While traditional mudlogging techniques provide largely qualitative data, the prime objective of Advanced Mud Logging (AML) is to provide quantitative real time measurements in aid of a complete formation evaluation. To achieve this, wellsite mudlogging technologies have been enhanced, and various techniques which historically were limited to laboratories, have been adapted for well site usage. AML well site techniques thus include: (1) high frequency, improved accuracy monitoring of drilling parameters; (2) enhanced cuttings image acquisition and processing; (3) direct measurements on cuttings, including graindensity, spectral GR, NMR, XRD, XRF; and (4) sophisticated mud gas analysis capabilities.We describe the main system components developed and present some results of the first pilot tests done in Saudi Arabia with AML techniques and a dedicated AML unit. Examples in the four areas mentioned above illustrate and confirm the potential of AML. On one special technology test well, different systems, from two different companies, were run in parallel to establish the merits and possible limitations of especially the hydrocarbon analysis systems.One of the most striking examples of the quality of AML is a perfect match between the hydrocarbon fluid composition determined from mud gas returns, and those subsequently obtained from PVT measurements on wireline fluid samples. To achieve this, AML technology developers in the industry advanced across the whole process chain affecting such quantification. First and foremost, improving sample extraction and handling, combined with enhanced calibration procedures, to convert from in situ to surface conditions. Second, in addition to sampling both the return mud flow and the inflow, a more precise tracking of flowrates and system volumes was made possible with modern operating systems. Third, adding a mass spectrometer to the gas chromatograph, improved the final measurement potential. Introduction.Several years ago, in Saudi Aramco, a clear business need emerged for additional petrophysical techniques in cases where traditional formation evaluation technologies were unable to provide all the necessary answers with sufficient certainty. Interpretation of tight gas formations in particular was challenging, because the formation properties typically were right at the edges of the operating envelopes of normal logging tool measurements and interpretation technology. With a perceived potential for AML technologies to aid in several of those challenges, an AML research area was set up. The mission was to expand and improve existing mudlogging technologies, and introduce and develop new ones. The vision had two related, but distinct elements. Firstly, also labeled as "ARCHIE'S DREAM" 1 , a complete, albeit preliminary, as a "first aid", formation evaluation, based solely on AML data, including mineralogy, fluid contacts and fluid characterization, porosity and even saturation, permeability and other parameters normally derived from conventional electric logging and cori...

The formation evaluation of Saudi Arabian reservoirs presents multiple challenges. The complexities encountered include varying mineralogy and mixed lithologies, a wide range of porosities and pore types, hydrocarbon viscosity, and variable formation water salinities.Two-dimensional (2D) analysis of NMR data acquired with simultaneous T1-T2 has proven to be beneficial for the identification and quantification of hydrocarbon-bearing reservoirs and providing valuable information about porosity and reservoir quality.NMR porosity measurements are free from mineralogical effects and, therefore, provide a very good estimate of formation porosity. Moveable and bound fractional fluid porosities from NMR provide additional reservoir information and are used for estimating permeability. Simultaneous T1-T2 acquisition and two dimensional analyses provide graphic 2D identification for the presence of hydrocarbons and hydrocarbon type, as well as a volumetric estimate of near wellbore hydrocarbons independent of formation water resistivity.Results from a simultaneous NMR T1-T2 acquisition are compared to formation tester results. The strong correlation between the NMR predictions and the formation tester results suggests this method is effective in the evaluation of challenging formations and might also be applicable to other reservoirs.

The increasing complexity of today's reservoirs requires a good understanding of a formation's mineralogy to make an accurate petrophysical analysis. This is particularly true in the case of unconventional reservoirs, for which the quantification of both mineralogy and organic carbon content is critical to confidently appraise and develop new prospects.A new spectroscopy tool is being applied to evaluate challenging shale gas reservoirs. The new measurements quantify key mineral-forming elements with higher precision and accuracy than previously possible. The new technology provides a direct determination of total organic carbon (TOC), which is an important parameter in the evaluation of kerogen-rich unconventional reservoirs.Accurate lithology and kerogen volumes ultimately affect the estimation of porosity and free and adsorbed gas saturations, which are critical for evaluating resources and planning for further field development. Mineralogy can also be used in geomechanical models to determine completion quality, design stimulation operations, and specify intervals for perforation.The results obtained show excellent agreement with core data for TOC, elemental concentrations, and mineral abundances. One of the main advantages of computing TOC directly from carbon is that it does not require calibration to core data as do empirical methods based on local correlations that use more indirect measurements such as bulk density, sonicresistivity overlay, or uranium concentration. The robustness of the proposed direct carbon approach is illustrated by comparing it with core and well-established methods for estimating TOC, such as the Schmoker technique.

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In heterogeneous tight sand formations, horizontal wells encounter intervals deposited under varying depositional environments along the lateral portion of the wellbore between landing point and total depth. Horizontal wells in this study were drilled in tight sands deposited in a marine environment where lateral depositional facies changes are common, and hydraulic fracture stimulation is necessary to achieve economic hydrocarbon extraction due to the relatively low permeability of the formation. Without geomechanical logs currently derived from wireline logging, it is not possible to optimize cluster spacing and placement. This step provides necesary information used to optimize completion design, which is crucial to the ultimate productivity of a well. Due to formation heterogeneity, expensive wireline logs must be collected in order to optimize fracture stimulation or else new methods to estimate these logs must be employed. This paper presents a technique to optimize cluster selection for hydraulic fracturing in unconventional tight gas development horizontal wells without wireline logging by leveraging Measure While Drilling (MWD) Gamma Ray logs and surface drilling parameters together with Artificial Intelegence (AI) algorythms to predict density, compressional and shear slowness logs for use in geomechanical evaluation.