Mohammed Alfarhan

Laser rangefinders and ArcGIS combined with three-dimensional photorealistic modeling for mapping outcrops in the Slick Hills, Oklahoma

The mapping of geology is conventionally done visually in a hands-on fashion, and the data are recorded in a field book or with photography. An alternative technique that combines reflectorless laser rangefinders or high-speed terrestrial laser scanners, global positioning system, and the Environmental Systems Research Institute (ESRI) ArcGIS software platform has been developed that is effective for mapping geology at a distance and in three dimensions. Portable handheld reflectorless lasers are used to capture geologic features such as contacts and terrain and can be combined with digital elevation models in ArcGIS software. Fast terrestrial laser scanners capture an entire exposure at the detail and accuracy of (3D) photorealistic (virtual) models with the additional color information from image pixels. This latter method is expensive and complicated and requires significant amounts of field and processing effort. The laser gun approach is simple, portable, and cost effective. When integrated with ESRI ArcGIS software and a module, such as our recently developed ArcGIS extension 3DLT (laser tool), a simple yet sophisticated platform exists for mapping, visualizing, and analyzing outcrops in real time in the field. The potential of laser mapping is demonstrated in the Paleozoic outcrops of a structural geology teaching site in the Slick Hills, Oklahoma. Fast laser scanning and digital photography are used to build a 3D photorealistic model of an area of the anticline. The 3DLT is used for mapping specific detailed features such as contacts and faults. Three-dimensional quantitative information can be extracted from the geology with these methods. A laser rangefinder combined with 3DLT can image and display terrain and outcrop features in the field, in real time. Mapping with fast scanners requires several steps in processing of the point cloud data utilizing a variety of sophisticated and expensive software, but can capture an entire outcrop, such as a mountainside. The resulting model then can be analyzed in the lab. When combined with digital photography, virtual photorealistic models derived from point clouds can be even more effectively analyzed. The most appropriate method for digitally mapping geology depends on a variety of issues, such as cost, time, complexity, portability, and the project goals.

Rise and demise of the New Lakes of Sahara

Multispectral remote sensing data and digital elevation models were used to examine the spatial and temporal evolution of the New Lakes of Sahara in southern Egypt. These lakes appeared in September 1998, when water spilled northwestward toward the Tushka depression due to an unusual water rise in Lake Nasser induced by high precipitation in the Ethiopian Highlands. Five lakes were formed in local depressions underlain by an impermeable Paleocene shale and chalk formation. The lakes developed through three stages. (1) A rise stage occurred from September 1998 to August 2001; the area covered by the lakes reached ∼1586 km 2 . In this stage the rate of water supply far exceeded the rate of water loss through evaporation. This stage was characterized by an early phase (August 1998–August 1999) when the area covered by the lakes increased by ∼75 km 2 /month. This was followed by a late phase (August 1999–August 2001), in which area increase averaged ∼28 km 2 /month. (2) A steady-state stage occurred from August 2001 to August 2003, during which the area covered by the lakes remained relatively unchanged and water lost through evaporation was continuously replaced by water supply from Lake Nasser. (3) A demise stage occurred from August 2003 to April 2007, during which water supply from Lake Nasser stopped completely and water was continuously evaporating. The area covered by the lakes decreased to ∼800 km 2 with an average loss of ∼17 km 2 /month. If this trend continues, the New Lakes of Sahara will disappear completely by March 2011. The spatial distribution of the New Lakes of Sahara is strongly controlled by morphologically defined east-, north-, northeast-, and northwest-trending faults. The water recharge of the Nubian aquifer by the New Lakes of Sahara is insignificant; much of the lakes9 area is above an impermeable formation.

ICESat waveform-based land-cover classification using a curve matching approach

Light detection and ranging waveforms record the entire one-dimensional backscattered signal as a function of time within a footprint, which can potentially reflect the vertical structure information of the above-ground objects. This study aimed to explore the potential of the Geoscience Laser Altimeter System sensor on board the Ice, Cloud, and Land Elevation Satellite to perform land-cover classification by using only the profile curve of the full waveform. For this purpose, a curve matching method based on Kolmogorov–Smirnov (KS) distance was developed to measure the curve similarity between an unknown waveform and a reference waveform. A set of reference waveforms were first extracted from the training data set based on a principal component analysis (PCA). The unknown waveform was then compared with individual reference waveforms derived using KS distance and assigned to the class with the closest similarity. The results demonstrated that the KS distance-based land-cover classification using the waveform curve was able to achieve an overall accuracy of 87.2% and a kappa coefficient of 0.80. It outperformed the widely adopted rule-based method using Gaussian decomposition parameters by 3.5%. The research also indicated that the PCA- selected reference waveforms achieved substantially better results than randomly selected reference waveforms.

Application of a 3D photorealistic model for the geological analysis of the Permian carbonates (Khuff Formation) in Saudi Arabia

Three dimensional (3D) photorealistic models of geological outcrops have the potential to enhance the teaching of earth sciences by providing scale models in a virtual reality environment. These models can be run on low-cost desktop computers. Photorealistic models for geological outcrops are a digital illustration of outcrop photographs with either a point cloud representation or Triangular Irregular Network (TIN) mesh of the outcrop surface. The level of detail for these models is dependent on the target resolutions (physical and optical) that were used during data acquisition. In addition, the technique in which the data is rendered as a digital model affects the level of detail that can be observed by the geologists. A colored point cloud representation is suitable for large-scale features, but fine details are lost when the geologist zooms in to view the model close up. In contrast, a photorealistic model that is constructed from photographs draped onto a triangle mesh surface derived from Light Detection and Ranging (LiDAR) point clouds provides a level of detail that is restricted only by the resolution of the photographs.

Workflow of integration of digital outcrop modeling and sedimentology of the Early Triassic Upper Khartam Member of Khuff Formation, central Saudi Arabia

The Permian–Triassic Khuff Formation is considered to be the most prolific for the natural gas production in the world. The Khuff reservoirs exhibit vertical and lateral heterogeneities which cannot be fully captured within the interwell spacing from the subsurface data. The Upper Khartam Member in central Saudi Arabia represents an excellent outcrop analog for the upper parts of Khuff-B and the whole Khuff-A reservoirs. The main objective of this study is to reconstruct digital outcrop model of the Upper Khartam Member. This study included sedimentological data and digital laser scanning modeling. Four stratigraphic sections were measured to cover the whole outcrop of Upper Khartam, and a composite section was constructed. The investigations revealed that the studied outcrop of Upper Khartam comprises six lithofacies associations deposited in three depositional settings: offshore (deep–shallow subtidal zone), foreshoal, and shoal complex. The terrestrial laser scanner was used to scan the outcrop from four different scan positions. The Polyworks software was used for the processing and to produce the photorealistic model for Upper Khartam. ArcGIS combined with the Geo Analysis Tool was utilized to interpret the digital models. The digital modeling allows accurate structural and statistical measurements of lithofacies and integrated with the traditional field data on it and examined the lateral continuity and the architecture of the strata in the outcrop. Also, the model revealed the architecture and the continuity of the reservoir units as well as the barriers or the non-reservoir units within the studied outcrop. The integration of the results of this work with subsurface data might help to provide better understanding and prediction of the quality of Khuff reservoirs in the subsurface.

Curve matching approaches to waveform classification: a case study using ICESat data

Light Detection and Ranging (LiDAR) waveforms are being increasingly used in many forest and urban applications, especially for ground feature classification. However, most studies relied on either discretizing waveforms to multiple returns or extracting shape metrics from waveforms. The direct use of the full waveform, which contains the most comprehensive and accurate information has been scarcely explored. We proposed to utilize the complete waveform to test its ability to differentiate between objects having distinct vertical structures using curve matching approaches. Two groups of curve matching approaches were developed by extending methods originally designed for pixel-based hyperspectral image classification and object-based high spatial image classification. The first group is based on measuring the curve similarity between an unknown waveform and a reference waveform, including curve root sum squared differential area (CRSSDA), curve angle mapper (CAM), and Kullback–Leibler (KL) divergence. The second group assesses the curve similarity between an unknown and reference cumulative distribution functions (CDFs) of their waveforms, including cumulative curve root sum squared differential area (CCRSSDA), cumulative curve angle mapper (CCAM), and Kolmogorov–Smirnov (KS) distance. When employed to classify open space, trees, and buildings using ICESat waveform data, KL provided the highest average classification accuracy (87%), closely followed by CCRSSDA and CCAM, and they all significantly outperformed KS, CRSSDA, and CAM based on 15 randomized sample sets.