Robust 4D Research Articles

Impact of setup and geometric uncertainties on the robustness of free-breathing photon radiotherapy of small lung tumors

Purpose:Respiratory motion and patient setup error both contribute to the dosimetric uncertainty in radiotherapy of lung tumors. Managing these uncertainties for free-breathing treatments is usually done by margin-based approaches or robust optimization. However, breathing motion can be irregular and concerns have been raised for the robustness of the treatment plans. We have previously reported the dosimetric effects of the respiratory motion, without setup uncertainties, in lung tumor photon radiotherapy using free-breathing images. In this study, we include setup uncertainty. Methods:Tumor positions from cine-CT images acquired in free-breathing were combined with per-fraction patient shifts to simulate treatment scenarios. A total of 14 patients with 300 tumor positions were used to evaluate treatment plans based on 4DCT. Four planning methods aiming at delivering 54 Gy as median tumor dose in three fractions were compared. The planning methods were denoted robust 4D (RB4), isodose to the PTV with a central higher dose (ISD), the ISD method normalized to the intended median tumor dose (IRN) and homogeneous fluence to the PTV (FLU). Results:For all planning methods 95% of the intended dose was achieved with at least 90% probability with RB4 and FLU having equal CTV D50% values at this probability. FLU gave the most consistent results in terms of CTV D50% spread and dose homogeneity. Conclusions:Despite the simulated patient shifts and tumor motions being larger than observed in the 4DCTs the dosimetric impact was suggested to be small. RB4 or FLU are recommended for the planning of free-breathing treatments.

Design and Mechanical Properties of Maximum Bulk Modulus Microstructures Based on a Smooth Topology with Grid Point Density

The aim of topology optimisation is to determine the optimal distribution of material phases within the periodic cells of a microstructure. In this paper, the density of grid points under element volume fraction is constructed to replace the finite elements in the traditional SIMP framework, avoiding jagged and blurry boundaries in the computational process due to grid dependence. This is then combined with homogenisation theory, a microstructure topology optimisation algorithm with maximum bulk modulus under prescribed volume constraints is proposed, which can obtain 2D and 3D topologies with smooth boundaries. In addition, a closed form expression for the two-dimensional topological concave edge structure (taking the most typical topology as an example) was derived, and a compression experiment was conducted on the topological microstructure based on 3D metal printing technology. Scanning electron microscopy showed that the powder bonded on the surface of the printed structure was not completely melted and the step effect caused the finite element analysis results to be higher than the experimental results. Overall, the finite element simulation and experimental results of the concave surface structure have good consistency, with high strength and energy absorption effects. Topologies based on grid point density obtain microstructures with smooth boundaries, and the introduction of the Heaviside smoothing function and multiple filtering steps within this algorithm leads to more robust optimisation, facilitating 3D or 4D printing of microstructures that meet specific design requirements and confirming the feasibility of the proposed topology for lightweighting studies.

Robust and fast stochastic 4D Flow Vector-field signature technique for quantifying composite flow dynamics from 4D Flow MRI: Application to left atrial flow in atrial fibrillation

4D flow MRI is an emerging imaging modality that maps voxel-wise blood flow information as velocity vector fields that is acquired in 7-dimensional image volumes (3 spatial dimensions + 3 velocity directions + time). Blood flow in the cardiovascular system is often complex and composite involving multiple flow dynamics and patterns (e.g., vortex flow, jets, stagnating flow) that occur and interact simultaneously. The spectrum of such complex flow dynamics is embedded in the velocity vector field dynamics derived from 4D Flow MRI. However, current flow metrics cannot fully measure high-dimensional vector-field data and embedded complex composite flow data. Instead, these methods need to break down the vector-field data into secondary scalar fields of individual flow components using fluid dynamics operators. These methods are gradient-based and sensitive to data uncertainties, and only focus on individual flow components of the overall composite flow, therefore potentially underestimating the severity of overall flow changes associated with cardiovascular diseases. To address these limitations, in MICCAI 2021, we introduced a novel comprehensive stochastic 4D Flow vector-field signature technique that works directly on the entire spatiotemporal velocity vector field. This technique uses efficient stochastic gradient-free interrogation of multi-million flow vector-pairs per patient to derive the patient's unique flow profile of the complex composite flow alterations and in real-time processing. The signature technique's probabilistic gradient-free formulation should allow for highly robust quantification despite inherent errors in 4D flow MRI acquisitions. Here, we extend the application of the 4D flow vector-field signature technique to the left atrium to analyze complex composite flow changes in patients with atrial fibrillation. In 128 subjects, we performed extensive sensitivity testing and determined that the vector-field signature technique is highly robust to typical sources of data uncertainties in 4D flow MRI: degradation in spatiotemporal resolution, added gaussian noise, and segmentation errors. We demonstrate the excellent generalizability of the stochastic convergence from the aorta to the left atrium and between different 4D Flow MRI acquisition protocols. We compare the robustness of our technique to existing advanced flow quantification metrics of kinetic energy, vorticity, and energy loss demonstrating a superior performance of up-to 14-fold. Our results show the potential diagnostic and clinical utility of our signature technique in identifying distinctly altered composite flow signatures in atrial fibrillation patients independent of existing flow metrics.

Robust 4D climate-optimal flight planning in structured airspace using parallelized simulation on GPUs: ROOST V1.0

Abstract. The climate impact of non-CO2 emissions, which are responsible for two-thirds of aviation radiative forcing, highly depends on the atmospheric chemistry and weather conditions. Hence, by planning aircraft trajectories to reroute areas where the non-CO2 climate impacts are strongly enhanced, called climate-sensitive regions, there is a potential to reduce aviation-induced non-CO2 climate effects. Weather forecast is inevitably uncertain, which can lead to unreliable determination of climate-sensitive regions and aircraft dynamical behavior and, consequently, inefficient trajectories. In this study, we propose robust climate-optimal aircraft trajectory planning within the currently structured airspace considering uncertainties in standard weather forecasts. The ensemble prediction system is employed to characterize uncertainty in the weather forecast, and climate-sensitive regions are quantified using the prototype algorithmic climate change functions. As the optimization problem is constrained by the structure of airspace, it is associated with hybrid decision spaces. To account for discrete and continuous decision variables in an integrated and more efficient manner, the optimization is conducted on the space of probability distributions defined over flight plans instead of directly searching for the optimal profile. A heuristic algorithm based on the augmented random search is employed and implemented on graphics processing units to solve the proposed stochastic optimization computationally fast. An open-source Python library called ROOST (V1.0) is developed based on the aircraft trajectory optimization technique. The effectiveness of our proposed strategy to plan robust climate-optimal trajectories within the structured airspace is analyzed through two scenarios: a scenario with a large contrail climate impact and a scenario with no formation of persistent contrails. It is shown that, for a nighttime flight from Frankfurt to Kyiv, a 55 % reduction in climate impact can be achieved at the expense of a 4 % increase in the operating cost.

4DCT is long overdue for improvement.

4DCT is long overdue for improvement.

Robust extension of light fields with probable 3D distribution based on iterative scene estimation from multi-focus images

In this study, we propose an iterative approach to perform pseudo-scene reconstruction based on multi-focus images for estimating the 4D light fields of the scene robustly. An analogous scene-independent linear filtering approach has been proposed to efficiently achieve free viewpoint image reconstruction and scene refocusing with virtual bokeh by solely extracting 3D frequency components. However, it only succeeded in synthesizing limited regions of 4D light fields from multi-focus images, which can lead to awful degradation of reconstructed free viewpoint images outside the range due to the lack of the corresponding frequency components. In this paper, we directly utilize a linear relationship of 3D convolution combining multi-focus images and 3D scene by 3D blurring filters to estimate the 3D distribution itself of the scene instead of deriving the scene-independent linear filters from the relationship. In other words, we perform the scene reconstruction as a simplified convex optimization problem by modeling multi-focus images in multi-layered blurring composed of the scene and a bokeh filter. Algebraic reconstruction techniques of computed tomography, which uses the classical steepest descent method combined with projection onto convex sets (POCS) to ensure the convexity of the problem constraints, are introduced into such 3D scene reconstruction. The new method can be highly anticipated to assist us in extensively estimating robust 4D light fields. Experimental results illustrate that this approach enables good quality 3D image reconstruction with a wider range of 4D light fields. We also discuss the reduction of high computational costs and enormous memory requirements imposed by iterative algebraic reconstruction techniques. The quality of the obtained 4D light fields is comprehensively evaluated using both synthetic and real multi-focus images of practicable image resolution and depth range, additionally to an analysis of the faster processing times when comparing our iterative approach to the performance of the prior linear filters.

Dosimetric robustness of lung tumor photon radiotherapy evaluated from multiple event CT imaging

Purpose:Intrafractional respiratory motion is a concern for lung tumor radiotherapy but full evaluation of its impact is hampered by the lack of images representing the true motion. This study presents a novel evaluation using free-breathing images acquired over realistic treatment times to study the dosimetric impact of respiratory motion in photon radiotherapy. Methods:Cine-CT images of 14 patients with lung cancer acquired during eight minutes of free-breathing at three occasions were used to simulate dose tracking of four different planning methods. These methods aimed to deliver 54 Gy in three fractions to D50% of the target and were denoted as robust 4D (RB4), homogeneous fluence to the ITV (FLU) and an isodose prescription to the ITV with a high central dose (ISD), concurrently renormalized (IRN). Differences in dose coverage probability and homogeneity between the methods were quantified. Correlations between underdosage and attributes regarding the tumor and its motion were investigated. Results:Despite tumor motion amplitudes being larger than in the 4DCT all but FLU achieved the intended CTV D50% for the cohort average. For all methods but IRN at least 93% of the patients would have received 95% of the intended dose. No differences in D50% were found between RB4 and ISD nor IRN. However, RB4 led to better homogeneity. Conclusions:Tumor motion in free-breathing not covered by the 4DCT had a small impact on dose. The RB4 is recommended for planning of free-breathing treatments. No factor was found that consistently correlated dose degradation with patient or motion attributes.

Accurate automatic object 4D tracking in digital in-line holographic microscopy based on computationally rendered dark fields

Building on Gabor seminal principle, digital in-line holographic microscopy provides efficient means for space–time investigations of large volumes of interest. Thus, it has a pivotal impact on particle tracking that is crucial in advancing various branches of science and technology, e.g., microfluidics and biophysical processes examination (cell motility, migration, interplay etc.). Well-established algorithms often rely on heavily regularized inverse problem modelling and encounter limitations in terms of tracking accuracy, hologram signal-to-noise ratio, accessible object volume, particle concentration and computational burden. This work demonstrates the DarkTrack algorithm—a new approach to versatile, fast, precise, and robust 4D holographic tracking based on deterministic computationally rendered high-contrast dark fields. Its unique capabilities are quantitatively corroborated employing a novel numerical engine for simulating Gabor holographic recording of time-variant volumes filled with predefined dynamic particles. Our solution accounts for multiple scattering and thus it is poised to secure an important gap in holographic particle tracking technology and allow for ground-truth-driven benchmarking and quantitative assessment of tracking algorithms. Proof-of-concept experimental evaluation of DarkTrack is presented via analyzing live spermatozoa. Software supporting both novel numerical holographic engine and DarkTrack algorithm is made open access, which opens new possibilities and sets the stage for democratization of robust holographic 4D particle examination.

A Light Field FDL-HCGH Feature in Scale-Disparity Space

Many computer vision applications rely on feature detection and description, hence the need for computationally efficient and robust 4D light field (LF) feature detectors and descriptors. In this paper, we propose a novel light field feature descriptor based on the Fourier disparity layer representation, for light field imaging applications. After the Harris feature detection in a scale-disparity space, the proposed feature descriptor is then extracted using a circular neighborhood rather than a square neighborhood. It is shown to yield more accurate feature matching, compared with the LiFF LF feature, with a lower computational complexity. In order to evaluate the feature matching performance with the proposed descriptor, we generated a synthetic stereo LF dataset with ground truth matching points. Experimental results with synthetic and real-world dataset show that our solution outperforms existing methods in terms of both feature detection robustness and feature matching accuracy.

Dosimetric Validation of a System to Treat Moving Tumors Using Scanned Ion Beams That Are Synchronized With Anatomical Motion.

PurposeThe purpose of this study was to validate the dosimetric performance of scanned ion beam deliveries with motion-synchronization to heterogenous targets.MethodsA 4D library of treatment plans, comprised of up to 10 3D sub-plans, was created with robust and conventional 4D optimization methods. Each sub-plan corresponded to one phase of periodic target motion. The plan libraries were delivered to a test phantom, comprising plastic slabs, dosimeters, and heterogenous phantoms. This phantom emulated range changes that occur when treating moving tumors. Similar treatment plans, but without motion synchronization, were also delivered to a test phantom with a stationary target and to a moving target; these were used to assess how the target motion degrades the quality of dose distributions and the extent to which motion synchronization can improve dosimetric quality. The accuracy of calculated dose distributions was verified by comparison with corresponding measurements. Comparisons utilized the gamma index analysis method. Plan quality was assessed based on conformity, dose coverage, overdose, and homogeneity values, each extracted from calculated dose distributions.ResultsHigh pass rates for the gamma index analysis confirmed that the methods used to calculate and reconstruct dose distributions were sufficiently accurate for the purposes of this study. Calculated and reconstructed dose distributions revealed that the motion-synchronized and static deliveries exhibited similar quality in terms of dose coverage, overdose, and homogeneity for all deliveries considered. Motion-synchronization substantially improved conformity in deliveries with moving targets. Importantly, measurements at multiple locations within the target also confirmed that the motion-synchronized delivery system satisfactorily compensated for changes in beam range caused by the phantom motion. Specifically, the overall planning and delivery approach achieved the desired dose distribution by avoiding range undershoots and overshoots caused by tumor motion.ConclusionsWe validated a dose delivery system that synchronizes the movement of the ion beam to that of a moving target in a test phantom. Measured and calculated dose distributions revealed that this system satisfactorily compensated for target motion in the presence of beam range changes due to target motion. The implication of this finding is that the prototype system is suitable for additional preclinical research studies, such as irregular anatomic motion.

4D Printing of Shape Memory Materials for Textiles: Mechanism, Mathematical Modeling, and Challenges

AbstractShape memory materials (SMMs) in 3D printing (3DP) technology garnered much attention due to their ability to respond to external stimuli, which direct this technology toward an emerging area of research, “4D printing (4DP) technology.” In contrast to classical 3D printed objects, the fourth dimension, time, allows printed objects to undergo significant changes in shape, size, or color when subjected to external stimuli. Highly precise and calibrated 4D materials, which can perform together to achieve robust 4D objects, are in great demand in various fields such as military applications, space suits, robotic systems, apparel, healthcare, sports, etc. This review, for the first time, to the best of the authors’ knowledge, focuses on recent advances in SMMs (e.g., polymers, metals, etc.) based wearable smart textiles and fashion goods. This review integrates the basic overview of 3DP technology, fabrication methods, the transition of 3DP to 4DP, the chemistry behind the fundamental working principles of 4D printed objects, materials selection for smart textiles and fashion goods. The central part summarizes the effect of major external stimuli on 4D textile materials followed by the major applications. Lastly, prospects and challenges are discussed, so that future researchers can continue the progress of this technology.

1D to 2D Transition in Tellurium Observed by 4D Electron Microscopy.

A new microwave-enhanced synthesis method for the production of tellurium nanostructures is reported-with control over products from the 1D regime (sub-5nm diameter nanowires), to nanoribbons, to the 2D tellurene regime-along with a new methodology for local statistical quantification of the crystallographic parameters of these materials at the nanometer scale. Using a direct electron detector and image-corrected microscope, large and robust 4D scanning transmission electron microscopy datasets for accurate structural analysis are obtained. These datasets allow the adaptation of quantitative techniques originally developed for X-ray diffraction (XRD) refinement analyses to transmission electron microscopy, enabling the first demonstration of sub-picometer accuracy lattice parameter extraction while also obtaining both the size of the coherent crystallite domains and the nanostrain, which is observed to decrease as nanowires transition to tellurene. This new local analysis is commensurate with global powder XRD results, indicating the robustness of both the new synthesis approach and new structural analysis methodology for future scalable production of 2D tellurene and characterization of nanomaterials.

Mitigation of the Interplay Effects of Combining 4D Robust With Layer Repainting Techniques in Proton-Based SBRT for Patients With Early-Stage Non-small Cell Lung Cancer.

ObjectiveThe objective of this study was to evaluate the interplay effects in proton-based stereotactic body radiotherapy (SBRT) using 4D robust optimization combined with iso-energy layer repainting techniques for non-small cell lung cancer (NSCLC).Materials and MethodsTwelve patients with early-stage NSCLC who underwent 4DCT were retrospectively selected. A robust CTV-based 4D plan was generated for each based on commercial Treatment planning system (TPS), considering patient setup errors, range uncertainties, and organ motion. The 4D static dose (4DSD) and 4D dynamic dose (4DDD) were calculated using a hybrid deformable algorithm and simulated proton delivery system. An index was developed to quantitatively evaluate the interplay effects. The interplay effects of the 4D robust plan and multiple iso-energy layers (3, 4, 5, 6, and 7) of the robust repainting 4D plan were calculated based on to select the optimal times for layer repainting.ResultsDue to the interplay effects, the mean target values D2 and D5 increased to 1.28 and 1.01%, and the target values D98 and D95 decreased to 2.01 and 1.77%, respectively, for the 4D Robust SBRT plan. After multiple iso-energy repainting times, the interplay effects of the target values D98 and D95 tended to migrate, from 2.01 to 0.92% in target value D98 and from 1.77 to 0.89% in target value D95, respectively. Moreover, a positive linear correlation was observed between the optimal interplay effect mitigation and target range of motion.ConclusionIn proton-based 4D Robust SBRT, the interplay effects degraded the target dose distribution but were mitigated using iso-energy layer repainting techniques. However, there was no significant correlation between the number of repainting layers and improvements in the dose distributions. The optimal layer repainting times based on the interplay effect index were ascertained according to the patient characteristics.

4D MRI: Robust sorting of free breathing MRI slices for use in interventional settings.

We aim to develop a robust 4D MRI method for large FOVs enabling the extraction of irregular respiratory motion that is readily usable with all MRI machines and thus applicable to support a wide range of interventional settings. We propose a 4D MRI reconstruction method to capture an arbitrary number of breathing states. It uses template updates in navigator slices and search regions for fast and robust vessel cross-section tracking. It captures FOVs of 255 mm x 320 mm x 228 mm at a spatial resolution of 1.82 mm x 1.82 mm x 4mm and temporal resolution of 200ms. A total of 37 4D MRIs of 13 healthy subjects were reconstructed to validate the method. A quantitative evaluation of the reconstruction rate and speed of both the new and baseline method was performed. Additionally, a study with ten radiologists was conducted to assess the subjective reconstruction quality of both methods. Our results indicate improved mean reconstruction rates compared to the baseline method (79.4% vs. 45.5%) and improved mean reconstruction times (24s vs. 73s) per subject. Interventional radiologists perceive the reconstruction quality of our method as higher compared to the baseline (262.5 points vs. 217.5 points, p = 0.02). Template updates are an effective and efficient way to increase 4D MRI reconstruction rates and to achieve better reconstruction quality. Search regions reduce reconstruction time. These improvements increase the applicability of 4D MRI as a base for seamless support of interventional image guidance in percutaneous interventions.

Towards fast and robust 4D optimization for moving tumors with scanned proton therapy.

Robust optimization is becoming the gold standard for generating robust plans against various kinds of treatment uncertainties. Today, most robust optimization strategies use a pragmatic set of treatment scenarios (the so-called uncertainty set) consisting of combinations of maximum errors, of each considered uncertainty source (such as tumor motion, setup and image-conversion errors). This approach presents two key issues. First, a subset of considered scenarios is unnecessarily improbable which could potentially compromise the plan quality. Second, the resulting large uncertainty set leads to long plan computation times, which limits the potential for robust optimization as a standard clinical tool. In order to address these issues, a method is introduced which is able to preselect a limited set of relevant treatment error scenarios. Uncertainties due to systematic setup errors, image-conversion errors and respiratory tumor motion are considered. A four-dimensional (4D)-equiprobability hypersurface is defined, which takes into account the joint probabilities of the above-mentioned uncertainty sources. Only scenarios that lie on the predefined 4D hypersurface are considered, guaranteeing statistical consistency of the uncertainty set. In this regard, twelve scenarios are selected that cover maximum spatial displacements of the tumor during breathing. Subsequently, additional scenarios are considered (sampled from the aforementioned 4D hypersurface) in order to cover any estimated residual range errors. Two different scenario-selection procedures were tested: (a) the maximum displacements (MD) method that only considers twelve scaled maximum displacement scenarios and (b) maximum displacements and residual range (MDR) method which, in addition to the scaled maximum displacement scenarios, considers additional maximum range uncertainty scenarios. The methods were tested for five lung cancer patients by performing comprehensive Monte Carlo robustness evaluations. A plan computation time gain of 78% is achieved by applying the MD method, whilst obtaining a target robustness of D larger than 95% of the prescribed dose, for the worst-case scenario. Additionally, the MD method has the potential to be fully automatic which makes it a promising candidate for fast automatic planning workflows. The MDR method produced plans with excellent target robustness (D larger than 95% of the prescribed dose, even for the worst-case scenario), whilst still obtaining a significant plan computation time gain of 57%. Two scenario-selection procedures were developed which achieved significant reduction of plan computation time and memory consumption, without compromising plan quality or robustness.

Four-dimensional Plan Optimization for the Treatment of Lung Tumors Using Pencil-beam Scanning Proton Radiotherapy.

Purpose This study aimed to evaluate the effectiveness of four-dimensional (4D) robust optimization for proton pencil-beam scanning (PBS) treatment of lung tumors.Patients and methods In seven patients with lung cancer, proton beam therapy was planned using 4D robust optimization over 4D computed tomography (CT) data sets. The gross target volume (GTV) was contoured based on individual breathing phases, and a 5-mm expansion was used to generate the clinical target volume (CTV) for each phase. The 4D optimization was conducted directly on the 4D CT data set. The robust optimization settings included a CT Hounsfield unit (HU) uncertainty of 4% and a setup uncertainty of 5 mm to obtain the CTV. Additional target dose objectives such as those for the internal target volume (ITV) as well as the organ-at-risk (OAR) dose requirements were placed on the average CT. For comparison, three-dimensional (3D) robust optimization was also performed on the average CT. An additional verification 4D CT was performed to verify plan robustness against inter-fractional variations.Results Target coverages were generally higher for 4D optimized plans. The difference was most pronounced for ITV V70Gy when evaluating individual breathing phases. The 4D optimized plans were shown to be able to maintain the ITV coverage at full prescription, while 3D optimized plans could not. More importantly, this difference in ITV V70Gy between the 4D and 3D optimized plans was also consistently observed when evaluating the verification 4D CT, indicating that the 4D optimized plans were more robust against inter-fractional variations. Less difference was seen between the 4D and 3D optimized plans in the lungs criteria: V5Gy and V20Gy.Conclusion The proton PBS treatment plans optimized directly on the 4D CT were shown to be more robust when compared to those optimized on a regular 3D CT. Robust 4D optimization can improve the target coverage for the proton PBS lung treatments.

PV-0202: Towards a more robust 4D optimization for PBS-based moving tumor treatments

PV-0202: Towards a more robust 4D optimization for PBS-based moving tumor treatments

Monitoring photopolymerization reactions through thermal imaging: A unique tool for the real‐time follow‐up of thick samples, 3D printing, and composites

ABSTRACTThe ever increasing applications of photopolymers from historical thin (<50 µm) coatings to very deep samples (>1 cm) require the development of robust 4D monitoring strategies able to assess photopolymerization efficiencies (first dimension) as a function of time (second dimension) and position (third and fourth dimensions). Therefore, here, we demonstrated that thermal imaging is a valuable photopolymerization monitoring device showing: (a) very high response times (<1 s); (b) high repeatability of the measurement; (c) strong adaptability of the setup to various conditions (e.g., onto irregular surfaces or inside a real time Fourier transformed infrared spectrometer (RT‐FTIR)); (d) extremely deep photopolymerization follow‐ups (and subsequent rationalization) with good resolution in time and in space (real‐time thermal imaging microscopy experiments); (e) adaptability to applied materials. This monitoring strategy was found particularly robust when taking into account all the heat generating phenomena (i.e., direct heating from the lamp vs. temperature raised due to monomer conversion). As a result, we propose thermal imaging as the next reference monitoring system for the new ranges of thick and/or filled samples (e.g., 3D objects, composites) and/or applied photopolymerizations (e.g., 3D printing) more and more present in the literature. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2018, 56, 889–899

Robust and Adaptive 4D Optimization of VMAT in Head and Neck Cancer Patients

Robust and Adaptive 4D Optimization of VMAT in Head and Neck Cancer Patients

Realizing 4D seismic value on stacked reservoirs in northwest Borneo

Time-lapse seismic is commonly used today for production monitoring worldwide. However, the experience in southeast Asian clastic reservoirs is more limited than in regions such as the North Sea or Gulf of Mexico. The regional structural complications associated with thin-stacked sands and faulting pose interpretation challenges in addition to unusual time-lapse signals, complex commingled production data, and seismic data holes due to platforms. An integrated approach is presented to use 4D seismic in stacked reservoirs to overcome these challenges. Several successful examples from northwest Borneo (Brunei Darussalam) are presented in which robust 4D signals have been interpreted and used for derisking near-field exploration wells, identifying infill drilling targets, changing well trajectories, supporting hydrocarbon maturation by identifying undrained hydrocarbons, and assessing the quality of static and dynamic reservoir models.