Four-dimensional and four-component seismic

This paper outlines the value of 4D for reducing uncertainty in the range of history-matched models and improving the production forecast. This paper describes interpretation results of a 4D seismic-monitoring program in a challenging Middle East carbonate reservoir. Integrated surveillance is critical for understanding reservoir dynamics and improving field management. A key component of the surveillance is areal monitoring of subsurface changes by use of time-lapse geophysical surveys such as 4D seismic. In this paper, the authors propose a new method for time-lapse-seismic surveys focused on water-injector wells.

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We present three field examples of applying a distributed compressive sensing technique, Joint Sparsity Recovery (JSR), to time-lapse (4D) seismic. These results demonstrate that JSR provides an effective way to extract reliable 4D signals from multiple time-lapse seismic volumes and to derive AVA 4D effects out of angle stacks, with simultaneous suppression of the non-production background noise.

JSR applies sparsity-promoting joint inversion on multiple datasets. It not only quantifies the common and unique parts between all input datasets, but also removes the data misfit as unwanted noise at the same time. JSR can improve the 4D interpretability with both quantitative or qualitative 4D inputs such as time-lapse seismic volumes and 4D inversion products. Applying JSR to 4D datasets effectively decreases the uncertainty of reservoir pressure and fluid saturation change estimations for iterative simulation model validation and infill well optimization.

Presentation Date: Wednesday, October 17, 2018

Start Time: 1:50:00 PM

Location: Poster Station 17

Presentation Type: Poster

Standard history matching workflows use qualitative 4D seismic observations to assist in reservoir modeling and simulation. However, such workflows lack a robust framework for quantitatively integrating 4D seismic interpretations. 4D or time-lapse seismic interpretations provide valuable inter-well saturation and pressure information and quantitatively integrating this inter-well data can help to constrain simulation parameters and improve the reliability of production modeling. This paper outlines technologies aimed at leveraging the value of 4D for reducing uncertainty in the range of history matched models and improving the production forecast.

The proposed 4D Assisted History Match (4DAHM) workflows utilize interpretations of 4D seismic anomalies for improving the reservoir simulation models. Design of Experiments (DOE) is initially used to generate the probabilistic history match simulations by varying the range of uncertain parameters. Saturation maps are extracted from the Production History Matched (PHM) simulations and then compared with 4D predicted swept anomalies. An automated extraction method was created and is used to reconcile spatial sampling differences between 4D data and simulation output. Interpreted 4D data is compared with simulation output, and the mismatch generated is used as a 4D filter to refine the suite of reservoir simulation models. The selected models are used to identify reservoir simulation parameters that are sensitive for generating a good match.

The application of 4DAHM workflows has resulted in reduced uncertainty in volumetric predictions of oil fields, probabilistic saturation S-curves at target locations, and fundamental changes to the dynamic model needed to improve the match to production data. Results from adopting this workflow in two different deep-water reservoirs are discussed. They not only resulted in reduced uncertainty, but also provided information on key performance indicators that are critical in obtaining a robust history match. In the first case study presented, the deep-water oil field 4DAHM resulted in a reduction of uncertainty by 20% in OOIP and by 25% in EUR in the P90-P10 range estimates. In the second case study, 4DAHM workflow exploited discrepancies between 4D seismic and simulation data to identify features necessary to be included in the dynamic model. Connectivity was increased through newly interpreted inter-channel erosional contacts, and sub-seismic faults. Moreover, the workflow provided an improved drilling location which has the higher probability of tapping unswept oil and better EUR. The 4D filters constrained the suite of reservoir simulation models and helped to identify 4 out of 24 simulation parameters critical for success. The updated PHM models honor both the production data and 4D interpretations, resulting in reduced uncertainty across the S-curve and, in this case, an increased P50 OOIP of 24% for a proposed infill drilling location, plus a significant cycle-time savings.

This paper presents construction and validation of a reservoir model for the Niobrara and Codell Formations in Wattenberg Field of the Denver-Julesburg Basin. Characterization of Niobrara-Codell system is challenging because of the geologic complexity resulting from the presence of numerous faults. Because of extensive reservoir stimulation via multi-stage hydraulic fracturing, a dual-porosity model was adopted to represent the various reservoir complexities using data from geology, geophysics, petrophysics, well completion and production. After successful history matching two-and-half years of reservoir performance, the localized presence of high intensity macrofractures and resulting evolution of gas saturation was correlated with the time-lapse seismic and microseismic interpretations. The agreement between the evolved free gas saturation in the fracture system and the seismic anomalies and microseismic events pointed to the viability of the dual-porosity modeling as a tool for forecasting and future reservoir development, such as re-stimulation, infill drilling, and enhanced oil recovery strategies.

Anomalous time shift observations from 4D seismic data shot in an HPHT field in the North Sea are being investigated. We are using these time shift signatures to understand the dynamic geomechanical behaviors of two major shales units (Shale Ι and Shale ΙΙ) between the main producing sands.

To capture the geomechanical and pressure diffusion behavior in these shale units, we have performed a coupled fluid flow and geomechanical simulation. Next, we use a 4D-Close-the-Loop workflow to integrate reservoir simulation results, the rock physics model, and seismic signature into a comprehensive and iterative process to update the simulation model. In this process, geomechanical modeling and the conversion of model results to synthetic 4D seismic time shifts allow for a quantitative comparison of synthetic response with the observed 4D seismic anomaly.

The application of this hands-on approach has prompted the calibration of the fluid flow and the geomechanical properties of different reservoir units. Consequently, a better match between the modeled 4D seismic time shifts and those observed from the field data has been achieved. Furthermore, this calibration provides a model that more reliably predicts the pore pressure and stress tensor changes, allowing more confidence in selecting safe well paths. The calibrated geomechanical model suggests that Shale Ι, which is a silty marine shale, undergoes pressure diffusion, and therefore, the trapping mechanism of Shale Ι is highly uncertain. The clay-rich Shale ΙΙ, however, acts as an effective pressure barrier, and hence it is overpressured relative to the surrounding formations and could be a high-risk formation for future drilling programs.

In this case study, the application of the 4D-close-the-loop workflow allows the calibration of the geomechanical model, and hence a close examination of stress distribution at the level of Shale Ι and Shale ΙΙ. These findings have provided additional information that could identify potential geohazards and prevent the risk of well deformation and failure.

An ensemble-based 4D-seismic history-matching case is presented in the complete paper.

Integrated surveillance is critical for understanding reservoir dynamics and improving field management. A key component of the surveillance is areal monitoring of subsurface changes by use of time-lapse geophysical surveys such as 4D seismic. The complete paper reviews the advances in these technologies with recent examples from the Gulf of Mexico (GOM) and deepwater Brazil. Data-Quality Improvement 4D seismic has played a pivotal role in monitoring offshore fields for some time. However, until recently, its application in the GOM had been limited, largely because the effects of the Loop Current and infrastructures make it difficult to repeat the feathering of streamers used in conventional 4D-seismic acquisition.