Integrated Semi-Supervised Clustering Method and Its Application in Rock-Typing in AA Reservoir

Rock-typing is complicated and critical for numerical simulation. Therefore, some researchers proposed several clustering methods to make classification automatic and convenient. However, traditional methods only focus in specific area such as lithofacies or petrophysical data instead of integrated clustering. Besides, all the clustering method are related to classification interval determined subjectively. Therefore, a new clustering method for rock-typing integrated different disciplines is critical for modelling and reservoir simulation. In this paper, we proposed a novel semi-supervised clustering method integrated with data from different disciplines, which can divide rock type automatically and precisely. Considering AA reservoir is a porous carbonate reservoir with seldom fracture and vug, FZI (Flow Zone Indicator) and RQI (Reservoir Quality Index) is utilized as the corner stone of the clustering method after collection and plotting for porosity and permeability data for cores from AA reservoir. Then lithofacies, sedimentary facies and petrophysical data are applied as constraints to improve FZI method. Hamming distance and earth mover distance are imported to build integrated function for clustering method. Finally, based on output results of integrated clustering method from experimental data, grid properties of model in Petrel software are imported as the input parameter for further procession. Therefore, saturation region for numerical simulation built by rock-typing is constructed. The results show that new method could make classification accurately and easily. History matching results for watercut indicate that new saturation regions improve the numerical simulation performance.

Geologically based integrated approach for zonation of a Late Jurassic–Early Cretaceous carbonate reservoir; a case from Persian Gulf

In this study, our attempt is to integrate sedimentological and petrophysical data for reservoir evaluation in the sequence stratigraphic framework. Petrographic analysis of the Late Jurassic–Early Cretaceous Fahliyan Formation reservoirs of two oilfields in the northwest of the Persian Gulf led to recognition of twelve microfacies. They can be classified into four facies associations, including open marine, shoal, lagoon and tidal flat, which are deposited in a homoclinal ramp carbonate. Sequence stratigraphy of the studied successions led to the recognition of three third-order depositional sequences based on vertical changes in microfacies and gamma ray analysis. Except for the upper boundary of the third sequence, the other sequence boundaries are type I (SBT.1). Dissolution is the most important diagenetic feature that affected the lower depositional sequence which is caused by the development of subaerial exposure after the deposition of the Fahliyan Formation, whereas cementation is the main diagenetic feature affecting the second- and third depositional sequences, causing their lower reservoir quality. In order to identify the flow units, the flow zone index methods, porosity throat radius (R35) and modified Lorenz based on stratigraphy were applied. The key wells studied in this area have shown good correlation throughout the studied oilfields which may potentially be used for hydrocarbon exploration and field development in the Late Jurassic–Early Cretaceous deposits of the Persian Gulf. This study integrates geological and petrophysical data (rock typing) toward sequence stratigraphic framework.

Correcting Subsurface Seismic Depth Uncertainty in Real-Time Using Reservoir Navigation Distance-to-Bed Mapping

The most common challenge in horizontal drilling is depth uncertainty which can be due to poor seismic data or interpretation. It is arguable that a successful landing of the wellbore in the reservoir optimally and within the desired zone is the most challenging in most geosteering operation. The presence of fluid contacts such as oil-water-contact (OWC) and gas-oil-contact (GOC) complicates the whole drilling process, most especially if these fluid contacts are not well defined or known. Additionally, the ability to map the boundaries of the reservoir as the BHA drills the lateral section is an added advantage to remaining within the desired reservoir section. The success of any reservoir navigation service where seismic uncertainty at the reservoir top is high will rely largely on how effective the geosteering system is and how the geosteering engineer is able to react promptly to changes while landing the well in the reservoir and drilling the lateral section with without exiting the reservoir. Reservoir Navigation Service (RNS) provides the means for the drilling near horizontal or horizontal wells for the purpose of increasing hydrocarbon extraction from the earth's subsurface. This involves the use of a pre-defined bottom hole assembly (BHA) with inbuilt downhole logging while drilling (LWD) and measurement while drilling (MWD) sensors. The measurements from these downhole sensors are uplinked to the surface of the wellbore where they are converted to meaningful petrophysical data. The goal is to use the downhole petrophysical data such as gamma ray, propagation resistivity and so on, to update an existing pre-well geological model of a section of the earth in such a way that the final result depicts the true model picture of the earth subsurface. This paper focuses on using well CBH-44L to showcase how the use of real-time distance-to-boundary (D2B) measurement from a deep reading azimuthal propagation resistivity tool is use to correct for depth uncertainty in seismic, thereby, improving the chance of successfully landing and drilling a horizontal well.

APPLICATION OF THE METHOD OF GROUP ACCOUNTING OF ARGUMENTS FOR THE ANALYSIS OF PETROPHYSICAL DATA

The paper considers a range of tasks related to the processing and analysis of petrophysical data, which are effectively solved by the method of group accounting of arguments (MGUA). MGUA is a machine learning method that is an alternative to regression analysis and neural network modeling. The method was tested when working with information from the petrophysical database of crystalline and sedimentary rocks of the Voronezh Crystal Massif (VCM). The basis of the analysis technology is the formation of complex identification equations that allow you to generalize, analyze and effectively use petrophysical data. Previously, the use of such equations for estimating the ore content of nickel-bearing intrusions of the mamonsky complex was considered. Examples of solving problems of robust estimation and identification of petrophysical data are provided. It is shown that the identification models of the MGUA allow automating the procedure for detecting outliers in the data, assess the belonging of rocks to a certain material complex. Since petrophysical information is a necessary link in the geological interpretation of geophysical observations, the experience of obtaining complex models linking the density of metamorphic and intrusive rocks of the VCM with electrical resistivity and magnetic susceptibility is interesting.

Petrophysical data analysis using MATLAB tools for the middle Miocene sediments in the Gulf of Suez, Egypt

<p>Middle Miocene sediments are the most important productive oil zone in the Sidri Member within Belayim oil field. The Belayim oil field is one of well-known oil fields in Egypt, which is located on the eastern side of the Gulf of Suez. The Sidri Member consists of shales, sandstones and limestone with net pay thickness ranges from 5 to 60 m. The oil saturated sandstone layers are coarse grained and poorly sorted, which are classified into sub-litharenite, lithic arkose and arkose microfacies with several diagenetic features. This study measured and collected petrophysical data from the sandstone core samples and well logging of drilling sites to evaluate oil potentiality and reservoir characteristics of the Sidri Member. The collected petrophysical data are porosity, permeability, water and oil saturation, resistivity and grain and bulk density. MATLAB tools were used to analyze the extensive dataset, quantify the correlation trends and visualize the spatial distribution. The porosity values range from 2% to 30%, which show very good positive correlation with horizontal permeability (0 to 1,300 md). The porosity as well as type and radius of pore throats present important relationship with permeability and fluid saturation. The petrophysical characteristics of the Sidri sandstones are controlled by the depositional texture, clay-rich matrix and diagenetic features. This study distinguished poorly, fairly, good to excellent reservoir intervals in the Sidri Member. The best quality reservoir potentiality is recorded in the well sorted sand layers with little clay matrix in the lower part of the Sidri Member. The petrophysical characteristics are high porosity (20% to 30%), high permeability (140 to 1250 md), high oil saturation (20% to 78%), low water saturation (13% to 36%), moderate to high resistivity and relatively low grain density. The hydrocarbon production rates reported from the Sidri reservoirs are greatly correlated with the petrophysical characteristics described in this study.</p>

Density and magnetic susceptibility relationships in non-magnetic granites; a “wildcard” for modeling potential fields geophysical data.

<p>Geophysical surveying (both gravity and magnetic) is of great help in 3D modeling of granitic bodies at depth. As in any potential-field geophysics study, petrophysical data (density [r], magnetic susceptibility [k] and remanence) are of key importance to reduce the uncertainty during the modeling of rock volumes. Several works have already demonstrated that ∂<sup>18</sup>O or [SiO<sub>2</sub>] display a negative correlation to density and to magnetic susceptibility. These relationships are particularly stable (and linear) in the so-called “non-magnetic” granites (susceptibilities falling within the paramagnetic range; between 0 and 500 10<sup>-6</sup> S.I.) and usually coincident with calc-alcaline (CA) compositions (very common in Variscan domains). In this work we establish robust correlations between density and magnetic susceptibility at different scales in CA granites from the Pyrenees. Other plutons from Iberia were also considered (Veiga, Monesterio). The main goal is to use the available and densely sampled nets of anisotropy of magnetic susceptibility (AMS) data, performed during the 90’s and early 2000’s, together with new data acquired in the last few years, as an indirect measurement of density in order to carry out the 3D modelling of the gravimetric signal.</p><p> </p><p>We sampled some sections covering the main range of variability of magnetic susceptibility in the Mont Louis-Andorra, Maladeta and Marimanha granite bodies (Pyrenees), all three characterized by even and dense nets of AMS sites (more than 550 sites and 2500 AMS measurements). We performed new density and susceptibility measurements along two main cross-sections (Maladeta and Mont Louis-Andorra). In these outcrops, numerous measurements (usually more than 50) were taken in the field with portable susceptometers (SM20 and KT20 devices). Density data were derived from the Arquimedes principle applied on large hand samples cut in regular cubes weighting between 0.3 and 0.6 kg (whenever possible). These samples were subsampled and measured later on with a KLY-3 susceptibility bridge in the laboratory. Additionally, some density data were derived from the geometry and weighting of AMS samples.</p><p> </p><p>After the calibration of portable and laboratory susceptometers, density and magnetic susceptibility were plotted together. Regressions were derived for every granite body and they usually followed a linear function similar to: r = 2600 kg/m<sup>3</sup> + (0.5 * k [10<sup>-6</sup> S.I.]). As previously stated, this relationship is only valid in CA and paramagnetic granites, where iron is mostly fractioned in iron-bearing phyllosilicates and the occurrence of magnetite is negligible (or at least its contribution to the bulk susceptibility). These relationships allow transforming magnetic susceptibility data into density data helping in the 3D modelling of the gravimetric signal when density data from rock samples are scarce. Given the large amount of AMS studies worldwide, together with the quickness and cost-effectiveness of susceptibility measurements with portable devices, this methodology allows densifying and homogenizing the petrophysical data when modelling granite rock volumes based on both magnetic and gravimetric signal.</p>