A Fast ANN Trained Solver Enables Real-Time Radial Inversion of Dielectric Dispersion Data & Accurate Estimate of Reserves in Challenging Environments

Dielectric dispersion measurements are increasingly used by petrophysicists to reduce uncertainty in their hydrocarbon saturation analysis, and subsequent reserves estimation, especially when encountered with challenging environments. Some of these challenges are related to variable or unknown formation water salinity and/or a changing rock texture which is a common attribute of carbonate reservoirs found in the Middle East. A new multi-frequency, multi-spacing dielectric logging service, utilizes a sensor array scheme which provides wave attenuation and phase difference measurements at multiple depths of investigation up to 8 inches inside the formation. The improvement in depth of investigation provides a better measurement of true formation properties, however, also provides a higher likelihood of measuring radial heterogeneity due to spatially variable shallow mud-filtrate invasion. Meaningful petrophysical interpretation requires an accurate electromagnetic (EM) inversion, which accommodates this heterogeneity, while converting raw tool measurements to true formation dielectric properties. Forward modeling solvers are typically beset with a slow processing speed precluding use of complex, albeit representative, formation petrophysical models. An artificial neural network (ANN) has been trained to significantly speed up the forward solver, thus leading to implementation and real-time execution of a complex multi-layer radial inversion algorithm. The paper describes, in detail, the development, training and validation of both the ANN network and the inversion algorithm. The presented algorithm and ANN inversion has shown ability to accurately resolve mud filtrate invasion profile as well as the true formation properties of individual layers. Examples are presented which demonstrate that comprehensive, multi-frequency, multi-array, EM data sets are inverted efficiently for dis-similar dielectric properties of both invaded and non-invaded formation layers around the wellbore. The results are further utilized for accurate hydrocarbon quantification otherwise not achieved by conventional resistivity based saturation techniques. This paper presents the development of a new EM inversion algorithm and an artificial neural network (ANN) trained to significantly speed up the solution of this algorithm. This approach leads to a fast turnaround for an accurate petrophysical analysis, reserves estimate and completion decisions.

Inversion-based Interpretation of Borehole Spontaneous Potential Measurements for Accurate Estimation of Water Resistivity in the Presence of Shoulder-Bed and Mud-Filtrate Invasion Effects

Electrical resistivity of formation water is a fundamental property used to quantify in situ water quality for human consumption or for assessment of hydrocarbon pore volume. Resistivity interpretation methods commonly used to quantify the electrical resistivity of formation water invoke rock porosity and fitting parameters that require additional and independent core measurements. Alternatively, the spontaneous potential (SP) log can be used to calculate water resistivity without knowledge of rock porosity in wells drilled with water-based mud. In combination with resistivity and gamma-ray logs, SP logs can be used to estimate water quality, apparent volumetric concentration of shale, and for qualitative assessments of permeability. However, SP logs often exhibit both shoulder-bed and mud-filtration effects; these effects need to be mitigated before using SP logs for calculation of water resistivity. We develop a new inversion-based method to simultaneously mitigate shoulder-bed and mud-filtrate invasion effects present in SP logs via fast numerical simulations based on Green functions. The interpretation method is implemented on SP logs acquired across aquifers with various degrees of complexity using noisy synthetic and field measurements to estimate equivalent NaCl concentration, radius of mud-filtrate invasion, and sodium macroscopic transport number. Interpretation results compare well to those obtained from resistivity and nuclear logs, provide estimates of uncertainty, and can incorporate a priori knowledge of aquifer petrophysical properties in the estimation.

Geochemical Techniques to Detect Sources of Fluids in Highly Pressured Casing-Casing Annuli CCA

The buildup of high casing-casing annulus (CCA) pressure compromises the well integrity and can lead to serious incidents if left untreated. Potential sources of water causing the elevated CCA pressure are either trapped water in the cement column or water from a constant feeding source. This study utilizes inorganic geochemical techniques to determine the provenance of CCA produced water as trigger for high pressure in newly drilled wells. Affinities in the hydrochemical (major, minor and trace elements) and stable isotopic (δ2H, δ18O) composition are monitored to identify single fluid types, multi-component mixing and secondary fluid alteration processes. As a proof-of-concept, geochemical fingerprints of CCA produced water from three wells were correlated with potential source candidates, i.e., utilized drilling fluids (mud filtrate, supply water) from the target well site, Early - Late Cretaceous aquifers and Late Jurassic - Late Triassic formation waters from adjacent wells and fields. Geochemical affinities of CCA water with groundwater from an Early Cretaceous aquifer postulate the presence one single horizon for active water inflow. Non-reactive elements (Na, Cl) and environmental isotopes (δ2H, δ18O) were found to be most suited tools for fluid identification. 2H/1H and 18O/16O ratios of supply water and mud filtrate are close to global meteoric water composition, whereas formation waters are enriched in 18O. Elevated SO4 and K concentrations and extreme alkaline conditions for CCA water indicates the occurrence of minor secondary alteration processes, such the contact of inflowing groundwater with cement or fluid mixing with minor portions of KCl additives. The presented technology in this study enables the detection of high CCA pressure and fluid leakages sources, thereby allowing workover engineers to plan for potential remedial actions prior to moving the rig to the affected well; hence significantly reducing operational costs. Appropriate remedial solutions can be prompted for safe well abandonment as well as to resume operation at the earliest time.

Dynamic Drilling Fluid Invasion Petrophysical Modeling and Corrections in the Presence of Gas Reservoirs - Arab Formation, UAE

Drilling fluid (mud) invasion occurs when the liquid component of the fluid (mud filtrate) invades porous and permeable formations caused by the differential pressure between the wellbore and formation fluids. Changes to the fluid distribution near the wellbore region affects logging tool response, especially those with shallow depths of investigation. The Arab formation in UAE exhibits different degrees of invasion primarily observed in the nuclear and resistivity measurements. This study utilizes tool physics, rock properties, logging time information, and drilling fluid properties, to model invasion corrected log responses and estimate accurate petrophysical properties. Drilling mud filtrate invasion is observed significantly in all wells drilled in the Arab formation in UAE, affecting both wireline and LWD logging tools. Most of the pilot vertical wells appear to be at residual saturations near the wellbore, where drilling mud filtrate invaded deep into the formation and the radial zones near the wellbore are expected to be completely flushed by the filtrate. Drilling mud invasion in the laterals appears to happen early during the drilling phase affecting LWD tool as well, and the measurement becomes function of the time after drilled, affecting mostly nuclear measurements (density and neutron). Clear understanding of the mud filtrate invasion is required to obtain valid petrophysical interpretations. To characterize these effects, two invasion indexes are estimated and used as inputs for the petrophysical model. Results are then validated with the use of Nuclear Modeling and Resistivity Inversion by the use of the SNUPAR (McKeon et al, 1988)(Edmundson, H., and Raymer, L.L., 1979)(Wiley, R., and Patchett, J.G., 1990) and UTAPWeLS (Jesus and Carlos, 2009) (Alberto and Carlos, 2010) (Alberto, Carlos and Bill, 2010) (Shaaban, David, and Carlos, 2017) (David, Joaquin and Carlos, 2019). Individual models are created to evaluate pilot vertical wells and horizontal laterals, as well as pure theoretical models are put forward to demonstrate the importance of performing corrections for mud filtrate invasion, showing the differences particularly in the nuclear responses.

Study on Nuclear Magnetic Resonance Logging T2 Spectrum Shape Correction of Sandstone Reservoirs in Oil-Based Mud Wells

The oil-based mud filtrate will invade the formation under the overbalanced pressure during drilling operations. As a result, alterations will occur to the nuclear magnetic resonance (NMR) response characteristics of the original formation, causing the relaxation time of the NMR T2 spectrum of the free fluid part to move towards a slower relaxation time. Consequently, the subsequent interpretation and petrophysical evaluation will be heavily impacted. Therefore, the actual measured T2 spectrum needs to be corrected for invasion. For this reason, considering the low-porosity and low-permeability of sandstone gas formations in the East China Sea as the research object, a new method to correct the incorrect shape of the NMR logging T2 spectrum was proposed in three main steps. First, the differences in the morphology of the NMR logging T2 spectrum between oil-based mud wells and water-based mud wells in adjacent wells were analyzed based on the NMR relaxation mechanism. Second, rocks were divided into four categories according to the pore structure, and the NMR logging T2 spectrum was extracted using the multidimensional matrix method to establish the T2 spectrum of water-based mud wells and oil-based mud wells. Finally, the correctness of the method was verified by two T2 spectrum correction examples of oil-based mud wells in the study area. The results show that the corrected NMR T2 spectrum eliminates the influence of oil-based mud filtrate and improves the accuracy of NMR logging for calculating permeability.

Case Study: Sound-Speed Measurement: Unique Measurement Across All Fluids for In-Situ Properties

Fluid samples collected using either wireline or logging-while-drilling (LWD) formation-testing technology for reservoir fluid characterization have long been accepted as the most representative of reservoir fluid. This, though, comes with a caveat that the collected sample is clean and devoid of any mud-filtrate contamination. With both techniques performed soon after drilling a well, there is always a risk of contaminating the collected fluid with mud filtrate. Toward the goal of reducing this risk, since the early 2000s, technologies have been brought forth to help identify the fluid down hole. There have been multiple developments with sensors for absorbance spectroscopy, fluorescence, fluid resistivity, fluid refractive index, and so on. Each sensor development was targeted toward a specific fluid interaction with the mud filtrate, thereby helping to differentiate the reservoir fluid from the mud filtrate. Downhole sampling conditions can be classified into two broad groups: one case where the reservoir fluid is miscible with the mud filtrate and the other where the reservoir fluid is not miscible with the mud filtrate. The immiscible cases are generally straightforward, since sensors such as absorbance spectroscopy can easily differentiate among oil, water, and gas. In addition, the technique can be used to determine the fractional portion of each phase in the flow. Complications arise when the reservoir fluids happen to be miscible with the mud filtrate system; for example, while sampling reservoir water in the presence of water-based mud filtrate, absorbance spectroscopy by itself is unable to differentiate among the fluids. Table 1 provides generic information about different fluid systems as well as the sensors used to differentiate the fluids. While there are other sources of correlation-based fluid-property information, the basic sensors mentioned are the ones used for correlations. As mentioned, each sensor provides detailed information for specific cases, but only sound speed provides a single-sensor solution for the conditions expected. Sound-Speed (SS) Measurement While acoustic data have long been used for reservoir characterization, data have been used for fluid characterization during downhole sampling for only a decade. Experience has shown that this measurement is sensitive enough to not only differentiate injection water or formation water but also to track and quantify small changes in oil compressibility—an important step in focused sampling. The measurement uses a pulse-echo technique based on the principle that an acoustic signal propagates approximately as a plane wave, and that the speed of sound is based on the distance the pulse travels divided by the time it took to traverse the distance. (SPWLA-2013-FFF). The 10-MHz piezoelectric transducer is mounted onto a machined flat surface on the flowline of RCX (the wireline formation testing tool reservoir characterization instrument) as schematically shown in Fig. 1. The travel path length is the distance between the two internal surfaces of the flowline. The result was a bulk measurement of the speed of sound across all the fluid flowing though the flowline. The only calibration needed is for this path length, which can differ due to slight machining variations. A calibrated sensor was able to differentiate fluids which exhibited sound-speed differences as small as 4.7 m/sec (0.5 msec/ft of sound-speed slowness).

Rapid modeling of borehole measurements of nuclear magnetic resonance via spatial sensitivity functions

Borehole measurements of nuclear magnetic resonance (NMR) are routinely used to estimate in situ rock and fluid properties. Conventional NMR interpretation methods often neglect bed-boundary and layer-thickness effects in the calculation of fluid volumetric concentrations and NMR relaxation-diffusion correlations. Such effects introduce notable spatial averaging of intrinsic rock and fluid properties across thinly bedded formations or in the vicinity of boundaries between layers exhibiting large property contrasts. Forward modeling and inversion methods can mitigate the aforementioned effects and improve the accuracy of true layer properties in the presence of mud-filtrate invasion and borehole environmental effects across spatially complex formations. We have developed a fast and accurate algorithm to simulate borehole NMR measurements using the concept of spatial sensitivity functions (SSFs) that honor NMR physics and incorporate tool, borehole, and formation geometry. Tool sensitivity maps are derived from a 3D multiphysics forward model that couples NMR tool properties, magnetization evolution, and electromagnetic propagation. In addition, a multifluid relaxation model based on Brownstein-Tarr’s equation is introduced to estimate layer NMR porosity decays and relaxation-diffusion correlations from pore-size-dependent rock and fluid properties. The latter model is convolved with the SSFs to reproduce borehole NMR measurements. The results indicate that NMR spatial sensitivity is controlled by porosity, electrical conductivity, excitation pulse duration, and tool geometry. We benchmark and verify the SSF-derived forward approximation against 3D multiphysics simulations for a series of synthetic cases with variable bed thickness and petrophysical properties, and in the presence of mud-filtrate invasion in a vertical well. Results indicate that the approximation can be executed in a few seconds in a central processing unit, by a factor of 1000 times faster than rigorous multiphysics calculations, with maximum root-mean-square errors of 1%.