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The article presents the concept of a computer system for interpreting unconventional oil and gas deposits with the use of X-ray computed tomography results. The functional principles of the solution proposed are presented in the article. The main goal is to design a product which is a complex and useful tool in a form of a specialist computer software for qualitative and quantitative interpretation of images obtained from X-ray computed tomography. It is devoted to the issues of prospecting and identification of unconventional hydrocarbon deposits. The article focuses on the idea of X-ray computed tomography use as a basis for the analysis of tight rocks, considering especially functional principles of the system, which will be developed by the authors. The functional principles include the issues of graphical visualization of rock structure, qualitative and quantitative interpretation of model for visualizing rock samples, interpretation and a description of the parameters within realizing the module of quantitative interpretation. [ABSTRACT FROM AUTHOR]

The paper discusses the opportunities for obtaining valuable knowledge on the basis of video recordings from introscopic cameras, used to investigate mining boreholes. It also presents an original approach to the task of building a system, which would facilitate the process of searching for visually similar geological structures, and which would constitute an alternative to time-consuming manual profiling. The analysis of measurements performed with an introscopic camera is based on a feature space defined by the Authors, and uses the methods of mathematical morphology for processing video sequences, as well as data analysis for the decision-making process. As a result of the research, it was established that the methods of image processing and data analysis are an effective tool when it comes to automate the decision-making process with regards to the determination of the visual similarity of geological layers which make up a given, investigated area of a borehole. The methods in question yield a high percentage of correct decisions. [ABSTRACT FROM AUTHOR]

Modern geological techniques have resulted in vast and growing databases of digital images and video sequences of rocks, which are available for the use of researchers. The number of database images continues to increase exponentially, creating a need for techniques that will enable the automation of data set management. Desired techniques include query by image, a topic that has been extensively elaborated on in the literature recently. Unfortunately, using such techniques in the geological sciences has been very sporadic and insufficient. This paper presents the evaluation of characteristic local features within rock images for tracking objects on images or video sequences. It also discusses the possibilities for using selected local feature descriptors for content-based image retrieval (CBIR) in the area of geological sciences. The evaluation was performed for the Speeded Up Robust Features (SURF), Binary Robust Invariant Scalable Keypoints (BRISK), Harris–Stephens Algorithm (HSA), Minimum Eigenvalue Algorithm (MEA), and Features from Accelerated Segment Test algorithm (FAST) methods, which are widely known and appreciated in the computer vision field. These methods were analysed for their application to microscopic images of rocks. Five functional cases of geological grain tracking were investigated, based on a selected non-transformed query image, as well as a computer-rotated, acquisitive-rotated, computer-magnified, and an acquisitive-magnified query image. The results demonstrated that these methods can be successfully used for geological applications. [ABSTRACT FROM AUTHOR]

Computed X-ray tomography (CT), together with pulse and pressure decay permeability methods were used to evaluate a formula for absolute reservoir permeability. For this reason, 62 core samples representing geological material of tight, gas-bearing sandstones, mudstones, limestones, and dolostones were studied. Samples were divided into two groups with lower and higher permeability values. Images of the pore space were processed and interpreted to obtain geometrical parameters of the objects (pores, microfractures) with 0.5 × 0.5 × 0.5 µm3 voxel size. Statistical methods, which included basic statistical analysis, linear regression, and multiple linear regression analysis, were combined to evaluate the formula for absolute permeability. It appeared that the following parameters: Feret Breadth/Volume, Flatness/Anisotropy, Feret Max/Flatness, moments of inertia around middle principal axis I2/around longest principal axis I3, Anisotropy/Flatness, Flatness/Anisotropy provided the best results. The presented formula was obtained for a large set of data and is based only on the geometric parameters of the pore space. The novelty of the work is connected with the estimation of absolute permeability using only data from the CT method for tight rocks. [ABSTRACT FROM AUTHOR]

The main goal was the analysis of parameters describing the structure of the pore space of carbonate rocks, based on tomographic images. The results of CT images interpretation, made for 17 samples of Paleozoic carbonate rocks were shown. The qualitative and quantitative analysis of a pore system was performed. Objects were clustered according to the pore size. Within the clusters, the geometry parameters were analysed. The following dependences were obtained for carbonate rocks, also for individual clusters (due to the volume): (1) a linear relationship (on a bilogarithmic scale) between the specific surface and the Feret diameter and (2) a strong linear relationship between specific surface area and Feret diameter and average diameter of the objects calculated for the sphere. The results were then combined with available results from standard laboratory tests, including NMR and MICP. [ABSTRACT FROM AUTHOR]

Strawberry fruits are products of high commercial and consumption value, and, at the same time, they are difficult to harvest due to their very low mechanical strength and difficulties in identifying them within the bush. Therefore, robots collecting strawberries should be equipped with four subsystems: a video object detection system, a collecting arm, a unit for the reception and possible packaging of the fruit, and a traction system unit. This paper presents a concept for the design and operation of the working section of a harvester for strawberry fruit crops grown in rows or beds, in open fields, and/or under cover. In principle, the working section of the combine should meet parameters comparable with those of manually harvested strawberries (efficiency, quality of harvested fruit) and minimise contamination in the harvested product. In order to meet these requirements, in the presented design concept, it was assumed that these activities would be performed during harvesting with the natural distribution of fruits within the strawberry bush, and the operation of the working head arm maneuvering in the vicinity of the picked fruit, the fruit receiving unit, and other obstacles was developed on the basis of image analysis, initially general, and in detail in the final phase. The paper also discusses the idea of a vision system in which the algorithm used has been positively tested to identify the shapes of objects, and due to the similarity of space, it can be successfully used for the correct location of strawberry fruit. [ABSTRACT FROM AUTHOR]