A fast Monte Carlo sampler for NMR T2 inversion

The inversion of noisy NMR T2 echo data into a T2 spectrum is widely recognized as an inherently non-unique process [1]. One approach to quantifying this uncertainty is to use Monte Carlo sampling. Uncorrelated measurement noise combine with the non-negativity constraint on T2 spectral values to yield spectra following a non-negative normal distribution. There are two published samplers for truncated normal distributions [2], of which nonnegative normal samples are a subset, but we show that these converge too slowly to be practical for the T2 spectral inversion problem. This is because they are based on Gibbs’ samplers that update the spectral estimate just one T2 component at a time. When all of the spectral elements are fixed but one, that one has little room for change without violating the noise constraints on the data. Thus each spectral sample can only be slightly different from the preceding sample, indicating a high degree of statistical correlation and slow convergence. Our solution is to simultaneously update two neighboring spectral components at a time, allowing changes due to one spectral component to be offset by changes in its neighbor. Central to this improvement is a fast 2D slice sampler for non-negative normal distributions. This improves convergence by more than two orders of magnitude. Such speedup allows routine Monte Carlo inversion of 1D NMR spectra, and opens the door for the inversion of 2D NMR spectra

Joint location of microseismic events in the presence of velocity uncertainty

The locations of seismic events are used to infer reservoir properties and to guide future production activity, as well as to determine and understand the stress field. Thus, locating seismic events with uncertainty quantification remains an important problem. Using Bayesian analysis, a joint probability density function of all event locations was constructed from prior information about picking errors in kinematic data and explicitly quantified velocity model uncertainty. Simultaneous location of all seismic events captured the absolute event locations and the relative locations of some events with respect to others, along with their associated uncertainties. We found that the influence of an uncertain velocity model on location uncertainty under many realistic scenarios can be significantly reduced by jointly locating events. Many quantities of interest that are estimated from multiple event locations, such as fault sizes and fracture spacing or orientation, can be better estimated in practice using the proposed approach

A unified Bayesian framework for relative microseismic location

We study the problem of determining an unknown microseismic event location relative to previously located events using a single monitoring array in a monitoring well. We show that using the available information about the previously located events for locating new events is advantageous compared to locating each event independently. By analysing confidence regions, we compare the performance of two previously proposed location methods, double-difference and interferometry, for varying signal-to-noise ratio and uncertainty in the velocity model. We show that one method may have an advantage over another depending on the experiment geometry, assumptions about uncertainty in velocity and recorded signal, etc. We propose a unified approach to relative event location that includes double-difference and interferometry as special cases, and is applicable to velocity models and well geometries of arbitrary complexity, producing location estimators that are superior to those of double-difference and interferometry

Relative event localization in uncertain velocity model

We study a problem of localization of an unknown event location relative to previously located events using a single monitoring array in a monitoring well. It has been shown that using the available information about the previously located events for locating new events is advantageous to localizing each event independently. We compare the performance of two previously proposed localization methods, double-difference and interferometry, in varying signal noise and velocity uncertainty, and propose a framework for selecting the optimal method for a given experiment

Climate Variability in Indonesia from 615 ka to present: First Insights from Low-Resolution Coupled Model Simulations

We analyse the dynamics of Indonesian waters using the results of a set of 13 time-slice experiments simulated by the CCSM3-DGVM model. The experiments were carried out to study global climate variability between and within the Quaternary interglacials of Marine Isotope Stages (MIS) 1, 5, 11, 13, and 15. During boreal summer (June-July-August-September), in most of Indonesia, seasonal surface temperature anomalies can largely be explained by local insolation anomalies induced by the astronomical forcing. However, for some time slices, climate feedbacks may modify the surface temperature response in Indonesia, most pronounced in open water close to the Indian and Pacific Oceans. The warmest boreal summer sea-surface temperature (SST) anomaly compared to Pre-Industrial (PI) conditions of up to 1 K was found in the Banda Sea at 125 ka (MIS 5) and 579 ka (MIS 15). The coolest boreal summer SST anomaly down to –2 K at 495 ka (MIS 13) is equally distributed in Indonesian waters. During boreal winter, most of the moderate cooling over large portions of the land and the waters of Indonesia is also associated with local insolation. The most interesting finding in this study, a dipole and tripole precipitation pattern with up to 3.6 mm/day of rainfall anomaly during boreal summer is identified in the western part of the Indonesian waters, Indian Ocean to Banda Sea, and the eastern part of Indonesian waters. The results of this study are expected to be used as basic information to predict the climate in Indonesia for the present and future. This may add to the assessment provided by the IPCC for a better understanding of future climate change in the region, which is a prerequisite for alleviating its impacts

Interferometric microseism localization using neighboring fracture

We show how interferometric methods can be used to improve the location of microseismic events when those events come from several different fractures and are observed from a single well. This is the standard setup for a multi‐stage hydraulic fracturing experiment. Traditionally, in such experiments each event is located separately. Here, we adapt the interferometric approach to the problem of locating events relative to one another and show that this reduces the uncertainty in location estimates. To completely recover the Green's function between two events with interferometry requires a 2D array of receivers. When only a single observation well is available, we do not attempt to recover the full Green's function, but instead perform a partial redatuming of the data allowing us to reduce the uncertainty in two of the three components of the event location

Seismic wave scattering from rough interfaces

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 1989.Includes bibliographical references.by Michael D. Prange.Ph.D

Joint microseismic event location with uncertain velocity

We study the problem of the joint location of seismic events using an array of receivers. We show that locating multiple seismic events simultaneously is advantageous compared to the more traditional approaches of locating each event independently. Joint location, by design, includes estimating an uncertainty distribution on the absolute position of the events. From this can be deduced the distribution on the relative position of one event with respect to others. Many quantities of interest, such as fault sizes, fracture spacing or orientation, can be directly estimated from the joint distribution of seismic events. Event relocation methods usually update only the target event, while keeping the reference events fixed. Our joint approach can be used to update the locations of all events simultaneously. The joint approach can also be used in a Bayesian sense as prior information in locating a new event.Massachusetts Institute of Technology. Earth Resources Laboratory (Founding Members Consortium); National Science Foundation (U.S.) (Grant SES-0962484

A unified framework for relative source localization using correlograms

We study the problem of determining an unknown event location relative to previously located events using a single monitoring array in a monitoring well. We show that using the available information about the previously located events for locating new events is advantageous to localizing each event independently. By analyzing confidence regions, we compare the performance of two previously proposed localization methods, double-difference and interferometry, in varying signal noise and velocity uncertainty. We show that the double-difference method combats the signal noise much better due to the averaging over a larger number of travel time measurements. The interferometric method is superior where the main source of error is the velocity uncertainty between the event locations and the monitoring array. We propose a hybrid method that automatically balances these two approaches and produces a location estimator that is superior to either.ConocoPhillips (Firm