REDUCING FRACTURE PREDICTION UNCERTAINTY BASED ON TIME-LAPSE SEISMIC (4D) AND DETERMINISTIC INVERSION ALGORITHM

2019 ◽  
Vol 9 (2) ◽  
pp. 187-204
Author(s):  
Liming Zhang ◽  
Chenyu Cui ◽  
Kai Zhang ◽  
Yi Wang ◽  
Zhixue Sun ◽  
...  
Keyword(s):  
Time Lapse ◽  
Fracture Prediction ◽  
Inversion Algorithm ◽  
Prediction Uncertainty

scholarly journals Applying compactness constraints to differential traveltime tomography

Geophysics ◽  
2007 ◽  
Vol 72 (4) ◽  
pp. R67-R75 ◽  
Author(s):  
Jonathan B. Ajo-Franklin ◽  
Burke J. Minsley ◽  
Thomas M. Daley
Keyword(s):  
Stable Solution ◽  
Model Space ◽  
Time Lapse ◽  
Process Time ◽  
Spatial Process ◽  
Weighted Norm ◽  
Inversion Algorithm ◽  
Time Data ◽  
Data Set ◽  
Traveltime Tomography

Tomographic imaging problems are typically ill-posed and often require the use of regularization techniques to guarantee a stable solution. Minimization of a weighted norm of model length is one commonly used secondary constraint. Tikhonov methods exploit low-order differential operators to select for solutions that are small, flat, or smooth in one or more dimensions. This class of regularizing functionals may not always be appropriate, particularly in cases where the anomaly being imaged is generated by a nonsmooth spatial process. Time-lapse imaging of flow-induced velocity anomalies is one such case; flow features are often characterized by spatial compactness or connectivity. By performing inversions on differenced arrival time data, the properties of the time-lapse feature can be directly constrained. We develop a differential traveltime tomography algorithm whichselects for compact solutions, i.e., models with a minimum area of support, through application of model-space iteratively reweighted least squares. Our technique is an adaptation of minimum support regularization methods previously explored within the potential theory community. We compare our inversion algorithm to the results obtained by traditional Tikhonov regularization for two simple synthetic models: one including several sharp localized anomalies and a second with smoother features. We use a more complicated synthetic test case based on multiphase flow results to illustrate the efficacy of compactness constraints for contaminant infiltration imaging. We apply the algorithm to a [Formula: see text]-sequestration-monitoring data set acquired at the Frio pilot site. We observe that in cases where the assumption of a localized anomaly is correct, the addition of compactness constraints improves image quality by reducing tomographic artifacts and spatial smearing of target features.

Complex conductivity tomography using low-frequency crosswell electromagnetic data

Geophysics ◽  
2014 ◽  
Vol 79 (1) ◽  
pp. E23-E38 ◽  
Author(s):  
Kris MacLennan ◽  
Marios Karaoulis ◽  
André Revil
Keyword(s):  
Oil Spills ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Time Lapse ◽  
Complex Conductivity ◽  
Inversion Algorithm ◽  
Polarization Tomography ◽  
Exploration And Production ◽  
Integral Equation Approach ◽  
Gradient Based

The complex conductivity of partially saturated siliciclastic sediments can now be reasonably predicted through recently developed petrophysical models like the POLARIS model. However, classical crosswell-induced polarization tomography (using a galvanometric approach) is characterized by a poor sensitivity map far from the wells, and thus other methods should be analyzed for potential improvements. The presence of low-frequency ([Formula: see text]) polarization effects in earth porous materials noticeably increases the amplitude and decreases the phase of measured electromagnetic (EM) fields. As such, the quadrature conductivity (directly associated with the low-frequency polarization effect) yields a significant contribution to the EM fields. We demonstrate that these contributions can be observed in crosswell EM data in terms of signal-to-noise ratio. With a realistic amount of noise, we can recover the distribution of the in-phase and quadrature conductivities for crosswell EM tomography. We use an integral equation approach for the forward modeling and a gradient-based approach with Tikhonov regularization for the inverse problem. We also develop a new inversion algorithm to invert time-lapse frequency domain EM data using an active-time-constrain approach. This information may be used in turn to improve our ability to monitor saturation changes in enhanced oil reservoir production, the remediation of oil spills, and the exploration and production of geothermal fields.

An AVO Inversion Algorithm Base on Time-Lapse Seismic Data

2011 ◽  
Author(s):  
Kai Xie ◽  
WenMao Yu ◽  
HuoQuan Yu ◽  
Peng Wu ◽  
Tao Li ◽  
...  
Keyword(s):  
Seismic Data ◽  
Time Lapse ◽  
Inversion Algorithm ◽  
Avo Inversion ◽  
Algorithm Base

Application of the finite-difference contrast-source inversion algorithm to seismic full-waveform data

Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. WCC47-WCC58 ◽  
Author(s):  
Aria Abubakar ◽  
Wenyi Hu ◽  
Tarek M. Habashy ◽  
Peter M. van den Berg
Keyword(s):  
Finite Difference ◽  
Conjugate Gradient ◽  
Gradient Method ◽  
Time Lapse ◽  
Source Inversion ◽  
Inversion Algorithm ◽  
Nonlinear Conjugate Gradient Method ◽  
Full Waveform ◽  
Contrast Source Inversion ◽  
Nonlinear Conjugate Gradient

We have applied the finite-difference contrast-source inversion (FDCSI) method to seismic full-waveform inversion problems. The FDCSI method is an iterative nonlinear inversion algorithm. However, unlike the nonlinear conjugate gradient method and the Gauss-Newton method, FDCSI does not solve any full forward problem explicitly in each iterative step of the inversion process. This feature makes the method very efficient in solving large-scale computational problems. It is shown that FDCSI, with a significant lower computation cost, can produce inversion results comparable in quality to those produced by the Gauss-Newton method and better than those produced by the nonlinear conjugate gradient method. Another attractive feature of the FDCSI method is that it is capable of employing an inhomogeneous background medium without any extra or special effort. This feature is useful when dealing with time-lapse inversion problems where the objective is to reconstruct changes between the baseline and the monitor model. By using the baseline model as the background medium in crosswell seismic monitoring problems, high quality time-lapse inversion results are obtained.

Dynamic Data Integration and Quantification of Prediction Uncertainty Using Statistical-Moment Equations

SPE Journal ◽  
2011 ◽  
Vol 17 (01) ◽  
pp. 98-111 ◽  
Author(s):  
P.. Likanapaisal ◽  
L.. Li ◽  
H.A.. A. Tchelepi
Keyword(s):  
Data Integration ◽  
History Matching ◽  
Dynamic Properties ◽  
Statistical Moment ◽  
Statistical Moments ◽  
Moment Equations ◽  
Inversion Algorithm ◽  
Reservoir Properties ◽  
Dynamic Data ◽  
Prediction Uncertainty

Summary The use of a probabilistic framework for dynamic data integration (history matching) has become accepted practice. In this framework, one constructs an ensemble of reservoir models, in which each realization honors the available (static and dynamic) information. The variations in the flow performance across the ensemble provide an assessment of the prediction uncertainty due to incomplete knowledge of the reservoir properties (e.g., permeability distribution). Methods based on Monte Carlo simulation (MCS) are widely used because of the generality and simplicity of MCS. As a black-box approach, only pre- and post-processing of conventional flow simulations are needed. To achieve reasonable accuracy in estimating the statistical moments of flow-performance predictions, however, large numbers of realizations are usually necessary. Here, we use a different, and direct, approach for model calibration and uncertainty quantification. Specifically, we describe a statistical-moment-equations (SMEs) framework for both the forward and inverse problems associated with immiscible two-phase flow. In the SME method, the equations governing the statistical moments of the quantities of interest (e.g., pressure and saturation) are derived and solved directly. We assume that statistical information and a few measurements are available for the permeability field. As for the dynamic properties, we assume that measurements of pressure, saturation, and flow rate are available at a few locations and at several times. For the forward problem, the flow (pressure and total-velocity) SMEs are solved on a regular grid, while a streamline-based strategy is used to solve the transport SMEs. We use a kriging-based inversion algorithm, in which the first two statistical moments of permeability are conditioned directly using the available dynamic data. We analyze the behaviors of the saturation moments and their evolution as they are conditioned on measurements, in both space and time. Moreover, we discuss the relationship between the widely used MCS-based Kalman-filter approach and our SME inversion scheme.

High-frequency localized elastic full waveform inversion for time-lapse seismic surveys

Geophysics ◽  
2021 ◽  
pp. 1-55
Author(s):  
Shihao Yuan ◽  
Nobuaki Fuji ◽  
Satish C. Singh
Keyword(s):  
High Frequency ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Time Lapse ◽  
Target Area ◽  
Full Waveform Inversion ◽  
Inversion Algorithm ◽  
Elastic Parameters ◽  
Model Inversion ◽  
Full Waveform

Seismic full waveform inversion is a powerful method to estimate the elastic properties of the subsurface. To mitigate the non-linearity and cycle-skipping problems, in a hierarchical manner, one inverts first low-frequency contents to determine long- and medium-wavelength structures and then increases the frequency contents to obtain detailed information. However, the inversion of higher frequencies can be computationally very expensive, especially when the target of interest, such as oil/gas reservoirs and axial melt lens, is at a great depth, far away from source and receiver arrays. To address this problem, we present a localized full waveform inversion algorithm where iterative modeling is performed locally, allowing us to extend inversions for higher frequencies with little computation effort. Our method is particularly useful for time-lapse seismic, where the changes in elastic parameters are local due to fluid extraction and injection in the subsurface. In our method, both sources and receivers are extrapolated to a region close to the target area, allowing forward modeling and inversion to be performed locally after low-frequency full-model inversion for the background model, which by nature only represents long- to medium-wavelength features. Numerical tests show that the inversion of low-frequency data for the overburden is sufficient to provide an accurate high-frequency estimation of elastic parameters of the target region.

Ultrastructure of melanocyte-keratinocyte interactions and pigment transfer in vitro

1978 ◽  
Vol 36 (2) ◽  
pp. 650-651
Author(s):  
Raul I. Garcia ◽  
Evelyn A. Flynn ◽  
George Szabo
Keyword(s):  
Direct Injection ◽  
Skin Pigmentation ◽  
Freeze Fracture ◽  
Pigment Granule ◽  
Time Lapse ◽  
Ultrastructural Level ◽  
Lanthanum Tracer ◽  
A Cell

Skin pigmentation in mammals involves the interaction of epidermal melanocytes and keratinocytes in the structural and functional unit known as the Epidermal Melanin Unit. Melanocytes(M) synthesize melanin within specialized membrane-bound organelles, the melanosome or pigment granule. These are subsequently transferred by way of M dendrites to keratinocytes(K) by a mechanism still to be clearly defined. Three different, though not necessarily mutually exclusive, mechanisms of melanosome transfer have been proposed: cytophagocytosis by K of M dendrite tips containing melanosomes, direct injection of melanosomes into the K cytoplasm through a cell-to-cell pore or communicating channel formed by localized fusion of M and K cell membranes, release of melanosomes into the extracellular space(ECS) by exocytosis followed by K uptake using conventional phagocytosis. Variability in methods of transfer has been noted both in vivo and in vitro and there is evidence in support of each transfer mechanism. We Have previously studied M-K interactions in vitro using time-lapse cinemicrography and in vivo at the ultrastructural level using lanthanum tracer and freeze-fracture.

High-voltage Electron Microscopy of astroglial cell whole mounts

1986 ◽  
Vol 44 ◽  
pp. 316-317
Author(s):  
J.N. Turner ◽  
W.G. Shain ◽  
V. Madelian ◽  
R.A. Grassucci ◽  
D.L. Forman
Keyword(s):  
Electron Microscopy ◽  
High Voltage ◽  
Time Lapse ◽  
Astroglial Cells ◽  
High Voltage Electron Microscopy ◽  
Rat Glioma ◽  
Voltage Electron ◽  
High Voltage Electron ◽  
Nervous System Function ◽  
Beta Adrenergic Agonist

Homogeneous cultures of astroglial cells have proved useful for studying biochemical, pharmacological, and toxicological responses of astrocytes to effectors of central nervous system function. LRM 55 astroglial cells, which were derived from a rat glioma and maintained in continuous culture, exhibit a number of astrocyte properties (1-3). Stimulation of LRM 55s and astrocytes in primary cell cultures with the beta-adrenergic agonist isoproterenol results in rapid changes of morphology. Studies with time lapse video light microscopy (VLM) and high-voltage electron microscopy (HVEM) have been correlated to changes in intracellular levels of c-AMP. This report emphasizes the HVEM results.

Measurement of spontaneous neuronal membrane activity by time lapse confocal microscopy

1995 ◽  
Vol 53 ◽  
pp. 972-973
Author(s):  
R H. Selinfreund ◽  
A. H. Cornell-Bell
Keyword(s):  
Membrane Potential ◽  
Confocal Microscopy ◽  
Patch Clamp ◽  
Electrical Activity ◽  
Time Lapse ◽  
Neuronal Firing ◽  
Neuronal Membrane ◽  
Pituitary Cells ◽  
Patch Clamp Recording ◽  
Spontaneous Electrical Activity

Cellular electrophysiological properties are normally monitored by standard patch clamp techniques . The combination of membrane potential dyes with time-lapse laser confocal microscopy provides a more direct, least destructive rapid method for monitoring changes in neuronal electrical activity. Using membrane potential dyes we found that spontaneous action potential firing can be detected using time-lapse confocal microscopy. Initially, patch clamp recording techniques were used to verify spontaneous electrical activity in GH4\C1 pituitary cells. It was found that serum depleted cells had reduced spontaneous electrical activity. Brief exposure to the serum derived growth factor, IGF-1, reconstituted electrical activity. We have examined the possibility of developing a rapid fluorescent assay to measure neuronal activity using membrane potential dyes. This neuronal regeneration assay has been adapted to run on a confocal microscope. Quantitative fluorescence is then used to measure a compounds ability to regenerate neuronal firing.The membrane potential dye di-8-ANEPPS was selected for these experiments. Di-8- ANEPPS is internalized slowly, has a high signal to noise ratio (40:1), has a linear fluorescent response to change in voltage.

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