Pseudo-probabilistic identification of fracture network in seismic clouds driven by source parameters

2020 ◽  
Vol 223 (3) ◽  
pp. 2066-2084
Author(s):  
Rike Koepke ◽  
Emmanuel Gaucher ◽  
Thomas Kohl
Keyword(s):  
Source Parameters ◽  
Synthetic Data ◽  
Fracture Network ◽  
Gas Production ◽  
Minimum Size ◽  
Seismic Events ◽  
Data Sets ◽  
Weighting Functions ◽  
Hydraulic Stimulation ◽  
Rupture Plane

SUMMARY Fracture networks in underground reservoirs are important pathways for fluid flow and can therefore be a deciding factor in the development of such reservoirs for geothermal energy, oil and gas production or underground storage. Yet, they are difficult to characterize since they usually cannot be directly accessed. We propose a new method to compute the likelihood of having a fracture at a given location from induced seismic events and their source parameters. The result takes the form of a so-called pseudo-probabilistic fracture network (PPFN). In addition to the hypocentres of the seismic events used to image the fracture network, their magnitudes and focal mechanisms are also taken into account, thus keeping a closer link with the geophysical properties of the rupture and therefore the geology of the reservoir. The basic principle of the PPFN is to estimate the connectivity between any spatial position in the cloud and the seismic events. This is done by applying weighting functions depending on the distance between a seismic event and any location, the minimum size of the rupture plane derived from the event magnitude, and the orientation of the rupture plane provided by the focal mechanism. The PPFN is first tested on a set of synthetic data sets to validate the approach. Then, it is applied to the seismic cloud induced by the deep hydraulic stimulation of the well GPK2 of the enhanced geothermal site of Soultz-sous-Forêts (France). The application on the synthetic data sets shows that the PPFN is able to reproduce fault planes placed in a cloud of randomly distributed events but is sensitive to the free parameters that define the shape of the weighting functions. When these parameters are chosen in accordance with the scale of investigation, that is, the typical size of the structures of interest, the PPFN is able to determine the position, size and orientation of the structure quite precisely. The application of the PPFN to the GPK2 seismic cloud reveals a large prominent fault in the deep-northern part of the seismic cloud, supporting conclusions from previous work, and a minor structure in the southern upper part, which could also be a branch of the main fault.

Analysis of the seismic response to reservoir development and long-term operation at the Rittershoffen deep geothermal site

2020 ◽  
Author(s):  
Rike Köpke ◽  
Olivier Lengliné ◽  
Jean Schmittbuhl ◽  
Emmanuel Gaucher ◽  
Thomas Kohl
Keyword(s):  
Fluid Flow ◽  
Seismic Response ◽  
Template Matching ◽  
Fracture Network ◽  
Seismic Events ◽  
Valuable Insight ◽  
Hydraulic Stimulation ◽  
Reservoir Development ◽  
Seismic Networks ◽  
Insight Into

<p>In a geothermal reservoir, seismicity may be induced due to changes in the subsurface as a result of drilling, stimulation or circulation operations. The induced seismic events are therefore strongly linked to the fluid flow, the mechanical state of the reservoir and the geological structures that impact the stress field and make this fluid flow possible. Here, the study is based on the monitoring of the development and operation of the deep geothermal site at Rittershoffen (Alsace, France) using different seismic networks covering various operational periods from September 2012 to present, including the drilling of the well doublet GRT1/GRT2, stimulation of GRT1 and well testing. The seismicity induced by these operations has the potential to give valuable insight into the geomechanical behaviour of the reservoir and the geometry of the fracture network. The present study gives an overview of the spatial and temporal development of the induced seismicity and the magnitudes of the events to provide insights into active structures in the reservoir.</p><p> </p><p>To improve the level of detection, we first apply a template matching algorithm to the continuous waveforms recorded by the seismic networks. After running the detection with the template matching, the relative locations of all detected events are calculated as well as relative magnitudes. This workflow is applied to the whole time period from the start of the drilling in 2012 up to 2017. The spatial and temporal evolution of the events and their magnitudes shows how the different operations during reservoir development influence the seismogenic development of the reservoir and the seismic activity during continuous operation of the site. Further analysis like b-value computation, estimation of the best-fitting planes to the seismic clouds and evaluation of the waveform correlation between the seismic events give insight into the processes that induced the seismicity and the relation between different seismic intervals.</p><p> </p><p>Focus of the present study is on the similarities and differences in the seismic response of the reservoir to the three subsequent stimulations of GRT1, called thermal, chemical and hydraulic stimulation. Results show that the seismicity induced during the hydraulic stimulation is much stronger in terms of seismicity rate and magnitudes than seismicity induced during thermal stimulation and migrates further into the reservoir. Noticeably, after a seismically quiet period of four days after the hydraulic stimulation a short burst of seismicity occurred unrelated to any operations on site. Seismicity during this delayed interval proved to have quite distinct characteristics from the seismicity induced during injection. While no significant seismicity was induced during chemical stimulation, the operation may have had an important influence on the seismic response of the reservoir during hydraulic stimulation by changing the state of the present fracture network.</p>

Crossline wavefield reconstruction from multicomponent streamer data: Part 2 — Joint interpolation and 3D up/down separation by generalized matching pursuit

Geophysics ◽  
2010 ◽  
Vol 75 (6) ◽  
pp. WB69-WB85 ◽  
Author(s):  
Ali Özbek ◽  
Massimiliano Vassallo ◽  
Kemal Özdemir ◽  
Dirk-Jan van Manen ◽  
Kurt Eggenberger
Keyword(s):  
Particle Motion ◽  
Matching Pursuit ◽  
Synthetic Data ◽  
Basis Functions ◽  
Seismic Events ◽  
Data Sets ◽  
Optimal Basis ◽  
A New Technique ◽  
Simultaneous Interpolation ◽  
Streamer Data

Computation of the 3D upgoing/downgoing separated wavefield at any desired position within a marine streamer spread is enabled by multicomponent streamers that can measure the crossline and vertical components of water-particle motion in addition to the pressure. We introduce the concept of simultaneous interpolation and deghosting and describe a new technique, generalized matching pursuit (GMP), to achieve this. This method is based on the matching-pursuit technique and iteratively reconstructs the signal as a combination of optimal basis functions. In the GMP method, the basis functions describing the unknown 3D upgoing wavefield are filtered by appropriate forward ghost operators before being matched to the multicomponent measurements. As a data-dependent method, GMP can operate on data samples that are highly aliased in the crossline direction without relying on assumptions about seismic events such as linearity. The technique is naturally suitable for data with only a small number of samples that may be irregularly spaced. We demonstrate the efficacy and robustness of the GMP method on several synthetic data sets of increasing complexity and in the presence of noise.

scholarly journals Methods for estimating uncertainty in factor analytic solutions

2014 ◽  
Vol 7 (3) ◽  
pp. 781-797 ◽  
Author(s):  
P. Paatero ◽  
S. Eberly ◽  
S. G. Brown ◽  
G. A. Norris
Keyword(s):  
Environmental Protection Agency ◽  
Synthetic Data ◽  
Analytic Solutions ◽  
Data Sets ◽  
Random Errors ◽  
Data Set ◽  
Factor Analytic ◽  
Uncertainty Estimates ◽  
Multilinear Engine ◽  
Analytic Models

Abstract. The EPA PMF (Environmental Protection Agency positive matrix factorization) version 5.0 and the underlying multilinear engine-executable ME-2 contain three methods for estimating uncertainty in factor analytic models: classical bootstrap (BS), displacement of factor elements (DISP), and bootstrap enhanced by displacement of factor elements (BS-DISP). The goal of these methods is to capture the uncertainty of PMF analyses due to random errors and rotational ambiguity. It is shown that the three methods complement each other: depending on characteristics of the data set, one method may provide better results than the other two. Results are presented using synthetic data sets, including interpretation of diagnostics, and recommendations are given for parameters to report when documenting uncertainty estimates from EPA PMF or ME-2 applications.

Reverse time migration

Geophysics ◽  
1983 ◽  
Vol 48 (11) ◽  
pp. 1514-1524 ◽  
Author(s):  
Edip Baysal ◽  
Dan D. Kosloff ◽  
John W. C. Sherwood
Keyword(s):  
Wave Amplitude ◽  
Synthetic Data ◽  
Data Sets ◽  
Field Observations ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Time Migration ◽  
Migration Method ◽  
Zero Offset ◽  
Time Extrapolation

Migration of stacked or zero‐offset sections is based on deriving the wave amplitude in space from wave field observations at the surface. Conventionally this calculation has been carried out through a depth extrapolation. We examine the alternative of carrying out the migration through a reverse time extrapolation. This approach may offer improvements over existing migration methods, especially in cases of steeply dipping structures with strong velocity contrasts. This migration method is tested using appropriate synthetic data sets.

Surface wave attenuation of seismic records with the co-core trace transform filter

Geophysics ◽  
2011 ◽  
Vol 76 (6) ◽  
pp. V115-V128 ◽  
Author(s):  
Ning Wu ◽  
Yue Li ◽  
Baojun Yang
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Field Data ◽  
Wave Attenuation ◽  
Seismic Events ◽  
Data Sets ◽  
Transform Domain ◽  
Recent Developments ◽  
Seismic Records ◽  
Trace Transform

To remove surface waves from seismic records while preserving other seismic events of interest, we introduced a transform and a filter based on recent developments in image processing. The transform can be seen as a weighted Radon transform, in particular along linear trajectories. The weights in the transform are data dependent and designed to introduce large amplitude differences between surface waves and other events such that surface waves could be separated by a simple amplitude threshold. This is a key property of the filter and distinguishes this approach from others, such as conventional ones that use information on moveout ranges to apply a mask in the transform domain. Initial experiments with synthetic records and field data have demonstrated that, with the appropriate parameters, the proposed trace transform filter performs better both in terms of surface wave attenuation and reflected signal preservation than the conventional methods. Further experiments on larger data sets are needed to fully assess the method.

Quasi-2D inversion of DCR and TDEM data for shallow investigations

Geophysics ◽  
2011 ◽  
Vol 76 (4) ◽  
pp. F239-F250 ◽  
Author(s):  
Fernando A. Monteiro Santos ◽  
Hesham M. El-Kaliouby
Keyword(s):  
Joint Inversion ◽  
Synthetic Data ◽  
Data Sets ◽  
Complex Environments ◽  
Inversion Algorithm ◽  
2D Inversion ◽  
New Approach ◽  
Earth Models ◽  
Time Domain Electromagnetic ◽  
Inversion Techniques

Joint or sequential inversion of direct current resistivity (DCR) and time-domain electromagnetic (TDEM) data commonly are performed for individual soundings assuming layered earth models. DCR and TDEM have different and complementary sensitivity to resistive and conductive structures, making them suitable methods for the application of joint inversion techniques. This potential joint inversion of DCR and TDEM methods has been used by several authors to reduce the ambiguities of the models calculated from each method separately. A new approach for joint inversion of these data sets, based on a laterally constrained algorithm, was found. The method was developed for the interpretation of soundings collected along a line over a 1D or 2D geology. The inversion algorithm was tested on two synthetic data sets, as well as on field data from Saudi Arabia. The results show that the algorithm is efficient and stable in producing quasi-2D models from DCR and TDEM data acquired in relatively complex environments.

scholarly journals Bootstrap inversion technique for atmospheric trace gas source detection and quantification using long open-path laser measurements

2018 ◽  
Vol 11 (3) ◽  
pp. 1565-1582 ◽  
Author(s):  
Caroline B. Alden ◽  
Subhomoy Ghosh ◽  
Sean Coburn ◽  
Colm Sweeney ◽  
Anna Karion ◽  
...  
Keyword(s):  
Natural Gas ◽  
Statistical Method ◽  
Frequency Comb ◽  
Synthetic Data ◽  
The United States ◽  
Source Location ◽  
Gas Production ◽  
Field Observations ◽  
Extraction Technology ◽  
Open Path

Abstract. Advances in natural gas extraction technology have led to increased activity in the production and transport sectors in the United States and, as a consequence, an increased need for reliable monitoring of methane leaks to the atmosphere. We present a statistical methodology in combination with an observing system for the detection and attribution of fugitive emissions of methane from distributed potential source location landscapes such as natural gas production sites. We measure long (> 500 m), integrated open-path concentrations of atmospheric methane using a dual frequency comb spectrometer and combine measurements with an atmospheric transport model to infer leak locations and strengths using a novel statistical method, the non-zero minimum bootstrap (NZMB). The new statistical method allows us to determine whether the empirical distribution of possible source strengths for a given location excludes zero. Using this information, we identify leaking source locations (i.e., natural gas wells) through rejection of the null hypothesis that the source is not leaking. The method is tested with a series of synthetic data inversions with varying measurement density and varying levels of model–data mismatch. It is also tested with field observations of (1) a non-leaking source location and (2) a source location where a controlled emission of 3.1  ×  10−5 kg s−1 of methane gas is released over a period of several hours. This series of synthetic data tests and outdoor field observations using a controlled methane release demonstrates the viability of the approach for the detection and sizing of very small leaks of methane across large distances (4+ km2 in synthetic tests). The field tests demonstrate the ability to attribute small atmospheric enhancements of 17 ppb to the emitting source location against a background of combined atmospheric (e.g., background methane variability) and measurement uncertainty of 5 ppb (1σ), when measurements are averaged over 2 min. The results of the synthetic and field data testing show that the new observing system and statistical approach greatly decreases the incidence of false alarms (that is, wrongly identifying a well site to be leaking) compared with the same tests that do not use the NZMB approach and therefore offers increased leak detection and sizing capabilities.

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