A Sound Approach to Drilling

Transcription

1 A Sound Approach to Drilling Of the many decisions drilling engineers make, selecting an optimal mud weight is one of the most challenging and far-reaching. Today, sonic loggingwhile-drilling tools are instrumental in making these decisions. Jeff Alford Roger B. Goobie Colin M. Sayers Ed Tollefsen Houston, Texas, USA Jay Cooke Helis Oil & Gas Houston, Texas Andy Hawthorn John C. Rasmus Sugar Land, Texas Ron Thomas PPI Technology Services Houston, Texas For help in preparation of this article, thanks to Ron Blaisdell, New Orleans; Lennert den Boer, Calgary; Joaquin Armando Pinto Delgadillo and Egbonna Obi, Youngsville, Louisiana; Nick Ellson and Dale Meek, Sugar Land, Texas; and Ivor Gray, CJ Hattier and Sheila Noeth, Houston. APWD (Annular Pressure While Drilling), CDR (Compensated Dual Resistivity), FPWD (Formation Pressure While Drilling), PERT (Pressure Evaluation in Real Time), sonicvision, StethoScope and TeleScope are marks of Schlumberger. 1. For more on the development of sonar devices: (accessed February 6, 006).. For more on sonic logging: Brie A, Endo T, Hoyle D, Codazzi D, Esmersoy C, Hsu K, Denoo S, Mueller MC, Plona T, Shenoy R and Sinha B: New Directions in Sonic Logging, Oilfield Review, no. 1 (Spring 1998): Barriol Y, Glasser KS, Pop J, Bartman B, Corbiell R, Eriksen KO, Laastad H, Laidlaw J, Manin Y, Morrison K, Sayers CM, Terrazas Romero M and Volokitin Y: The Pressures of Drilling and Production, Oilfield Review 17, no. (Autumn 005): 1.. For more on underbalanced drilling: Bigio D, Rike A, Christensen A, Collins J, Hardman D, Doremus D, Tracy P, Glass G, Joergensen NB and Stephens D: Coiled Tubing Takes Center Stage, Oilfield Review 6, no. (October 199): 9. Generations of drilling engineers have struggled to visualize the dark and formidable downhole drilling environment. Today, engineers and geoscientists rely on increasingly sophisticated sensors to gather data from deep beneath the Earth s surface, understand subsurface lithology, identify geologic features, locate hydrocarbons and make a host of drilling and completion decisions. Even though our sense of sight is highly developed, it has its limitations. So, early in the 0th century, scientists began development of technologies that would allow visualization of environments that could not otherwise be seen. In 1906, Lewis Nixon invented the first sound navigation and ranging, or sonar, device, as a way of detecting icebergs. 1 Early sonar devices were passive; they could only listen. However, between 191 and 1918, World War I accelerated interest in and development of active sonar tools for submarine detection. The first active sonar technology transmitted a sound, or ping, through water. Multiple receivers called transponders detected the returning sound echo, providing data on the relative positions of static and moving objects. Today, advanced acoustic technologies have many uses in areas such as medicine, military applications and oil and gas exploration and production (E&P). Acoustic-based logging-while-drilling (LWD) tools provide data that help reduce uncertainty and allow engineers to make effective and timely drilling decisions. Data from sonic LWD tools not only help establish pore-pressure gradients, but also help define porosity and permeability, detect and type hydrocarbons, evaluate borehole stability, interpret lithology changes, monitor fluid-flow effects in the borehole and pick accurate casing-setting depths. More importantly, these data are available in real time to help engineers and geoscientists make critical decisions that affect drilling cost and efficiency (see Acting in Time to Make the Most of Hydrocarbon Resources, page ). In this article, we describe how advanced sonic tools and interpretation techniques are helping to better define the safe mud-weight window, drill deeper and optimize casing-setting depths. Field examples from the Gulf of Mexico and offshore Australia show how operators are using real-time acoustic data and wellsite-to-shore telemetry systems to limit risk and uncertainty while reducing well cost. A Pressing Need for Pressure Prediction Key to the well construction process is an understanding of the subsurface pressure environment. Changes in the normal pressure gradient affect drilling safety, casing design and setting depths, and in particular, the mudweight window. Engineers restrict the mud-weight range to sustain borehole stability, control downhole pressures and optimize casing-setting depth. Most often, the mud weight is maintained above the formation pressure at a level required to control formation stress and prevent kicks or influxes that can lead to costly well-control problems and below the fracture gradient to prevent the formation from breaking down and losing returns. Wells are also sometimes drilled with the static mud weight below formation pressure, or underbalanced. 68 Oilfield Review

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3 Spontaneous Potential (SP) Depth Resistivity Normal trend line Resistivity i it deviationi > Electric log analysis to predict pore pressure. In normally compacted sediment, electrical resistivity will increase with depth along a normal trend line (red). A deviation in resistivity from the normal trend may indicate abnormal formation pressure. The optimal mud-weight range is frequently narrow and difficult to define; this is especially true in tectonically stressed regions and in deepwater environments. Within this narrow mud-weight window, engineers balance several factors, including the minimum flow rate required for hole cleaning, downhole motor and telemetry operations and equivalent circulating and static densities. Drilling fluids such as oilbase and synthetic-base muds frequently exhibit thermomechanical and compressibility properties that vary with depth, making it difficult to optimize drilling efficiency while maintaining mud weight. Operating within the mud-weight window allows engineers to improve drilling efficiency and set casing at the best possible depth. If casing is set too shallow, well-construction cost typically increases, well depth is limited, production rate may be compromised and, in some cases, the target may not be reachable. Maintaining the mud weight within a specific window w relies on accurate determination and prediction of anomalous changes in formation pressure. The analysis of shale resistivity using wireline log data is one of the oldest methods for detecting abnormal pressure. Formation resistivity depends on porosity, the type of the fluid within the pore space and its ionic strength. Under normal compaction conditions, an increase in shale resistivity with depth corresponds to a reduction in porosity (left). An anomalous change in formation pressure is usually associated with a shift in the normal compaction trend, indicated on an electric log by a reduction in resistivity associ- ated with an increase in porosity. For the purpose of maintaining safe mud weight while drilling, information about abnormal pressure needs to be available while drilling. Although formation resistivity is one of the most common LWD measurements, several factors can have a significant effect on the data, potentially masking changes in the normal compaction trend and hindering the detection of abnormal pressure. 5 Changingg temperature in the borehole with depth alters the resistivity of formation water, while the presence of hydrocarbons considerably increases resistivity. Large deposits of organic matter may also increase resistivity, obscuring undercompaction indicators. Changes in the condition of the borehole, such as an increase in borehole diameter due to washout or caving, furtherr increase resistivity measurement error. Although many of these effects can be Depth, km Distance, km > Predicting pore pressure in the Gulf of Mexico with seismic data. In this example, the initial velocity model based on conventional stackingvelocity analysis (above left) predicts the presence of overpressure (black circle). Although pore-pressure predictions based on this information are not sufficiently accurate for drilling, a higher degree of seismic-velocity resolution can be obtained by using tomographic analysis and checkshot data to refine the velocity model (above right). Further data processing allows construction of a three-dimensional (D) pore-pressure cube (bottom right). compensated for, reliance on resistivity data alone for pore-pressure prediction significantly increases drilling risk. Geoscientists can often identify abnormally pressured formations using seismic velocities. For a given lithology, acoustic velocity usually depends on porosity: the greater the porosity, the lower the acoustic velocity. In normally com- pacted sediments, compaction increases with depth. Porosity, in turn, decreases with depth, and so the velocity of sonic and seismic waves traveling through the formation generally increases with depth (below). Deviations from this trend can often be attributed to layers of sediments that have not compacted, signaling abnormally high pressure, called overpressure. However, uncertainties in seismic velocities commonly result in depth errors, making it difficult to define exact distances to drilling hazards and geological targets. Velocity models created from seismic dataa can be improved by adding high-resolution information from sonic measurements obtained while drilling (next page). Today, geoscientists and engineers combine while-drilling and wireline 5. Aldred W, Bergt D, Rasmus J and Voisin B: Real-Time Overpressure Detection, Oilfield Review 1, no. (October 1989): Depth, km Depth, km y, km Checkshot Tomography Interval velocity calculated from stacking velocity Velocity, km/s x, km Pore pressure, lbm/galus 70 Oilfield Review

4 Normal compaction trend 0 50 Gamma Ray gapi 150 Rate of Penetration ft/h 0 Depth, ft 8,800 Attenuation Resistivity 0. ohm.m.0 Phase Shift Resistivity 0. ohm.m Sonic LWD t µs/ft 50 9,000 Divergence 9,00 9,00 9,600 Onset of overpressure Overpressured red zone 9,800,000, t 50,00 MD, ft Mud Weight Gamma Ray 0 gapi 150 Depth, ft Overburden Gradient 0 psi 5,000 Maximum Stress 0 psi 6,000 Unconfined Minimum Stress Compressive Strength 0 psi 5,000 0 psi 5,000 Fracture Losses Kick Poision s Ratio Tensile Strength 0 ( ) psi 6,000 Breakout V p /V s Ratio Friction Angle 0 ( ) 6 0 deg 50 5 lbm/galus 5 Fracture Shear Failure: Breakout Shear Failure: Echelon Shear Failure: Knockout Overgauge Caliper 5 in. 5 Diameter 5 in. 5 7,680 7,700 7,70 Safe mudweight window 7,70 7,760 7,780 7,800 7,80 7,80 7,860 > Defining mud-weight windows. Sonic velocity can be used to predict changes in the normal compaction trend that is often an indicator of abnormal pressure (top left). Unlike resistivity measurements, sonic velocity is unaffected by changes in borehole temperature and salinity. Real-time compressional-slowness measurements from sonic LWD tools are used to predict pore pressure and help define kick and borehole breakout limits (top right). Adding sonic shear measurements (bottom), available in fast formations, helps determine kick and mud-loss potential, fracture limits, and the safe mud-weight window shown in white (Track ). Various types of shear failure can also be defined (Track 5). Winter 005/006 71

5 Density Sonic slowness Acoustic impedance Reflectivity Wavelet Synthetic seismogram > Placing a bit on the seismic map using synthetic seismograms. Sonic LWD slowness data are inverted with the density measurement to produce an acoustic-impedance (AI) measurement (process from left to right). The AI is converted to reflectivity and convolved with a 5-Hz wavelet at each reflector to obtain the synthetic seismogram (right). Geophysical analysis of the seismic data determines the wavelet frequency. With increasing depth, higher frequency seismic signals are attenuated, so a lower frequency, generally 0 Hz instead of 5 Hz, is used to correlate the sonic LWD data to surface seismic measurements. This helps engineers and geoscientists place the bit on the seismic map more accurately. sonic data with checkshots to generate synthetic seismograms that are then correlated with predrilling seismic measurements, providing the drilling team with a way to locate the drill bit within the geophysical environment (above). 6 These real-time processes help engineers prepare for pressure changes before drilling into them. Generating a synthetic seismogram from LWD data involves combining transit-time ( t) data with density measurements, to produce an acoustic impedance (AI) model. This model is converted into a seismic reflectivity sequence, and then convolved with a selected wavelet to produce a synthetic seismogram. 7 A synthetic seismogram is much more useful when it is depth-calibrated with either a wireline or whiledrilling checkshot or vertical seismic profile (VSP). Although the synthetic seismogram can be generated at the wellsite, more often, the realtime data are transmitted to an engineering center for processing. Correlating a synthetic seismogram with surface seismic traces helps geoscientists and engineers place the borehole trajectory on a seismic section. Calculation of the spatial position of the borehole relative to seismic markers, or reflectors, allows the drilling team to look ahead to abnormal changes in formation pressure. Sonic Measurements While Drilling Soon after the introduction of sonic LWD measurements in the late 1990s, an operator experimented with using sonic LWD measurements to improve drilling efficiency in several major operating areas. On an exploration well in the Gulf of Mexico, USA, in an area known for abnormally pressured formations, sonic and density LWD data were transmitted from the rig to the operator s office. There, geoscientists generated a synthetic seismogram, which was correlated to the surface seismic section imaging the target zone and an overlying overpressured zone. 8 The synthetic seismogram indicated that the top of the overpressured zone was 60 ft [18 m] deeper than what the seismic section predicted. This information allowed engineers to place the casing shoe significantly closer to the overpressured zone, optimizing casing-setting depth and improving the safety and drilling efficiency of subsequent borehole sections. In another early example, BHP (now BHP Billiton) and Schlumberger demonstrated the use of sonic LWD measurements not only to calibrate seismic reflections, but also to update pore-pressure calculations ahead of the bit. 9 Several exploration wells offshore Western Australia had been abandoned prematurely due to wellbore-stability problems associated with overpressured formations. As the bit approached the predicted overpressured zone, acoustic velocity acquired while drilling was used to continuously update the velocity models derived from existing surface seismic and VSP surveys. Simultaneously, engineers at the wellsite used real-time CDR Compensated Dual Resistivity data, sonic LWD, weight-on-bit (WOB), rotary torque and rate-ofpenetration (ROP) measurements, in conjunction with the PERT Pressure Evaluation in Real Time program, to monitor changes in pore pressure a few meters behind the bit. This information was used to calibrate the porepressure predictions from the seismic and VSP data. Using multiple techniques for pore-pressure prediction, the operator accurately predicted changes in formation pressure, identified minimum mud-weight requirements and optimized casing-setting depth to construct a successful well in this hostile environment. Narrowing the Window of Uncertainty Drilling in technically demanding areas is usually associated with high cost and elevated levels of risk and uncertainty. Sonic LWD data available in real time play a key role in reducing cost, risk and uncertainty by updating models created before drilling. However, creating those models 7 Oilfield Review

6 in the first place can be a bottleneck. In 000, geoscientists began looking at opportunities to increase the speed and accuracy of while-drilling pore-pressure modeling and prediction. 11 In the deepwater Gulf of Mexico (GOM), overpressure causes major drilling hazards. Overpressure is caused by Mississippi River sedimentation that is rapidly buried compared with the time it takes for sediments to expel pore water. This prevents sediments from compacting as they are buried and causes the pore fluid to become overpressured. In undercompacted sediments, sediment grain contacts are weak, causing low rock strength and low acoustic velocities. Accurate determination of pore pressure is a key requirement to making optimized drilling decisions in these overpressured environments. Before drilling, pore pressure can be predicted using seismic velocities assuming there is a seismic survey available and processed together with a velocity-to-pore-pressure transform calibrated to offset-well data. However, this procedure takes considerable time. Synthetic seismograms can be generated quickly, compared with the time needed for analyzing seismic velocities and creating a pore-pressure cube. As engineers focus on ways to reduce risk and uncertainty, the time required to process and correlate seismic and sonic LWD data becomes critical. To speed up this process for prospects in the northern GOM, Schlumberger geoscientists developed a pore-pressure cube for the entire area using data released by the Minerals Management Service (MMS) (right). 1 Checkshot data from the MMS in the Gulf of Mexico were inverted to obtain compressional velocity versus depth below the mudline. These velocity functions were then combined with upscaled sonic logs from deepwater wells and kriged to populate a three-dimensional (D) mechanical earth model (MEM) displaying both velocity and levels of expected uncertainty. 1 By applying a threshold to the predicted kriging error, maps of undercompaction and overpressure can be restricted to specific areas of interest. For commercial projects, a confidential client subcube may be extracted from the full GOM pore-pressure cube. Any additional information provided by the operator and data acquired during the drilling process with sonic LWD and real-time pore-pressure tools is used to update the client model, increasing resolution 6. A checkshot is a type of borehole seismic survey designed to measure the acoustic traveltime from the surface to a known depth. Formation velocity is measured directly by lowering a geophone to each depth of interest, emitting energy from a source on the surface and recording the resulting signal. A checkshot differs from a vertical seismic profile in the number and density of receiver depths recorded; geophone positions may be widely and irregularly located in the wellbore, whereas a vertical seismic profile usually has numerous geophones positioned at closely and regularly spaced intervals in the wellbore. 7. A wavelet is a pulse representing a packet of energy from the seismic source. 8. Hashem M, Ince D, Hodenfield K and Hsu K: Seismic Tie Using Sonic-While-Drilling Measurements, Transactions of the SPWLA 0th Annual Logging Symposium, Oslo, Norway, May 0 June, 1999, paper I. 9. Tcherkashnev S, Rasmus J and Sanders M: Joint Application of Surface Seismic, VSP and LWD Data for Overpressure Analysis to Optimize Casing Depth, presented at the EAGE Workshop: Petrophysics Meets Geophysics, Paris, November 6 8, Pore pressure, lbm/galus > Building a three-dimensional (D) mechanical earth model in the Gulf of Mexico. Seismic, checkshot and sonic data released by the Minerals Management Service (green dots) were gathered from wells in the Gulf of Mexico (top) where pore pressure exceeded lbm/galus [1,198 kg/m ] and the predicted velocity error was less than ± 1,00 ft/s [± 66 m/s]. The data were then trend-kriged to predict pore pressure, and then plotted in a D model (bottom).. Malinverno A, Sayers CM, Woodward MJ and Bartman RC: Integrating Diverse Measurements to Predict Pore Pressure with Uncertainties While Drilling, paper SPE 90001, presented at the SPE Annual Technical Conference and Exhibition, Houston, September 6 9, Sayers CM, Johnson GM and Denyer G: Predrill Pore Pressure Prediction Using Seismic Data, paper IADC/SPE 591, presented at the IADC/SPE Drilling Conference, New Orleans, February 5, Sayers CM, den Boer LD, Nagy ZR, Hooyman PJ and Ward V: Regional Trends in Undercompaction and Overpressure in the Gulf of Mexico, Expanded Abstracts, 75th SEG Annual Meeting, Houston (November 6 11, 005): Kriging is a statistical technique used with two-point statistical functions that describe the increasing difference or decreasing correlation between sample values as separation between them increases, then to determine the value of a point in a heterogeneous grid from known values nearby. Winter 005/006 7

7 ,000 1,000 epth h, m De 1,500,000,500 epth h, m De 1,500,000,500 Sonic 1,500,000,500 V p, m/s 15 0 Pore-pressure gradient, lbm/galus lus 1,500,000,500 V p, m/s 15 0 Pore-pressure gradient, lbm/galus lus ,000 Mud weights 1,000 Mud weights epth h, m De 1,500,000,500 Sonic epth h, m De 1,500,000,500 Sonic Porepressure data 1,500,000,500 V p, m/s 15 0 Pore-pressure gradient, lbm/galus lus 1,500,000,500 V p, m/s 15 0 Pore-pressure gradient, lbm/galus lus > Reducing uncertainty with pressure data from multiple sources. The degree of uncertainty in a pore-pressure gradient is exemplified by the width and low resolution of the compressional-velocity (V p ) and pore-pressure gradient curves (1). Velocity data from sonic checkshots are added to the model, somewhat reducing pore-pressure uncertainty (). Adding mud weights from drilling reports () and physical pore-pressure measurements () refines estimates and dramatically improves pore-pressure resolution. and reducing pore-pressure uncertainty both in the immediate drilling environment and ahead of the bit (above). Along with improved modeling, technological advances in LWD tools and telemetry systems are yielding more accurate real-time measurements and in greater quantities. The sonicvision, new generation sonic-while-drilling LWD tool introduced in April 00 has increased confidence in the accuracy of real-time compressionalwave velocities. Until fairly recently, many believed that it would be impossible to achieve sonic measurements while drilling. Engineers thought that the fast acoustic-signal arrival down the tool collar from the transmitter to the receivers would dominate all the arrivals, making it impossible to discriminate and record formation arrivals. With this in mind, the designers of firstgeneration sonic LWD tools focused on mitigating direct collar arrivals. To accomplish this, the tools were designed around what is referred to as the hoop-mode frequency range of the collars. This frequency depends on the collar thickness and diameter, but for most tools, falls in a narrow band between 11 and 1 khz. At the hoop-mode frequency, acoustic waves attempt to expand the collar rather than travel down to the receiver, thereby attenuating the collar arrivals at the receivers. By designing the transmitters to fire within the narrow hoop-mode frequency band and filtering received data to the 7 Oilfield Review

8 same range, engineers hoped to receive clean and discernable formation arrivals, free from distortion caused by collar arrivals. This technique proved somewhat satisfactory for fast formations where the excitation frequency falls within the appropriate range. However, for slower formations, larger hole sizes and for lower frequency components of the wave train, such as shear and Stoneley waveforms, these first-generation tools did not excite the formation at the optimum frequency and were discarding data outside of the narrow band around the hoop mode (right). Narrow-band processing also promoted spatial aliasing, a condition in which nonformation arrivals, or processing artifacts, appear within the slowness time coherence (STC) search-band window. Aliasing depends on the frequency of the transmitted pulse, the recorded waveform frequencies and the interreceiver spacing. With an almost monofrequency system, aliasing was well-developed and led to incorrect picking of events that were not formation arrivals. Misinterpretation of signal arrivals can also limit the usefulness of acoustic data. Previous tools analyzed all acoustic arrivals within a time window associated with a depth. So within this dataset, there could be compressional, shear, mud, collar and aliased arrivals. The tool s downhole processors then discriminated the compressional arrival from other signals based on the coherency of those events. With compressional arrivals being one of the smallest events discernible in the wave train, their coherency is typically low when compared with other arrivals (below right). Early tools often confused or misidentified the data, sending incorrect values to the surface. To mitigate these problems, Schlumberger engineers designed the sonicvision tool to transmit and receive wide-band acoustic signals in a frequency range from to 19 khz, a range more likely to generate a measurable response from most formations. Acoustic shear waves are difficult to acquire with narrow-band tools because they contain lower frequencies than compressional waves. The sonicvision tool frequency is optimized to excite the formation across a significantly wider frequency band than that of previous tools. This allows both shear and compressional measurements to be routinely made while drilling in faster formations. Poweroutput levels were also increased -fold to more effectively couple the wide-band acoustic energy to the formation. Amplitude Transmitter firing Amplitude, mv 1,000 0 Stoneley energy Previous tool frequency range sonicvision frequency range Collar attenuation Compressional and shear energies 15 0 Frequency, khz > Frequency range of the new tool design. The frequency ranges of previous tools were narrowly aligned within the collar attenuation frequency. Newer tools have an expanded frequency range covering a broader spectrum of soft and hard formations (yellow bar). Lower frequency arrivals such as Stoneley and leaky-p (not shown) are now captured. Total transit time Compressional arrivals Shear arrivals Rayleigh arrivals Mud arrivals Stoneley arrivals Time, s > Acoustic wave train. Once an acoustic signal is transmitted, it travels through the formation, annular fluid, and to some degree the tool, ultimately arriving at the receiver array. Low-amplitude compressional signals (red) arrive first, followed in harder rock by the shear arrival. Newer tools take advantage of slower arrivals such as Rayleigh and Stoneley. Winter 005/006 75

9 Min Amplitude Max 0 Slowness Projection 1 Recorded Mode 0 µs/ft 0 t Shear from Receiver Array 0 µs/ft 0 t Compressional from Receiver Array 0 µs/ft 0 Depth, ft X,00 Slowness Time Coherence Peaks Maximum and Minimum t Compressional Label Limits Maximum and Minimum t Shear Label Limits t Shear from Receiver Array 0 µs/ft 0 µs/ft 0 t Compressional from Receiver Array 0 µs/ft 0 Min Amplitude Max 0 Slowness Projection 1 Real Time t Peak 1 Compressional Computed Uphole, Real Time 0 µs/ft 0 To speed data to the surface, Schlumberger recently released the TeleScope high-speed telemetry-while-drilling service. This new measurement-while-drilling (MWD) system is capable of providing enough power to run eight or more LWD tools while offering up to a fourfold increase in data rate over comparable tools. Field application of these new hardware technologies, in combination with improved pore-pressure modeling described earlier, promises to enhance drilling efficiency and reduce geologic and wellconstruction uncertainty. Advancements in sonic LWD tool design and telemetry systems have overcome many of the inadequacies previously inherent in whiledrilling sonic measurements. New data processing techniques and improvements in telemetry systems have minimized earlier limitations, allowing real-time access to while-drilling sonic compressional measurements in almost any drilling environment. X,00 > Compressional and shear peaks available in real time. Because of improvements in downhole tool and telemetry systems, slowness time coherence peaks can now be sent to the surface for evaluation and labeling while drilling (Track ). Previously, the semblance projection was available only by processing tool memory after the tool was pulled from the borehole (Track 1). The semblance projection based on the real-time peaks (Track ) is consistent with the memory-mode data. Station measurements of compressional t (white circles) acquired during quiet periods, such as when pumps were off during pipe connections, also confirm the accuracy of the real-time data. The sonicvision system has the unique capability to modify label limits (Track ) at surface for better extraction of compressional data, and for the first time, real-time shear data. These improvements in real-time quality control make the compressional input, used for pore-pressure calculation of minimum mud weight, more robust. Combining the real-time compressional and shear data also enables geomechanical calculations of the maximum mud-weight window. The new design also transmits real-time coherent events, called peaks. The sonicvision tool can send up to four peak arrivals uphole at any given time, enabling engineers at the surface to accurately differentiate arrivals rather than relying on downhole processing. These peaks are then assembled to form an STC projection log that helps improve data accuracy and provides a significant step forward in data quality control (above). STC projection logs help engineers accurately differentiate compressional, shear and other modes in real time. The novel design of the sonicvision tool now allows engineers to modify label limits at the surface thereby improving extraction of the compressional t and also providing real-time shear data. Accurate discrimination of arrivals improves pore-pressure measurement and allows geomechanical interpretation based on while-drilling compressional, shear and density data. Acoustic data can now also be further refined by acquiring data while the pumps are off. Background noise of the same frequency as sonic measurements, generated by drilling and circulation, can be problematic for making accurate acoustic measurements. During a drillpipe connection, the sonicvision tool can acquire real-time formation velocity measurements in a quiet environment, increasing confidence in the STC projections and potentially allowing engineers to observe velocity changes caused by flow-induced stress variance. Seismic, Sonic and Pressure Measurement Defining the Mud-Weight Window In many GOM fields, pore pressure changes rapidly with depth, and tight mud-weight windows make drilling and completion difficult, or even impossible. One example of an extremely difficult environment is the Vermillion offshore area. Here, mud weights often reach 18 lbm/galus [,157 kg/m ], the risk of wellbore instability and lost circulation is high, and six or more casing strings are typically required to reach target reservoirs. Today, operators use data retrieved during drilling from sonicvision, StethoScope formationpressure-while drilling service and other LWD tools to help improve well-construction efficiency and reduce cost by accurately defining and managing the effective stress and mud-weight window. Sonic LWD, real-time formation pressure and other while-drilling tools were successfully used to reduce risk and operational uncertainty while drilling a well in Vermillion Block 8 during 005. In this well, which was owned by Helis Oil & Gas LLC and operated by PPI Technology Services, engineers planned and executed an aggressive drilling program. This program extended both the 9 5 -in. intermediate casing and 7-in. liner strings to sufficient depths to eliminate a string of casing common to wells in the area, in this case, a 5-in. casing string. These efforts not only reduced well cost, but more importantly, eliminated the difficulties associated with slimhole drilling and the completion limitations inherent in small production casing. 76 Oilfield Review

10 Depth, 1,000 ft Pressure gradient, lbm/galus Depth, 1,000 ft Pressure gradient, lbm/galus Pressure gradient, lbm/galus > Telemetry to engineering centers. The wellsite engineer collects drilling, mud and sonic LWD data, then transmits this information to the engineering center where a team of experts analyzes and processes the data. Once the results are returned to the wellsite, initial pore-pressure predictions (A) are updated with pore-pressure estimations (B), ultimately reducing the cone of uncertainty (C) and providing more accurate predictions of pore pressure ahead of the bit (D). Depth, 1,000 ft Pressure gradient, lbm/galus A B C D Depth, 1,000 ft Accurate prediction of geologic target depth and pore pressure is essential to the success of aggressive drilling plans. Helis and PPI engineers based their initial well design on mud weights from wells in the area. They next approached Schlumberger to refine these predictions using the GOM D mechanical earth model, to be further refined with while-drilling sonic data. While-drilling data were transmitted by satellite to a remote operations and collaboration center where the wellbore hydrodynamics and geomechanical earth models were updated in real time using data from the rig (above). To account for variations in lithology and sedimentcompaction rates, the nonlinear normal compaction transform established during predrilling planning was validated and recalibrated while drilling using sonicvision data and direct pressure measurements from the FPWD Formation Pressure While Drilling tool. Correlating data acquired from the sonicvision and FPWD tools significantly increased confidence in the real-time porepressure prediction model. These measurements allowed predrilling uncertainties associated with the velocity-to-pore-pressure transform to be properly defined while drilling. The calibrated transform was then applied to revise and update Winter 005/006 77

11 the predrilling pore-pressure model, both behind and ahead of the bit (right). The results, including the mud-weight recommendations, were then conveyed to the rig, and action was taken to ensure that the surface mud weight, the equivalent circulating density (ECD) and the equivalent static density (ESD) were kept within the limits of the mudweight window. The initial requirements for setting the 9 5 -in. casing were constrained by a 1-lbm/galUS [1,558-kg/m ] fracture point derived from previous experiences in the field. However, the calculated fracture gradient derived from whiledrilling formation velocity and density measurements indicated that the rock strength was substantially higher, and capable of accommodating a heavier drilling fluid. The mud weight was increased to 1 lbm/galus based on the real-time porepressure analysis as drilling approached 6,800 ft [,07 m]. Using real-time sonic LWD data, while-drilling pressure measurements and advanced data processing techniques, geoscientists at the remote collaborative center established a safe mud-weight range that allowed the driller to reach a depth of 8,187 ft [,95 m] before running 9 5 -in. casing; at casing depth, the ECD was within 0.1 lbm/galus [11.98 kg/m ] of the calculated fracture gradient. Once the 9 5 -in. casing was set, drilling resumed with an 8 1 -in. bit. At 9,500 ft [,896 m], the annular pressure exceeded the fracture gradient, and circulation was lost. Time-lapse resistivity analysis indicated two zones near the previous casing shoe where the formation had probably been damaged. On further evaluation, engineers believed that the cost of remedial squeeze operations outweighed the risk of drilling ahead with tight hydraulic control and a maximum mud weight of 17.5 lbm/galus [,097 kg/m ]. Carefully monitoring and maintaining the annular pressures within an accurately calibrated hydraulicpressure envelope allowed the operator to complete the well at 1,507 ft [,81 m] in the target reservoir without an additional string of casing. The combined efforts of Schlumberger, PPI and Helis engineers eliminated the preplanned 5-in. casing string and avoided the difficulties associated with slimhole drilling and completion. Sonic LWD, while-drilling pressure measurements and careful hydrodynamic monitoring using the APWD Annular Pressure While Drilling tool succeeded in identifying pore-pressure changes and fracture points, and allowed drilling to proceed within the constraints of a narrow mudweight envelope. Depth, ft,000 5,000 6,000 7,000 8,000 9,000,000 11,000 1,000 Predrilling pore pressure Real-time t (sonic) pore pressure Real-time mud weight Real-time equivalent circulating density Real-time t (sonic) fracture gradient Equivalent static density Formation integrity test Formation pressure while drilling data Casing point Pore pressure, lbm/galus > Drilling in a narrow mud-weight window. The top of the pore-pressure ramp is confirmed at around 6,800 ft by the sonic (red) and formation pressure whiledrilling measurements (green diamonds). Between 7,000 and 8,000 ft [,1 and,8 m], a significant divergence between the predrilling model (green curve) and actual pore pressure represents an example of the importance of using real-time measurements to update the predrilling model. As drilling progressed below 9,000 ft [,7 m], accurate pore-pressure prediction, pressure measurements and hydraulic modeling allowed the drilling team to maintain the mud weight (black curve), equivalent static (blue diamond) and equivalent circulating (purple curve) densities within a narrow window just below the real-time fracture gradient (gold curve). Engineers significantly reduced the uncertainty associated with pressure-prediction models by updating the predrilling velocity-topore-pressure transform using sonic LWD data and measuring true formation pressure. The critical 9 5 -in. casing depth was pushed 1,187 ft [6 m] deeper than planned, eliminating an entire casing section and reducing well cost by more than US$ 1.7 million. A Sound Future for While-Drilling Acoustic Tools A new generation of sonic LWD tools is helping drillers, engineers and geoscientists make many decisions that facilitate safe and cost-effective well construction. By supplying timely information on formation velocity, while-drilling acoustic tools have proved to be a valuable asset to the well-engineering team. Today s sonic LWD systems are providing accurate acoustic data that in turn, are being processed in real time to reliably determine pore pressure and the geophysical limits of formations being drilled. When combined with seismic and other real-time data, this information helps geoscientists see ahead of the bit to the next geologic horizon and beyond. Defining the mudweight window while drilling enables engineers to deviate from predrilling casing designs, pushing casing seats to greater depths and significantly reducing well cost. Much like the development of sonar early in the 0th century, advances in modeling software, acoustic tool design and decisionprocessing utilities are helping engineers see the unseen and make sound drilling decisions, reducing cost and increasing wellconstruction efficiency. DW 78 Oilfield Review