In 2014-2015 a large Ocean Bottom Node (OBN) seismic survey was acquired over the Atlantis Field. This survey provides a time lapse (4D) view of the changes in the reservoirs. The main goals of this dataset were to monitor changes around the water injectors, to observe aquifer influx and to study compartmentalization. The movement of the water in the reservoirs was clearly observed and indicated by a hardening response above the Original Oil Water Contact (OOWC). Besides the movement of the water, these observations also provided a good indication of the OOWC location. These and other observations were used to update the reservoir model and thereby improve the predictions based on this model, including the expected outcome for future wells. The survey covered the imaging challenged subsalt area of the Atlantis Field and shows hints of time lapse response below the salt. The value of the information more than justified the cost of the survey, and as a result a new time lapse seismic data acquisition is being considered.
Presentation Date: Wednesday, September 27, 2017
Start Time: 3:55 PM
Presentation Type: ORAL
van Gestel, Jean-Paul (BP)
This presentation describes observations of 3D and 4D noise levels for deepwater reservoirs that are both subsalt and extra salt. First, noise levels and seismic data quality are defined. Then, a strong correlation between 3D and 4D noise levels is shown for two deepwater Gulf of Mexico fields. These same observations have been confirmed at other subsalt fields. The correlation can be used to indicate 4D signals in noisy areas since they stand out from the background trend. The correlation can also be used as a predictor of 4D noise levels for 4D feasibility studies for subsalt fields. Instead of assuming a constant background 4D noise level, this method produces a map of spatially varying 4D noise levels that is a better indication of those 4D noise levels. The map makes it possible to differentiate simple salt structures from more complex ones, and it indicates potential 4D data quality issues in any field with static imaging issues. Another implication from this work is that 4D would be possible on any field that is subsalt as long as the 3D static imaging problem can be solved.
Time lapse (or 4D) seismic allows for visualization along sections, on maps or within volumes of changes in the reservoir resulting from production related changes in pressure and saturation (Johnston, 2013). 4D seismic has been successfully applied in many fields. However, in the Gulf of Mexico (GoM) and in several other regions in the world, the time lapse technique is very challenging subsalt (Stopin et al., 2011, van Gestel et al., 2013). In this situation, the 4D repeatability becomes much worse and it is difficult to separate signal from noise. A positive exception was shown by Hatchell et al. (2013), who observed a 4D signal from a reservoir subsalt. A large portion of the future GoM production is subsalt, and most of these fields would benefit from good quality 4D seismic data. The observations presented here may help to resolve the subsalt 4D problem by better describing the actual problem that is at hand.
The first part is to define noise levels or data quality levels as they are each other’s inverse. There are several methods to extract 3D noise levels from seismic data quality. The goal of the 3D noise map is not only to show where the noise level is high within a field, but to be able to compare one processing flow to another and ideally present a quantitative measure that can be compared from one field in one region to any other field in any other region. In this study several 3D noise level measurements are compared: Signal to Noise Ratio (SNR), coherency, and average amplitude extractions.
This study shows the results from finite difference modeling for optimizing the acquisition design of the Atlantis 2014-2015 Ocean Bottom Nodes (OBN) survey. During the planning of this Atlantis time lapse acquisition, it was realized that additional nodes would be available, which provided an opportunity to use those nodes to improve the 3D static seismic image. A modeling study was initiated with the objective to identify optimum placement of the additional nodes. The model was generated using realistic detailed stratigraphy modeling and several cases were studied by adding node patches in different directions. Observations show that the addition of the nodes to the South, has the largest impact on the imaging of Atlantis Field. To measure the imaging impact of each added node location a more detailed tool was generated; the node areal contribution map, which shows how much each individual node contributes to the image of the reservoir. Improved imaging was also shown by modeling of reduced node spacing and increased node density. Altogether, the insights from this modeling work enabled optimized acquisition design for the survey that was acquired on the Atlantis Field in 2014-2015.
The Atlantis Field sits about 300 km south of the Louisiana coast in the Gulf of Mexico in around 7000 feet of water (Figure 1). It began production in October 2007 from Middle Miocene turbidite reservoirs that lie about 17,000 feet below sea level. As the field is sitting under the Sigsbee escarpment and the edge of a very complicated salt body with multiple salt fingers, seismic imaging has been challenging (Roberts et al., 2011). Only the southern end that sits outside of the salt can be imaged with confidence.
The primary objective of the 2005-2006 OBN survey was to obtain a consistent, high-quality image of the subsalt portion of the reservoir. This survey was the world’s first large-scale deepwater survey to employ autonomous nodes (Beaudoin and Ross, 2007). OBN technology also allows for operationally highly repeatable time-lapse seismic and overcomes the challenges presented by surface and subsea installations. Therefore, in 2009 a monitor survey was acquired (Reasnor et al., 2010). This time lapse data had excellent geometric repeatability and low 4D noise levels. The survey showed the depletion signature of the field in the time shift and the amplitude response (van Gestel et al., 2013).
Elebiju, Bunmi (BP America) | Ariston, Pierre-Olivier (BP America) | van Gestel, Jean-Paul (BP America) | Murphy, Rachel (BP America) | Chakraborty, Samarjit (BP America) | Jansen, Kjetil (BP America) | Rodenberger, Douglas (Shell America) | White, Roy C. (Shell America) | Chen, Yongping (CGG) | Hren, David (CGG) | Hu, Lingli (CGG) | Huang, Yan (CGG)
Using the Kepler and Ariel Fields as a case study, this paper discusses the processing challenges and solutions applied to a 4D co-processing of Wide Azimuth Towed Streamer (WATS) on Narrow Azimuth Towed Streamer (NATS) data. Unlike a dedicated 4D acquisition, WATS on NATS 4D has relatively low repeatability in terms of acquisition geometry and bandwidth differences. All these factors can negatively impact the extraction of a meaningful 4D signal. In this paper, we demonstrate how processing techniques can help to increase repeatability and enhance 4D signal. We focus on the following 4D processing procedures: 4D co-binning, data matching, and post-migration co-denoise. Due largely to these techniques, the final co-processed volumes show an optimized 4D seismic signal with a median Normalized Root Mean Square (NRMS, which measures the repeatability between base and monitor. Details refer to Kragh and Christie, 2002) of 0.10 along the water bottom and 0.28 above the reservoir.
Chakraborty, Samarjit (BP America Inc.) | Brusova, Olga (BP America Inc.) | Davis, Stan (BP America Inc.) | van Gestel, Jean-Paul (BP America Inc.) | Ai, Anita (BP America Inc.) | Walker, Chris (BP America Inc.) | Rollins, Fran (BP America Inc.)
In this case study we present the results from a time-lapse (4D) feasibility study that includes analysis of core data and reservoir simulator to seismic modeling to predict time-lapse seismic response from dynamic reservoir model from the Mad Dog field.
Ultrasonic velocities (UV’s) for both P and S waves were obtained from nine axially oriented sandstone core plug samples. These experiments were conducted under uniaxial strain conditions, in which radial strain was kept constant. The samples were cleaned, dried and then subjected to multiple loading and unloading cycles designed to simulate reservoir stress conditions of pressure depletion and build-up due to production and water injection. Travel times were obtained by careful picking of first arrival events on P and S full waveforms. These picks were used to compute P and S velocities, which were then used together with density data to compute dynamic bulk and shear moduli. These core data were then used to characterize the sensitivity of the dry rock frame to changes in effective stress. Sensitivity of porosity to changes in effective stress was also characterized.
Dry frame moduli were obtained from sonic log measurements using Gassmann fluid substitution for comparison with core data. Computed dry frame moduli from logs show close agreement with the core measurements. This comparison provides more confidence in the laboratory core measurements with less likelihood of core damage. Moreover, we could estimate the effective stress coefficient by matching the dry frame bulk moduli from cores to logs.
Next the core dry frame parameters were used to model rock properties changes in the reservoir for a single interface. Finally, full-field time-lapse feasibility study with the 3D reservoir simulation model was done to model the expected time-lapse response of the Mad Dog field. Results from the feasibility study show that the model-based time-lapse signal could be observed in extra-salt reservoirs using a time-lapse noise threshold derived from time-lapse ocean bottom nodes data from analog fields.
The core analysis and time-lapse feasibility studies demonstrate the need to integrate field-based core measurements to predict time-lapse signal in deepwater reservoirs under complex overburden.
Atlantis Field is a large field in the Gulf of Mexico that has significant imaging challenges due to a complicated overlying salt body. In 2005-2006 the world’s first deepwater Ocean Bottom Nodes (OBN) survey was acquired over this field to improve imaging and to serve as a base line for future time lapse (4D) surveys. In 2009, which was two years after production started, the world’s first OBN repeat survey was acquired. The results from this time lapse survey are presented in this abstract. Due to excellent repeatability of both sources and receivers, extremely low 4D noise has been achieved with an average Normalized Root Mean Square (NRMS) value as low as 5.3% after post stack processing. Unfortunately due to the imaging challenges the area with good data quality is limited. The most valuable time lapse observations are the time shift response in the part of the reservoir that has undergone the strongest pressure depletion. This time shift response can be related to reservoir compaction and confirms other observations seen in production data. The amplitude difference response occurs in a similar area as the time shift response, but is weaker than and opposite to predictions. Sensitivity to pressure response remains the main uncertainty as the observations in the amplitude data do not match observations from laboratory measurements on core data.
Choice of processing strategy for 4D seismic projects with a large number of surveys and excellent repeatability will differ compared to what is traditionally done for timelapse projects with only a few vintages of data recorded with changing acquisition parameters. Here we present some of the issues which will influence processing strategy based on the experience from the Life of Field Seismic project at the Valhall field in the North Sea.
Several decimation tests were run on the Valhall Life of Field Seismic (LoFS) survey 1 (November 2003) and survey 2 (March 2004) to determine which decimations may be acceptable while still maintaining a good 4D signal quality. Three different analysis methods were studied: NRMS analysis, 4D resolution and cross-correlation. An automated process to measure 4D resolution was developed using statistical comparisons of 4D attributes. This 4D resolution method combines both 4D signal and background noise and provides a better measure of 4D signal quality than the NRMS method that only looks at background noise. Results from this study indicate that reducing the receiver sampling or reducing the shot effort, both have a large impact on the 4D resolution of the 4D signal. For a particular decimation factor, shot decimated datasets have better 4D quality signal than cable or node decimation datasets. This should be understood in the context that the survey design is already biased towards shots (shot/receiver ratio 20:1) and so a larger 4D signal quality degradation is expected by increasing the receiver distance further. Furthermore, node decimated datasets produce a better 4D quality signal than cable decimated datasets with the same decimation factor. These observations were corroborated by the cross-correlation method on the amplitude difference maps.
The Valhall Life of Field Seismic (LoFS) project has collected seven time-lapse surveys with very high repeatability. Standard workflows have been established to generate and analyze the resulting 4D images. These workflows have been automated to facilitate a fast and reproducible process that provides standardized products and necessary documentation. A shell script-based workflow was created to replace the existing workflow that was labor-intensive, slow, and error-prone. The final products, extracted attribute maps and 3D volumes, are uploaded to the relevant interpretations system, while key 4D graphic files are generated for each individual wells and linked to an indexed HTML format to allow easy screening of the results. The automated workflow provides a much more reliable and user-friendly procedure, and allows the geophysicist to focus on the interpretation rather than the mechanical data manipulations. This automated workflow was fully-implemented for LoFS survey six and generated time-lapse maps within six hours after delivery of the processed volumes. Combined with the rapid-turnaround processing workflow, the complete suite of time-lapse images were available three weeks after the last shot of the survey was acquired.