Anisotropy parameters provide vital information for surface and borehole seismic data processing, imaging and interpretation. The objective of this research is to introduce a reliable technique, for estimating local seismic anisotropy using both P- and SV-wave from VSP data in VTI media where the overburden is heterogeneous.
The technique uses P- and SV-wave vertical slowness components and polarization angles in VTI media to estimate Thomsen parameter δ and anellipticity parameter ƞ. The proposed method is applied to a synthetic VSP data with anisotropic properties. The estimated δ and ƞ parameters, using both P- and SV-wave data, show better correlation with anisotropy parameters in the model compared to the technique that only uses P- wave data.
Time-lapse, multicomponent seismic data were acquired during the start-up of the CO2 flood at Delhi Field, Louisiana. The purpose of the integrated study at Delhi was to identify zones of high residual oil saturation and to monitor flow paths in the reservoir. Contacting bypassed oil is critical for economic enhanced oil recovery (EOR).
The inversion of seismic data for elastic and shear impedance and density volumes is a technique that offers several advantages. It facilitates integrated interpretation, improves the vertical resolution allowing sub-seismic features to be seen, and it optimizes the correlation between seismic and petrophysical properties of the reservoir. Mapping the porosity is extremely important in the development of a hydrocarbon reservoir. Combining seismic attributes derived from the P-P and P-S data and porosity logs we use linear multi-regression and neural networks geostatiscal tools to predict porosity between the seismic attributes and porosity logs at the well locations. After predicting porosity in well locations, those relationships were applied to the seismic attributes to generate a 3-D porosity volume of a deep water Campos basin reservoir.
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Quantitative integration of time-lapse seismic and flow simulation in a CO2 enhanced oil recovery (EOR) process is an effective tool for performing dynamic reservoir characterization. The non-uniqueness of the history match process is largely reduced by quantitatively incorporating 4D seismic responses along with production data. Many papers in the literature had discussed the application of 4D seismic assisted reservoir simulation in either water flood or EOR reservoirs. However, very few of these publications have touched a stratigraphically complex reservoir with continuous CO2 injection strategy such as Delhi Field in Northeastern Louisiana. In this research, we proposed a time-lapse seismic assisted reservoir simulation workflow to improve history match of CO2 flood stage and reservoir modeling in in Delhi Field. The objective of this work also includes investigating the feasibility of incorporating time-lapse seismic data into history matching a very thin reservoir with unavailable historical water flood scheme. 4D seismic data was utilized in both qualitative and quantitative manner to assist reservoir model updating. A Petro-Elastic Model (PEM) was constructed to connect simulation outputs with seismic attributes. In this process, dynamic simulation results (pressure, saturation and CO2 density) along with elastic moduli were assembled into synthetic seismic attributed. The quantitative comparison of seismic inversion attributes and synthetic seismic attributes is an effective tool to evaluate previous history match process and guide the subsequent model updating.
This paper shows three level of history match process. The first level is preliminary model with poor production rate and pressure match. After that, a careful history match was performed by qualitatively incorporating time-lapse seismic interpretations. As a result, the production is greatly improved. The final stage of is to quantitatively compare synthetic and observed seismic attributes and use the objective function to further optimize the simulation model. The results of level two and three demonstrate that time-lapse seismic plays a significant role in Delhi Field reservoir simulation.
The contribution of this research consists of the following aspects. First, an updated and predictable model is important for the subsequent reservoir engineering work in Reservoir Characterization Project (RCP) at Colorado School of Mines (CSM). Secondly, this work provides an effective integration procedure of interdisciplinary dynamic reservoir characterization process for complex reservoirs. Thirdly, the optimized simulation results validate the effect of 4D seismic integration in continuous CO2 injection EOR process.
Battalora, Linda Ann (Colorado School of Mines) | Curtis, John Blair (Colorado School of Mines) | Davis, Thomas L. (Colorado School of Mines) | Miller, Mark Gerard (Colorado School of Mines) | Smith, Bruce W. (BP plc) | Sonnenberg, Stephen (Colorado School of Mines)
An educational model exists at the Colorado School of Mines (CSM) that responds to current industry objectives, incorporates the SPE Professional Competency Matrices1 (hereinafter, Competency Matrices) and satisfies the Accreditation Board of Engineering and Technology (ABET)2 requirements.
GEGN/GPGN/PEGN439 Multidisciplinary Petroleum Design (hereinafter, 439 Capstone Course) is the cross-discipline, senior-level, capstone design course in the Geological Engineering, Geophysical Engineering and Petroleum Engineering Departments. Historically, the 439 Capstone Course has met ABET requirements and industry objectives by providing students with multidisciplinary problem solving and integrated team experience prior to entering the work force.
Teamwork experiences focused on the integration of data, information, and people from the disciplines of geology, geophysics, and petroleum engineering.
However, the need exists to move beyond "integration" with a step forward to "implementation." Using the Competency Matrices as a guideline and responding to industry feedback, the revised 439 Capstone Course is a novel educational approach that accomplishes this goal.
The 439 Capstone Course is an applied problem-solving course. The curriculum comprises an initial instruction phase lasting approximately two weeks where students are introduced to the theory of multidisciplinary teamwork, task performance strategy, facilitation/meeting management, group decision-making, conflict resolution, brainstorming, and peer evaluations are discussed. During this phase students learn how to apply various performance strategies to open-ended problems. These problems do not have unique solutions and require the integration of information from multiple sources to solve. The Faculty from the Petroleum, Geological and Geophysical Engineering Departments look for integration of information across each the three disciplines. The instruction phase is followed by the project planning and execution phase. Faculty members assume the role of industry management.
Self-learning and combined team learning are required throughout the course. The Faculty does not have a set of lectures because this is not a lecture course. Some introductory lectures are given at the onset of the project assignment and additional lectures are scheduled as needed depending on the specifics of the project assignment.
In the past, teams of 4 or 5 members have proven to be ideal considering the amount of work expected from each team to complete the project. However, due to large enrollment the students presently work in teams of 7 or 8. The ideal team includes at least one geologist and one geophysicist. Students are randomly assigned to teams given these constraints.
Peer evaluations are performed mid-project and at the end of the project. Peer feedback is anonymous. Codes are used in lieu of individual names. Thus, both the source of the evaluation and a given individual's average peer rating are kept anonymous.
There are numerous opportunities to make oral presentations during the course. Presenters are generally selected at random, however, all team members must be prepared to present. Additionally, a formal, technical report is required for mid-project and final project. Representatives from industry are invited to attend and critique the group presentations along with Management. Mid-project and Final project reviews are made at the team level with Management.
In management of mature oil fields for enhanced oil recovery, 4D seismic imaging plays a very important role. Previously, we published the qualitative results of integrating flow simulation with time-lapse multi-component seismic data for a CO2 EOR project in the thin valley-fill Morrow formation at Postle Field. In this paper, we will present our quantitative approach and results from integrating flow simulation with time-lapse seismic.
Three seismic surveys have been acquired at Postle Field to monitor the ongoing CO2 flood. Since presentation of the previous paper, additional seismic and production data has become available which has influenced both the history match of the reservoir flow model and seismic interpretation. Gassmann's fluid substitution method was used to relate the flow simulation results with time-lapse seismic attributes. In addition, a sensitivity analysis was performed using a conceptual model to investigate the effect of various reservoir dynamic parameters on seismic response.
Flow simulation and rock physics modeling show that production and injection in the reservoir causes saturation and pressure changes, which affect acoustic and elastic properties of the reservoir. Acoustic impedance calculated from the simulation model was compared to the corresponding results from seismic data. The magnitude of changes of acoustic impedance calculated from the flow simulation is similar in range to that from seismic inversion. The effect of fluid saturation change in the reservoir, particularly CO2 saturation, is greater than the effect of pressure change. Conceptual modeling indicates that the sensitivity of seismic attributes to changes in CO2 saturation and water saturation is weak and may be difficult to detect seismically. On the other hand, to have a relatively big change in acoustic impedance, a big change in pressure is needed.
Our research results demonstrate that for a credible dynamic reservoir characterization, an integration of flow simulation and 4D seismic is required which, in turn, could be a viable method to guide field operations. However, this process is challenging in thin reservoirs undergoing CO2 WAG injection.
The thickness of the producing sand layer in Postle field is below tuning thickness. In reflection seismology, tuning happens when the ratio of seismic wavelength to bed thickness is equal to or greater than four. When tuning happens, the amplitude of the overlying layer shows a linear relationship with the thickness of the underlying layer (in this case, reservoir layer). This relationship is used in studying thin reservoirs. However, to perform more sophisticated characterization of a thin reservoir such as time lapse, that linear relationship is not enough and it is required to measure reservoir characteristics directly. To see the reservoir layer, it is necessary to increase frequency content of seismic data while keeping the noise level low at high frequencies. The current methods of frequency enhancement in the industry cannot provide enough increase in the frequency content to make the reservoir layer visible. In this study, I have created a workflow to increase the frequency content of seismic data without introducing noise. The bandwidth extension procedure begins with a zero-phase spiking deconvolution. This procedure increases the frequency content, but it tends to decrease signal to noise ratio at high frequencies. To make sure that no incoherent noise is extrapolated, the original dataset is split into seven frequency subsets using band pass filter. A mild smoothing filter on each subset prepares them for extrapolation and removes incoherent noise. Then sparse-spike deconvolution is applied on each subset separately. When the subsets are stacked back, extrapolated noise is suppressed if any exist. Sparse-spike deconvolution can see very subtle changes in the waveform that are related to thin layers. Furthermore, frequency splitting method helps sparse-spike deconvolution detect spikes more effectively. Lastly, zero-phase spiking deconvolution increases the power of those subtle spikes and makes them visible in the seismic image. The workflow is linear, so the result is reversible. That is, if the high-frequency data are filtered back to the original bandwidth, the result is the same as the original product. The final product of my workflow has a flat spectrum while showing greater spatial and temporal resolution than the original data.