Going quantitative with 4D seismic analysis

MacBeth, Colin; Soldo, Juan; Floricich, Mariano

doi:10.1190/1.1843311

Cited by 14 publications

(21 citation statements)

References 4 publications

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“…Timelapse geophysical measurements have been shown to be successful in monitoring and understanding physical processes in the subsurface, e.g. ͑Ramirez et al, 1993͑Ramirez et al, , 1995Lumley, 2001;Tsourlos et al, 2003;Singha and Gorelick, 2005;Lane et al, 2006;MacBeth et al, 2006;Anno and Routh, 2007͒. In a general sense, time-lapse methodologies can be utilized to determine the rate at which a process is occurring, define the volume of subsurface region affected by a particular process, and understand the complex interactions between various subsurface processes. Time-lapse is especially important for near-surface studies since the medium is much more dynamic due to the proximity of the air-earth interface.…”

Section: Introductionmentioning

confidence: 99%

Application of time-lapse ERT imaging to watershed characterization

et al. 2008

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Time-lapse electrical resistivity tomography ͑ERT͒ has many practical applications to the study of subsurface properties and processes. When inverting time-lapse ERT data, it is useful to proceed beyond straightforward inversion of data differences and take advantage of the time-lapse nature of the data. We assess various approaches for inverting and interpreting time-lapse ERT data and determine that two approaches work well. The first approach is model subtraction after separate inversion of the data from two time periods, and the second approach is to use the inverted model from a base data set as the reference model or prior information for subsequent time periods. We prefer this second approach. Data inversion methodology should be considered when designing data acquisition; i.e., to utilize the second approach, it is important to collect one or more data sets for which the bulk of the subsurface is in a background or relatively unperturbed state. A third and commonly used approach to time-lapse inversion, inverting the difference between two data sets, localizes the regions of the model in which change has occurred; however, varying noise levels between the two data sets can be problematic. To further assess the various time-lapse inversion approaches, we acquired field data from a catchment within the Dry Creek Experimental Watershed near Boise, Idaho, U.S.A. We combined the complimentary information from individual static ERT inversions, time-lapse ERT images, and available hydrologic data in a robust interpretation scheme to aid in quantifying seasonal variations in subsurface moisture content.

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Section: Introductionmentioning

confidence: 99%

Application of time-lapse ERT imaging to watershed characterization

et al. 2008

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“…Unfortunately, examples of pressure‐dominated 4D seismic are scarce at present, and for most fields there is the necessity to separate saturation and pressure changes before pursuing the permeability calculation. Various techniques have been published in an attempt to tackle this separation, such as the rock‐physics‐based approaches of Tura and Lumley (1999), Landrø (2001) and Ribeiro and MacBeth (2004), and the production‐calibrated procedure of MacBeth et al . (2006a).…”

Section: Discussionmentioning

confidence: 99%

“…Evaluation of a could be seen as a potential drawback of this approach and, in practice, this factor should be viewed as a free parameter to be determined by a calibration exercise (see section below on the application to the field data). If direct rock‐physics calculation is not possible, another possibility is the use of a technique similar to that of MacBeth, Floricich and Soldo (2006a). The lighter and hence the more compressive the oil, the more important it is to include this factor.…”

Section: Application To Model‐controlled Datamentioning

confidence: 99%

Extraction of permeability from time‐lapse seismic data

MacBeth¹,

Almaskeri²

2006

Geophysical Prospecting

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A B S T R A C TTwo formulae are developed for estimating horizontal permeability directly from maps of 4D seismic signatures. The choice of the formula used depends on whether the seismic is dominated by changes of pressure or saturation. However, pressure derived from time-lapse seismic, or seismic amplitudes controlled predominantly by pressure are to be preferred for optimal 'illumination' of the reservoir. The permeability is predicted to be dependent on porosity but weighted by a 4D term related to the magnitude and spatial gradient of the 4D signature. Tests performed on model-based synthetic seismic data affirm the validity and accuracy of this approach. Application to field data from the UK continental shelf reveals a large-scale permeability variation similar to the existing simulation model, but with additional fine-scale detail. The technique thus has the potential of providing extra information with which to update the simulation model. The resultant permeability estimates have been successfully ground-truthed against the results of two well tests. As non-repeatable noise in the time-lapse seismic data diminishes with improved 4D-related acquisition, it will become increasingly possible to make robust permeability estimates using this approach. I N T R O D U C T I O NIt is now widely acknowledged that time-lapse seismic data, if interpreted appropriately with due consideration of reservoir production and injection history, can provide invaluable information with which to optimize hydrocarbon recovery. This information includes, for example, the location of hydraulically conductive faults, no flow barriers or high permeability pathways, the identification of isolated compartments possibly containing bypassed oil, the position of injected fluid fronts or contacts, and general field-wide pressure and saturation changes. To date, most of these features are commonly inferred by detecting regions of brightening or dimming on difference sections or maps, and are thus essentially semiquantitative and can provide ambiguous interpretations. This style of 4D analysis is useful for reservoir management purposes, but in general may not offer sufficient accuracy to update the flow simulation model and hence to reduce uncertainty in reservoir performance predictions. A more detailed and in-depth level * E-mail: Colin.MacBeth@pet.hw.ac.uk of quantitative analysis is required, one that delivers accurate numerical estimates of absolute permeability variations, transmissibility factors, and reservoir connectivity at a variety of scales. To address this general challenge, we start by focusing here on estimating one of these parameters, i.e. reservoir permeability, which is the key flow property that controls strategies for well completion and production.The usual starting point for determining the permeability field for the flow simulation model is the core plug or welllog data. The interwell space is then populated by extrapolating between wells using an appropriate set of geostatistics, and this final reservoir model i...

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“…Since the fluid pressure pulse travels faster than the CO 2 plume across the storage reservoir, leakage of brine through possible "weak" areas of the caprock into overlying permeable formations should be identifiable sooner than CO 2 leakage by measuring even small and localized fluid pressure variations in these formations. Fluid pressure changes can be detected, for example, by pressure-monitoring wells [5] or four-dimensional (4D) time-lapse seismic data [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Detection of potential leakage pathways from geological carbon storage by fluid pressure data assimilation

González‐Nicolás

Baù

Alzraiee

2015

Advances in Water Resources

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One of the main concerns of geological carbon storage (GCS) systems is the risk of leakage through "weak" permeable areas of the sealing formation or caprock. Since the fluid pressure pulse travels faster than the carbon dioxide (CO 2) plume across the storage reservoir, the fluid overpressure transmitted into overlying permeable formations through caprock discontinuities is potentially detectable sooner than actual CO 2 leakage occurs. In this work, an inverse modeling method based on fluid pressure measurements collected in strata above the target CO 2 storage formation is proposed, which aims at identifying the presence, the location, and the extent of possible leakage pathways through the caprock. We combine a three-dimensional subsurface multiphase flow model with ensemble-based data assimilation algorithms to recognize potential caprock discontinuities that could undermine the long-term

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Going quantitative with 4D seismic analysis

Cited by 14 publications

References 4 publications

Application of time-lapse ERT imaging to watershed characterization

Application of time-lapse ERT imaging to watershed characterization

Extraction of permeability from time‐lapse seismic data

Detection of potential leakage pathways from geological carbon storage by fluid pressure data assimilation

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