Tuesday, May 28, 2019

Modeling Logs for Horizontal Well Planning and Evaluation

Horizontal wells can increase production rates and ultimate recovery, and can reduce the number of platforms or wells required to develop a reservoir. They can also help avoid water or gas breakthrough, bypass environmentally sensitive areas and reduce stimulation costs.

As exploration and development budgets tighten, companies are becoming more efficient by drilling fewer, well-placed holes. Reentry and multilateral wells are growing in number, along with short-radius wells. There are greater expectations and smaller margins for error in driling today's horizontal wells. 

Drilling horizontal wells presents formidable challenges. Planning trajectories, choosing fluids, steering, formation evaluation and completion- each stage is a huge task. Several stages-planning,steering and formation evaluation- benefit from combining the efforts of geologist, log analyst and directional drillers. 

A powerful partner in all these stages is forward modeling, or log simulation. Other industries are using simulation to help train pilots , model aircraft and automobile reliability and response, design buildings, test weapons, record music, predict weather- the list is endless. In the oil field, modeling helps make efficient use of logs in horizontal wells in two ways- first by predicting logging-while-drilling (LWD) tool response to guide directional drilling, and second by constraining formation evaluation when the conventional assumptions of a vertical well no longer hold. 

Directional drilling practice and technology have evolved to the point where , given a good plan, the target can be hit with high accuracy. The drill bit can be placed within a target the volume of an engineer's office at a depth and lateral offset of a few miles. Trajectories are becoming more complex as directional drillers push the technology to its limits in "designer" wells. To improve the odds of these wells hitting the target, they are carefully planned in two steps: definition of the target from maps and logs, then design of a wellbore trajectory to hit it. 

No plan, unfortunately, is foolproof. Uncertainties in the position of the target , combined with unpreditictability of structural and stratigraphic variations, even in developed fields, can cause directional drillers to lose their way. The chance of going astray declines significantly, however, with the use of real-time formation evaluation logs and comparison of the logs with modeled cases to gauge the position of the tool within the sequence of beds. The INFORM Integrated Forward Modeling program provides an interface for building a formation model and simulating log response, allowing drillers to anticipate what's ahead. We look first at modeling for horizontal well planning, then explore how the INFORM system facilitates postdrilling visualization of LWD and wireline logs in horizontal wells.  


Model First, Then Drill

Often the objective of drilling a horizontal well is to penetrate the reservoir but stay close to a caprock shale or gas-oil contact- to drill parallel to a boundary or a contrast in material properties- for thousands of feet. Such a viewing angle is unusal for electromagnetic tools, the tools most commonly used for steering. Other measurements, such as gamma ray and density, are also affected by the horizontal geometry, giving an asymmetric response as they lie against the floor of the borehole. 

Because most resistivity tools probe several feet into the formation, they are affected by resistivity inhomogeneities in the vicinity of the well and even ahead of the drill bit. This early warning feature is beneficial to directional drillers, who harness it to steer wells into target layers or away from problem zones before they are encountered by the bit. This "proximity effect" can be accurately modeled during predrilling planning to provide a road map for drilling.

In a planning example from the North Sea, Jim White of Schlumberger Wireline & Testing in Aberdeen, Scotland, used log modeling to demonstrate the feasibility of landing the well in a thin sand and avoiding high-resistivity , calcite-cemented , tight streaks. Forward modeling computed the response of the CDR Compensated Dual Resistivity tool with its two depths of investigation- shallow from the phase shift measurement and deep from the attenuation log. When the wellbore came to within 3 ft of the calcite zone, the modeled attenuation and phase shift curves crossed, because the deeper-reading attenuation measurement senses the high-resistivity calcite. 

The CDR logs acquired when the well was drilled corroborated the modeled predictions. Based on the simulations, the signature of the lower boundary- the deep reading crossing over the shallow was recognized while drilling, and the well was steered away. Had the well entered the cemented zone, drillers estimated they would have spent several days trying to get back on target. 

Geologist from Chevron Niugini are using INFORM forward modeling to plan and geosteer horizontal wells in the Iagifu Hedinia field, within the Southern Highlands Province of Papua New Guinea. Located in Papuan Fold and Thrust belt, this field is part of a double anticline complex in the Hedinia thrust sheet. The major oil reservoir is the Lower Cretaceous Toro sandstone. Within the Toro, the hydrocarbon accumulation consists of an oil band up to 218 meters [ 715 ft] thick overlain by a gas cap. Gas cap expansion and gravity drainage are the major drive mechanisms for the field, with support from the Toro aquifer making a minor contribution.

Development well planning and drilling are complicated by the complex fold geometry. Unfortunately, the rugged karst topography created in the Darai Limestone at surface prohibits the acquisition of usable seismic data. For predicting the subsurface reservoir geometry, geologist rely on surface geological mapping, side-scan radar imagery, dipmeter data and correlation logs from adjacent wells.

In order to maximize productivity and ultimate recovery from the horizontal wells, wells are programmed to be horizontal in the Toro oil reservoir at a level of 15 m [50 ft] above the oil-water-contact. This enables the wells to produce oil at lower solution gas/oil ratios (GOR) and should delay breakthrough from the advancing gas front. 

During drilling to the Toro objective, the landing phase is critical to the success of the horizontal well program. With an unstable Alene shale section overlying the Toro, it is important to minimize the amount of horizontal section drilled before encountering the top Toro. Conversely, encountering the Toro during the build section of the well course, before reaching horizontal, can result in loss of productive interval since this hole section may be too close to the current gas-oil contact and would not be perforated. The Alene is drilled with mud weights in the range of 12 to 14 ppg, while the current reservoir pressure in the Toro are in the 4.5 to 5.5 ppg equivalent range. To prevent loss circulation problems and possible loss of the hole, it is necessary to identifiy the top of the Toro casing point before penetrating more than 1.5 to 3 m [ 5 to 10 ft] of the sandstone. 













An accurate predictive model of the Toro anticlinal geometry resulting from recognition of overlying stratigraphic markers while drilling -as well as the ability to determine the structural attitude of these layers - increases the probability for a successful landing phase. With INFORM processing, a model of stratigraphic interval above the target can be built using well logs and dipmeter data from nearby wells along with geological structure models developed for the planned horizontal well. LWD responses for the potential range of structural dips within a particular area of the anticlinal fold can be simulated. 

As the well course builds to horizontal, the geosteering specialist and geologist correlate major stratigraphic LWD markers and estimate the structural dip of a stratigraphic unit in the plane of the well course by optimizing the match between the LWD curves and the model log curves. The calculated structural dip estimates are compared to those in the geologist's predicted fold geometry cross-sectional model. The new dips are then used to correct the subsurface structure model and revise the top target coordinates.

During the planning for the first well, IHT-1, gamma ray and resistivity logs from three nearby wells were used to create a model for computing CDR responses for the full range of possible structural dip magnitudes along potential well trajectories. The responses were stored in a relative angle data base. The programmed well course was oblique to the strike of the Toro in this area of the Iagifu anticline, and was designed to be horizontal 15 m above the oil-water contact. This entry point is depth-constrained by the predicted oil-water contact level, and laterally constrained by the projected position of the Toro entry point, determined by projecting the Toro structural dip away from well control points higher on the anticlinal flank. The kick-off depth and deviation angle build rate depend on knowing this entry position. (picture)











During the drilling of well IHT-1, a computer structure model with sections of 6 degree and 8 degree apparent dip was constructed with the INFORM system, using data transmitted via satellite link. The stratigraphic horizon boundaries, dip magnitude and true vertical depth of each section was determined from the match between the measured CDR logs and the modeled logs. This match is consistent down to the Toro, indicating the structural dip model is a good representation of the actual Toro subsurface structure. 


Typically the CDR tool, producing characteristic horns at high-angle bed boundaries, is run to land wells. FOr the IHT-1 well bottomhole assembly configurations, however, this tool is located 18 m [60 ft] behind the bit. To precisely locate the 9 5/8 -inch casing setting depth at the top Toro, the last bit trip is run with the Geosteering tool, an instrumented steerable downhole motor with two resistivity sensors.

 The primary purpose of the Geosteering tool is to drill the horizontal drainhole and confirm that the well is above the oil-water contact in each sand. Normally Geosteering tool data are not acquired in the upper 6 to 9 m [20 to 30 ft] of the Toro, until the tool signal receiver clears casing. Because of mechanical problems, the 9 5/8 in. casing in IHT-1 ended 27 m [90 ft] above the Toro. This allowed the Geosteering tool to acquire data across the shale-sandstone resitivity contrast at the top of the Toro.

Unexpectedly, IHT-1 entered the dipping Toro reservoir beneath a present-day oil-water contact at 8741 ft true vertical depth (TVD). The contact was apparently 15 to 18 m [50 to 60 ft] shallower than predicted, probably due to pressure depletion of the upper Toro reservoir in this area of the field. The bit resistivity gave an immediate indication of water-saturated Toro. The planned trajectory was modified to build angle to greater than 90 degrees in an upward trajectory, crossing the oil-water contact from underneath. During drilling in the mid-Toro, the well encountered lost fluid circulation problems, possibly at a fault or fracture zone. With sudden unloading of the borehole, collapse occured in the unstable shale openhole section above the Toro, and the hole was lost.

IHT-1A, a sidetrack designed to take a parallel well path, was planned using the structural attiiude data and oil-water contact information from IHT-1. A short 30.5 -m [100 ft] , 8 1/2 inch pilot hole was drilled at the end of the buildup section with the Geosteering tool to "geostop" exactly on the shale-sandstone reservoir boundary. This hole was enlarged, and the 9 5/8 inch casing set just on the reservoir top. As expected, dips were close to those in IHT-1, and the well was landed within the Toro oil leg as planned, 15 m above the present day oil-water contact. It continued for 427 m [1400 ft] across the three main Toro reservoir sandstone members. The well was completed as an oil well, producing more than 10,000 stock tank barrels of oil per day, at solution GOR. 

Another well, IHT-2, on the same structure, encountered 55 degree dips, much steeper than the 22 degree anticipated. These were successfully modeled and the well path modified to hit the target.

After drilling, Model Again

Once drilled and logged, horizontal wells continue to pose challenges in visualization and formation evaluation. Log simulation can help verify a formation model or the location of  a well in space, to use for future development planning and quality control. More importantly, modeling helps untagle true formation properties such as formation fluid resistivity, Rt , and water saturation, Sw from the melange of shallow and deep responses of while-drilling and wireline tools.




In the Gulf of  Mexico, Lee Lehtonen at Mobil Exploration and Producing in New Orleans Lousiana, USA tested simulation to validate the model of a horizontal well designed to tap multiple compartments in a faulted reservoir. The horizontal well was to traverse four fault blocks.












Pay in the first and fourth blocks would be isolated by enough shale to allow setting external packers. In this case, INFORM modeling showed how LDW porosity logs could be used to distinguish a change in formation properties associated with faulting from changes encountered in a new stratigraphic layer. 

The ADN Azimuthal Density Neutron tool measures-while drilling- bulk density, ultrasonic standoff, photoelectric factor and neutron porosity. Magnetometers continously measure tool orientation , and results are distributed into readings above, below and to each side of the borehole. This allows discrimination of the orientation of planes of porosity and density discontinuity in the formation. 

In the Mobil well, CDR and ADN data were recorded into memory while drilling, and data were brought uphole with each bit change. These logs were compared with logs simulated using a formation model built from the known structure and pilot well logs. During the fifth bit run, the density tool encountered a shale-sand contact. Examination of the density porosity logs shows that the average and bottom quadrant curves both detect the interface at the same measured depth, XX340 ft. Comparing the acquired and simulated logs shows the contact can be modeled as a fault separating shale from sand. 

















Sunday, May 12, 2019

AVO in VSPs

When a wavefront hits a boundary at vertical incidence, the amount of compressional energy reflected and transmitted is dependent only on the contrast of acoustic impedance- density times compressional velocity- of the rocks at that boundary. But when the incident angle is not 0 degree, the amount of compressional energy reflected of tranmitted depends on the angle of incidence, or source offset, and contrast in densities and shear and compressional velocities. In such cases, the reflection AVo can be measured and analyzed to yield information about lithology and pore fluid through their effects on density and compressional and shear velocities. 

Carrying out a walkaway VSP with the receivers straddling such a boundary allows direct measurement of the variation in amplitude with offset that arises from lithology and fluid properties above and below the reflector. The results can be analyzed for fluid and lithology identification in a wide zone around the well. Formation properties inferred from VSPs can be integrated with those interpreted from well logs and measured directly from cores. In this way the VSP can also provide independent calibration of the same amplitude variation seen across a surface seismic reflection point gather- a gather is thee collection of traces that reflect at the same point, but at different angles, or offsets.

Calibrating the surface seismic AVO data with the VSP AVO response brings added value by:


  • establishing viability of using AVO to map a reservoir.
  • reducing the risk involved with the added cost of AVO studies
  • improving the reliability of AVO interpretations
  • quantitatively assessing the effects of processing on the AVO response.


To establish whether AVO is applicable as an interpretation tool for a particular reservoir, the expected AVO response is usually modeled. This requires knowledge of the model parameters, including shear velocity. Dipole shear sonic logging tools are used to measure shear velocities even where this velocity is slower than the borehole fluid velocity.









However, use of density and velocity log data to model anticipated AVO anomalies has not always succeeded in fully explaining the AVO response observed on surface seismic gathers. The reasons for this are many and include reflectivity mismatches between surface seismic and log data, wave propagation effects through fine layers, tuning effects (constructive and destructive interference at seismic wavelengths), geometric effects, processing-related issues and intrinsic anisotropy.

Borehole seismic data can quantify these effects. VSPs provide an independent measure of the seismic AVO response and the ability to include necessary effects in the forward modeling to satifactorily explain the origins of the surface seismic AVO response. Anisotropy is one such effect - one that can both mimic and mask AVO responses, giving false hope for or concealing the presence of hydrocarbons. 

Informaiton about anisotropic velocities for forward modeling often comes from measurements made on cores. But being scale-dependent, anisotropy may be different at the seismic wavelength scale. Therefore, it is better to measure  the elastic anisotropy at the seismic scale. 

In 1994, at Schlumberger Cambridge Research in Cambridge, England, Doug Miller proposed a method to do this using the arrival times from a walkaway survey to provide a measure of compressional velocity anisotropy in a shale, and from this to characterize the elastic properties of that shale, governing compressional and vertically polarized shear waves.

Shale consists of finely- layered clay platelets and exhibits an anisotropy called transverse isotropy (TI). The acoustic properties vary depending on whether waves propagate with particle motions parallel or perpendicular to the platelet layers- often thought of as horizontally or vertically because the clays usually lie flat.

Miller proposed that the vertical slowness - the inverse of velocity - of a shale may be measured across an array of geophones for each shot point offset along a walkaway profile. And the horizontal slowness can be measured at a single receiver location for adjacent shots in the same profile, providing the subsurface layers are essentially flat. A crossplot of these measurements for each shot position defines the compressional anisotropic response of the shale. A curve fitted to these data points provides a solution to the equations that deliver shear anisotropy through a complete description of the elastic properties of the shale.

These research efforts have been put to practical use in the BP-operated Forties field in the UK sector of the North Sea. The ultimate aim is to enable AVO attributes to be mapped with confidence from 3D surface seismic data. To achieve this,  a detailed evaluation of shear velocity anisotropy in the formations overlying the Forties sand has been undertaken to build a velocity model. The data used included acoustic measurements from preserved shale and sand cores, a full suite of logs- including standard density and DSI Dipole Shear Sonic Imager Logs- in addition to walkaway, rig source and vertical-incidence VSP data.

Initially, two models were generated, one assuming the shale overlying the reservoir sand was isotropic and another in which TI anisotropy was introduced. Differences in amplitude response between the two models were immediately observed, particulary at far offsets for the interface between the shale and the reservoir sand at 1.07 normal incidence time. 

The predicted response assuming an anisotropic shale was validated by the amplitude measured in the calibration walkaway. This implies that the effect of the anisotropic velocity in the shale must be taken into account before attributing the AVO response in the surface seismic data to effects of fluid in the reservoir. 

It is clear from this study that the combination of AVO measurement from VSP and log-based, anisotropic forward modeling provides a powerful methodology for calibrating AVO responses observed on surface seismic data near wells in low dip structures. Where AVO analysis is used as the basis for hydrocarbon indication in fields with existing wells, the method helps identify the origin of observed AVO effects, determining whether large-scale AVO analysis and reprocessing effort are worthwhile in terms of achieving the desired objectives. 

The greater understanding of observed AVO effects should minimize the risk of missing genuine hydrocarbon-related AVO anomalies or of misinterpreting anomalies caused by other factors, such as anisotropy.