented at IPTC are subject to publication review by Sponsor Society Committees of IPTC. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of the International Petroleum Technology Conference is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of where and by whom the paper was presented. Write Librarian, IPTC, P.O. Box 833836, Richardson, TX 75083-3836, U.S.A., fax +1-972-952-9435 Abstract Seismic guided drilling (SGD) is a workflow that uses drilling information from a well being drilled and existing surface seismic data plus offset well information, to recalibrate and update the existing 3D earth model, including seismic image, pore pressure, fracture gradient, and geological hazards in order to reduce drilling uncertainty and mitigate drilling risk ahead of bit. The modern practices in drilling heavily rely on the predrill earth models. The predrill models often are not precise due to the inherent non-uniqueness in our remote sensing techniques. While LWD/SWD and WL provide useful information along the borehole, they offer little understanding about the rock property ahead of bit. SGD is such a technology that constantly improves the 3D earth model ahead of the bit through the integration of current well measurements with existing surface seismic data, with a turnaround time on the order of 24 hours. It not only corrects the model error behind the bit but also improve predictions ahead of the bit. The lack of adequate technologies, measurements, and turnaround time limitations, has made this type of optimum utilization/integration of seismic data and well data impractical until now. Recent developments in model building, rapid and accurate imaging technologies, and the availability of new well measurements, aided with modern engineering and computation, have made this optimum combination a reality. SGD has been used in several high-profile deep water HPHT wells worldwide with considerable successes. The technology is especially valuable in areas of low exploration activity or high geological complexity. The paper focuses on illustrating the concept of SGD technology and presenting a field example in the Gulf of Mexico, USA. Introduction An accurate 3D earth model, in terms of spatial position of geological structure, fault, and reservoir rock properties is the key for the success in petroleum exploration and exploitation drilling. Particularly formation pore pressure profile, more accurately, the drilling window profile (which is the corridor between pore pressure and fracture gradient versus drilling depth) determines the drillability of a proposed target. Seismic information has been extensively used for earth model building, including imaging and pore pressure estimation, in petroleum basins worldwide. These tasks usually take months even years to accomplish due to geological complexity and demand for large-scale computation. Despite of the effort, the earth model, including formation pore pressure and other beyond imaging products, is still error-prone due to the lack of resolution, high noise level, and the intrinsic nature of nonuniqueness. The error not only directly affects the success rate of exploration but also poses engineering hazards throughout drilling. Often the ground truth measurements from drilling such as LWD, SVWD, VSP, MDT, LOT, etc. show that pre-drill prediction is not accurate enough. These real time measurements are crucial information for recalibrating and updating the predrill earth model in order to improve predictions in the deep section. In the past, the recalibration is usually done post-drill due to the time and effort needed. For this reason, the recalibration with the latest drilling information does not impact the actual drilling of the well.

2 IPTC 16575 To maximize the information usage and to optimize the drilling, a workflow named, Seismic Guided Drilling (SGD) is devised. SGD builds an earth model, including imaging, formation pore pressure, and other beyond imaging products. It updates the earth model multiple times at designated depths during drilling. The target SGD depths are of either geological or engineering importance, such as pressure ramps, fault locations, casing depths, etc. This paper focuses on illustrating the SGD workflow and presenting a field example in the Gulf of Mexico. Seismic Guided Drilling A typical SGD study covers an area of ~10 by 10 km around a proposed well location. It usually includes a baseline study in pre-drill to construct the initial earth model and several updates to the earth model while drilling. In baseline the best pre-drill earth model is generated through the application of modern seismic imaging and inversion and offset well calibration (, pore pressure, lithology). The process is constrained by the first principle of rock physics (Dutta et al., 2012). This is done by taking only a small volume around the well location and producing an image only in this drilling volume of investigation using advanced, typically computationally intensive, techniques that may not be practical for large data sets. Furthermore, localization of the process allows the creation of a model representative of the local geology. Figure 1. Pre-drill planning of a well with the new process. The local seismic data are re-processed for best local high-resolution pre-drill image, and pore pressure and fracture gradient estimate. Benefits are improved pre-drill planning of well trajectory, casing points, and mud weights Pre-drill analysis of a well in SGD is made using the seismic image and estimated rock properties important for drilling such as pore pressure, fracture gradient, and other geomechanical properties derived from reprocessed baseline volumes. Figure 1 shows an example SGD baseline seismic image, and a model, that normally would have come from the processing of a large exploration data set. A well plan is made including trajectory (blue dash-line in figure 1), casing locations, mud program, etc. The better this initial pre-drill model is the better drilling and completion plan can be. new Figure 2. Using new well data as constraint seismic data are completely re-processed and structural and and therefore pore pressure and fracture gradient uncertainty ahead of the bit is reduced. Note that the depth and lateral position of the target (blue box) has moved. As the well is being drilled, new information become available from the LWD logs, checkshots, MDT, LOT, mud weights, cuttings, drilling events, etc. These could come from LWD or intermediate wireline measurements. The new information represents the true property of the earth in the drilled interval.

IPTC 16575 3 At the depth indicated by the black-dash line shown in Figure 2, an SGD update is triggered. Seismic data are completely reprocessed by using this local information thus far as constraints (recalibration). Checkshot-constrained local tomographic inversion is used to get new velocities (Bakulin et al., 2010). This is followed by a full depth migration. An updated image with updated profile along the wellbore (red curve) is shown in figure 2. Note that the drilling target (blue box) now has moved in both vertical and lateral position. In addition, well logs are used to update the local rock model used in pore pressure prediction, and the pore pressure and fracture gradient are updated with the enhanced rock model and information in near real time. This provides key information in a timely fashion to modify the drilling program such as casing plan and mud program ahead of bit (~24 hours turnaround time). The work cannot be accomplished by any other workflow that only uses well data for model updates. As a result of the update, the drilling trajectory (blue dash-line), casing design, and mud program are adjusted in order to successfully intersect the target, as shown in Figure 3. The target would have been missed without the aid of SGD implementation on this well. In real SGD applications, model updates usually occur multiple times at designated depths which are of either exploration or engineering importance. Sometimes, SGD updates are triggered when significant errors in predrill models are detected from the LWD measurements or other drilling information. Update casing points new Update pore pressure, frac gradient Update well trajectory Figure 3. Well trajectory, casing points, and mud weights are modified based on the new image and predictions ahead of the bit. Benefit is reduced risk and/or elimination of unnecessary casings. SGD Field Example SGD workflow was tested in the drilling of well C in the Gulf of Mexico as shown in figure 4. The primary challenge was to place a 13-5/8 inch casing below a secondary fault at the interval covered within the blue circle shown. This was necessary for the hole size requirements in the final well completion. Locating both primary and secondary faults accurately was deemed critical for drilling hazard mitigation purposes. Data from one offset well, Well B (see Figure 4) were used to build a local anisotropic model extending into the new well location. However, Well B data were limited to the deeper sections and could not be used to build a reliable pre-drill model in the shallower section in the drilling volume of interest. Large uncertainties were expected in positioning of pressure changing faults on existing seismic data. It was important to improve the model and reimage while drilling using shallow information from Well C itself to reduce the positional uncertainty of the fault locations. LWD, checkshot, and wireline data were acquired all the way up to the mudline to complement the offset well for a good model. Anisotropic models were created in several stages by seismic tomography where the vertical velocities were constrained by well data. The volume for models included the offset well to ensure a proper tie to that well B in addition to the well being drilled. Multiple updates were triggered throughout the drilling. For each updated model, the surface seismic data were reimaged while drilling, enhancing fault location accuracy in time to impact drilling and casing decisions. The desired casing location was accurately predicted within +/- 10 ft (Lower panel in figure 5), comparing to ~750 ft error existed in the legacy data (shown in figure 5). The final SGD update is made at ~1500 feet above the planned casing depth. Comparison of structure maps for the key horizon between legacy and the latest update is shown in figure 6. Faults definition and positioning, and structure accuracy are much enhanced in the latest update. SGD update not only helps the well placement but also reduces uncertainty in planning of subsequent development wells (including side tracks). Figure 7 shows the faults enhancement of the final update as against the legacy images. Substantial fault shifts are observed

4 IPTC 16575 between the two stage images. Accurate fault positioning in the SGD updated image is crucial for the correct setup of the 13 5/8 inch casing for the test well, which is the key objective of the SGD test project. The field test shows that SGD is a powerful workflow to recalibrate and enhance the earth model in real time for drilling decisions, by incorporating new information from the well under drilling. It utilizes the latest imaging technology and produces model update in a very short time. Well C would be extremely challenging to drill without the aid of SGD implementation. Well C Field Test Well B Figure 4. In a Gulf of Mexico well (Well C) a primary challenge was to place the 13-5/8 inch casing below a secondary fault due to hole-size requirements in the final well completion. Locating both primary and secondary faults accurately was critical. Large uncertainties were expected in the positioning of events using the existing seismic image. While-drilling data from Well C was used to improve the model and reimage to reduce the positional uncertainty of the fault locations. Conclusions Successful drilling planning and execution can greatly benefit from an accurate high-resolution earth model obtained from seismic data integrated with real time well information. The workflow is called SGD (Seismic Guided Drilling). SGD is the only workflow that can update subsurface geological and geophysical models and provide in time corrections to predrill mud weights, casing depth, fracture gradients, and other geological hazard predictions. The workflow for the first time enables the application of traditional geological and geophysical analysis in the context of active well drilling. References Bakulin, A., Woodward, M., Nichols, D., Osypov, K., and Zdraveva. O., 2010. Building tilted transversely isotropic depth models using localized anisotropic tomography with well information. Geophysics, 75, D27 D36. Dutta, N. C., S. Yang, and J. Dai, 2012. Advances in Depth Imaging Technology: Rock Physics Guided Migration of Seismic Data in 3D. Proceedings of Indonesian Petroleum Society, 36th Annual Conference, May, 2012.

IPTC 16575 5 Well-image depth mis-tie > 750 ft Well-image depth mis-tie < 10 ft (a) Figure 5. The left panel shows the legacy image that existed prior to the project. An anisotropic model was built using the offset well (Well B) data and seismic data were depth migrated. The right panel shows the result giving the best possible predrill image at the baseline stage. There are a significant (>750 ft) depth shift in the new image compared with the legacy image.drilling showed that the new image for this horizon was within 10 ft of the prediction. (b) (a) Figure 6. The same comparison as in Figure 5 in plan view. The left panel is the legacy image that existed prior to the project. The right panel shows the new image. The updated image shows a better description of structure and faults becasue of the utilization of all available data and better focusing provided by the new anisotropic local model. The updated image has high frequency content than the legacy image due to parameterization of legacy processing. (b)

6 IPTC 16575 (a) Figure 7. The left panel is the legacy image that existed prior to the project. The right panel is the seismic image after the final update. Both have faults interpretations displayed. There was a significant shift in the spatial locations of the faults targeted for casing point. The lower fault is believed to sealing. (b)