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1-19 of 19

Chanh Cao Minh

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Proceedings Papers

Paper presented at the SPWLA 61st Annual Logging Symposium, June 24–July 29, 2020

Paper Number: SPWLA-5067

Abstract

The Gaymard-Poupon (1968) and Segesman-Liu (1971) equations are widely used to correct density-neutron logs for gas/light hydrocarbons effect. The equations assume an "average" gas and an "average" oil, at "average" reservoirs conditions that might not be applicable in all circumstances. Moreover, in the absence of a light hydrocarbon trend on the density-neutron crossplot, no correction is possible. Since time-lapse data contains information about the hydrocarbon properties at reservoir conditions and shows fluid changes with invasion, we propose to use time-lapse data to quantify and auto-correct for the gas effect. The result is an easy-to-use density-neutron crossplot overlay to determine total porosity. The graphical method provides valuable insights about various combination rules of crossplot porosity such as the half density, half neutron rule, which is a special case of the weighted sum rule. We discover that the weighted difference rule gives the residual gas volume. Thus, residual gas saturation from density-neutron can also be estimated. Al Daghar et al. (2013) laid out the general framework of formation evaluation using multi-measurements time-lapse data. In the simple case of two measurements, density and neutron, the measurement space reduces to the familiar density-neutron crossplot. The porosity space becomes the line joining the matrix point to the water point. Since gas has lower density and hydrogen index than water, any data point affected by gas will plot in the North-West corner above the porosity (water) line. The direction (slope) of the gas effect is given by tracing the time-lapse data back to the water line. Two workflows can be used to compute the gas-corrected porosity. The first is to compute the intersection of the data points projected along the gas slope onto the porosity line. The second is to rotate the density-neutron axes perpendicular to the gas slope. Then, gas-corrected porosity can be read directly from the new axis. Since the rotated axes are linear combinations of the original axes, the second workflow readily gives the respective weight factors of the density and neutron logs in the gas-corrected porosity equation. We successfully apply both methods to one gas well in Europe and two gas wells in the Middle East. In all wells, the time-lapse porosity differs from porosities derived from conventional combination rules such as the square root rule, the half density plus half neutron rule, and the two-third density plus one-third neutron rule. We attribute the discrepancies to the gas properties downhole (composition and/or pressure) being different from those used in the rule-of-thumb algorithms. One Middle East well has three time-lapse datasets. This allows us to compare the results of using all 3 datasets (#1 + #2 + #3) versus using only 2 dataset (#1 + #2) and (#1 + #3). Here, #1 denotes the dataset acquired while drilling, #2 is the first dataset after drilling, and #3 is the second dataset after drilling. We conclude that two datasets are sufficient to obtain good results provided there are observable changes in the logs caused by invasion. An additional benefit of obtaining accurate porosity in the presence of gas is the estimation of residual gas saturation S hr . This is done in the European well where we observe reasonable agreement between S hr derived from density-neutron logs and S hr computed from Rxo log via Archie's equation.

Proceedings Papers

Paper presented at the SPWLA 60th Annual Logging Symposium, June 15–19, 2019

Paper Number: SPWLA-2019-FFF

Abstract

ABSTRACT Accurate estimation of oil and gas productivity in development wells is crucial for perforation decisions and planning for future development activity. The production capacity of a well can be described by the productivity index (J), which is mainly determined by the effective permeability to the mobile fluid phase. In exploration wells, J is usually estimated from Drill Stem Tests (DST), which measure the flow rate of the reservoir section isolated for production. In development wells, however, DST's are typically scarce, and hence J must be estimated from well logs. The log-based permeability model, K-Lambda, estimates the absolute permeability (k) from mineral abundances, which in turn are derived from geochemical logs. The model associates a specific surface area ( S 0 ) with each lithology to calculate the permeability from the surface area-to-volume ratio of the rock. In general, S 0 for sand and carbonate are well defined and stable. However, S 0 for clay depends largely on the clay type and varies from reservoir to reservoir. Since clay has the most significant effect on permeability, correctly accounting for its surface area is key to improving the prediction accuracy. This paper describes a workflow to improve J estimation in development wells by calibrating the clay S 0 parameter with fluid mobility, which is estimated from formation pressure pretests. Since the pretest mobility is defined as the effective permeability to the mud filtrate over its viscosity, the pretest effective permeability in water-based mud ( k w ) must first be converted to absolute k before it can be used in the calibration process. The conversion relies on relative permeability ( k rw ) measurements on core samples as (Equation). Once the calibrated K-Lambda permeability log is obtained, we use it to improve J estimation in development wells. The workflow consists of the following steps: Establish a relationship between k and effective permeability to water ( k w ) at irreducible oil saturation ( S or ), using relative permeability measurements on core samples from the exploration (or development) well. Using the relationship in step 1, convert the measured pretest permeability at discrete points from k w to k (assuming water-based mud). Calibrate clay S 0 in the K-Lambda model for each pay sand with the converted k at the pretest points and compute a continuous k log with the calibrated model. Compute the relative permeability logs to water ( k rw ) and oil ( k ro ) from known correlations. Then, calculate the continuous effective permeability to oil ( k 0 ) as k × k ro . Calculate J in the development well from k 0 using the well testing data in exploration wells as a reference. This workflow is demonstrated using formation pressure tests and geochemical logs acquired by LWD tools in an offshore siliciclastic brownfield. The productivity estimation from this workflow shows excellent agreement with actual production data in our case studies.

Proceedings Papers

Paper presented at the SPWLA 60th Annual Logging Symposium, June 15–19, 2019

Paper Number: SPWLA-2019-V

Abstract

ABSTRACT To evaluate formation petrophysical properties, a common methodology is to determine the reservoir porosity, permeability and water saturation through conventional measurements including gamma ray, resistivity, density, and neutron porosity. At least two or three logging tools need to be connected in the bottom hole assembly (BHA) together with a radioactive source. Several interpretation parameters, such as a (tortuosity factor), m (cementation exponent), n (saturation exponent), and formation water resistivity need to be determined through local knowledge or core measurements. In short, we look for alternatives to estimate water saturation (S w ) is without the above constraints. A newly published method allows water saturation to be derived from nuclear magnetic resonance (NMR) transverse relaxation time ( T 2 ) distribution. Because it is independent of the resistivity measurement, it is viewed as a way to address the challenges mentioned above. The workflow builds on recent advancements to extract maximum information from minimal NMR data acquisition, such as factor analysis, a statistical method to determine various T 2 cutoffs, and fluids substitution, a method to replace all hydrocarbons with water in T 2 distribution. It is summarized below: Identify fluids T 2 cutoffs from factor analysis of the T 2 distribution. Perform T 2 fluid substitution to get the 100% water T 2 distribution. Establish T 2 log-mean, T2LM of 100% water ( T 2 LM 100% water ) and T2LM of the hydrocarbon ( T2LM hc ), then, calculate S w by interpolating the measured T2LM between the 1 water and hydrocarbon T2LM endpoints. Using the proposed workflow, we conducted a case study on two wells in Bohai Bay, China. The target reservoirs are heterogeneous shaly sand formations that produce light oil. Both wells have logging-while-drilling (LWD) triple combo, NMR and core data in the main reservoir intervals. Overall, S w derived from T 2 shows good agreement with S w calculated from Archie equation in both wells. The feasibility of the proposed NMR method is well demonstrated in the study field. By replacing neutron-density tools with NMR, the operator is able to eliminate radiation hazard. With S w computed from T 2 distribution, the interpreter can corroborate resistivity-based interpretation or provide an independent reference when conventional interpretation is not conclusive.

Proceedings Papers

Maria Cecilia Bravo, Mirza Hassan Baig, Artur Kotwicki, Nicolas Gueze, Mathias Horstmann, Yon Blanco, Chanh Cao Minh, Julian Pop, Scott Paul

Paper presented at the SPWLA 60th Annual Logging Symposium, June 15–19, 2019

Paper Number: SPWLA-2019-HHHHH

Abstract

ABSTRACT Identification of hydrocarbon type and fluid contacts and assessing production potential are vital to successfully develop infill reserves. Geosteering decisions must be made in real time to achieve the optimal well path that would drain remaining reserves. Thus, highly flexible data acquisition strategies while drilling are needed to be able to adapt to unpredictable reservoir structures, hydrocarbon saturation, and variable fluid contacts. Logging-while-drilling (LWD) technology has enabled a step change in well construction from geometric trajectories to those actively steered by formation and fluid characteristics in real time. Depending on geosteering challenges, an LWD bottomhole assembly (BHA) can include tools for deep directional resistivity (DDR), standard petrophysical logs, LWD spectroscopy, nuclear magnetic resonance (NMR), formation pressure, advanced downhole fluid analysis (DFA), and surface mud log gas. In recent years, DDR measurements have been widely used for their deep depth of investigation to map reservoirs and geosteer the well within the hydrocarbon column. DDR measurements use the resistivity contrast of hydrocarbons to conductive water to map and delineate the top and bottom of the hydrocarbon-bearing zones. However, it does not always differentiate between hydrocarbons as gas or oil because they share similar resistivity signatures. It continuously maps hydrocarbon-water-contact but rarely maps a gas-oil contact (GOC), valuable to be known, since usually to drain remaining oil reserves the well must be placed below the GOC and at a safe distance from the oil-water contact (OWC). Leveraging the short time-after-bit and less exposure to drilling fluid invasion, two measurements have become particularly useful to differentiate gas from oil: advanced downhole fluid analysis and real-time interpretation of petrophysical log data. In this paper, we discuss an infill reserves development case study of the Boa field in the North Sea where it was desired to place four lateral wells within a thin oil rim. Fluids were continuously mapped along the wellbore trajectory as gas, oil, light oil, and free and irreducible water by using petrophysical logs in real time. Fluid typing from downhole optical spectrometry provided validation points for the petrophysical interpretation. Software and data transmission technologies were utilized to create an integrated answer product of continuous near- and far-wellbore fluid characterization for well-considered geosteering decisions and optimal well placement.

Proceedings Papers

Paper presented at the SPWLA 59th Annual Logging Symposium, June 2–6, 2018

Paper Number: SPWLA-2018-CCC

Abstract

ABSTRACT We used conventional logging while drilling (LWD) nuclear magnetic resonance (NMR) transverse relaxation time (T2) data to estimate virgin zone water saturation ( Sw ) in environments challenging to conventional resistivity based evaluation: such as fresh water, high shale content, varying or unknown water salinity, and uncertain Archie parameters (a, m, n). It is important to stress the use of while drilling data to minimize the effect of invasion, although this can be corrected. The technique relies on the T2 log-mean ( T2lm ) equation written for a binary fluid system of water ( T2lm w ) and hydrocarbon ( T2lm hc ): T2lm=T2lm w Sw .T2lm h (1− Sw) . It is trivial to expand the equation to accommodate more fluids such as filtrate or bound water. The water endpoint, T2lm w , is obtained from the fluids-substituted 100% water endpoint corrected for partial saturation. The hydrocarbon endpoint, T2lm hc , if unknown, can be estimated from the difference between the original T2 distribution and the 100% water T2 distribution after fluids substitution. The salient point is that computing Sw from the T2lm equation is always possible unless the fluids endpoints are identical, in contrast to computing saturations from the fluids volumes obtained by partitioning the T2 distribution. For example, we have found that Sw can be estimated reliably even when T2lm w and T2lm hc are in the same decade of T2 relaxation time, while their respective T2 distributions are inseparable. Moreover, the technique is visual and straightforward to quality control, i.e. Sw is the weighted distance of the log data point with respect to the water endpoint and the hydrocarbon endpoint in the logarithmic space. The first example is laboratory data of a sandstone, first saturated with water, then de-saturated with kerosene at fixed saturation steps. The controlled measurements allow the explanation of the algorithms used in the Sw from NMR T2 workflow. Several field examples demonstrate the cases of: water relaxing faster than hydrocarbon ( T2lm w < T2lm hc ) such as conventional reservoirs with light oil, water relaxing slowe r than hydrocarbon ( T2lm w > T2lm hc ) such as unconventional reservoirs or heavy oil reservoirs, varying hydrocarbons such as reservoirs with a gas cap above oils with various API gravity, and varying water salinity such as waterflooded reservoirs in mature fields. In the examples, we compare Sw determined from NMR T2 with Sw determined from deep resistivity, pulsed neutron capture sigma (that is independent of a, m, n) and joint-inversion of resistivity-sigma (that is used in the case of unknown water salinity) to show the viability of the new technique when conventional approaches fail to deliver reliable answers.

Proceedings Papers

Nicholas Heaton, Douglas Hupp, Chanh Cao Minh, Vikas Jain, Doruk Sargin, Alexandre Maciel, Olutunde Akindipe, Michael Werner

Paper presented at the SPWLA 59th Annual Logging Symposium, June 2–6, 2018

Paper Number: SPWLA-2018-SSSS

Abstract

ABSTRACT Nuclear Magnetic Resonance (NMR) is now a firmly established formation evaluation service available in logging while drilling (LWD) mode. Key NMR products including lithology-independent porosity, fluids, and producibility answers are broadly accepted in the industry. Existing commercial services focus either on T 2 or T 1 acquisition modes, each of which has its own advantages and disadvantages. This paper presents initial results of a new generation LWD NMR service for slim holes which offers the benefits of both T 2 and T 1 measurements. The new slim hole NMR technology introduced in this paper has been designed with service efficiency as a primary objective, along with hardware reliability, data quality, and answer products objectives. Using novel acquisition electronics and an optimized magnet configuration, the sensor is highly tolerant to variations in borehole salinity and operates with a short echo spacing. The new tool delivers simultaneous T 1 and T 2 distributions while drilling, along with all derived NMR answer products in real time while the BHA is either rotating or sliding. The simultaneous T 1 - T 2 capability allows good definition of both slow and fast-relaxing components, enabling more accurate differentiation of different fluid environments. Because of the high quality raw data and an efficient T 1 - T 2 acquisition scheme, NMR answers are delivered at high resolution even at moderate drilling speeds, with formation features in the order of 1 ft thick being accurately identified. A common processing workflow ensures that all real-time answers are equivalent to post-acquisition recorded mode products. The potential effects of lateral motion, a concern for all LWD NMR tools, are largely mitigated in the new slim hole tool through optimization of the magnet and antenna and by adopting a short echo spacing for data acquisition. The standard acquisition of T 1 data also helps to minimize the risk of motion effects compared with T 2 -only measurements. In addition, a workflow has been developed which integrates NMR physics with drilling dynamics so that BHA configurations may be optimized to minimize motional modes at the NMR sensor, as part of the overall job planning exercise. Results are presented from two field tests with prototype tools. The first was in a vertical hole at a test facility. Multiple runs were acquired while drilling both with and without a motor and in washdown mode. The second field test was performed in an operator well on the North Slope, Alaska. Here, the new NMR tool was run in a horizontal 6.75in hole drilled through a sand-shale formation with the primary objective of identifying permeable pay zones in real time as targets for subsequent wireline fluid sampling. Additionally, this data set was used to understand the complex fluid distributions and properties within an isolated fault block.

Proceedings Papers

Paper presented at the SPWLA 59th Annual Logging Symposium, June 2–6, 2018

Paper Number: SPWLA-2018-RRRR

Abstract

ABSTRACT In complex reservoirs, variations in pore geometrical attributes define distinct hydraulic units, which must be accounted for in a permeability prediction model. In this paper, we study an offshore siliciclastic brownfield where the reservoirs are highly heterogeneous with matrix permeability ranging from 0.1 mD to over 1 Darcy. Logging-While-Drilling (LWD) triple combo and NMR T2 relaxation data were acquired while drilling. Core samples were taken in the target sands and conventional core analysis was performed. We characterize the pore geometry variations by classifying core samples into a number of petrophysical rock types using a novel scheme. The novel classification is done by applying carefully designed cutoffs to the pore throat radii of the core samples and is propagated to the entire well with an artificial neural network. For each rock type, the parameters in the Timur-Coates permeability equation are calibrated with core measurements and a continuous permeability is computed using the calibrated parameters. The workflow consists of these detailed steps: Compute pore throat radius from core porosity and permeability using established equations. Classify the samples by defining a set of pore throat radius cutoffs based on statistical analysis, modified Lorenz plot and porosity vs. permeability (poroperm) crossplot. For each rock type, calibrate the T2 cutoff value and the multiplier (the A value) in the Timur-Coates equation by minimizing the difference between measured and predicted permeabilities. With supervised machine learning, learn rock type classification from cored intervals and propagate the classification to un-cored intervals using selected log curves. Compute a continuous Timur-Coates permeability for the entire well using the calibrated parameters pertinent to each petrophysical rock type. The proposed workflow significantly improves the match between core and predicted permeability, as demonstrated in two development wells. By comparison, a conventional permeability model is unable to capture the permeability variations seen in the core data. An additional deliverable is a calibrated T2 cutoff curve that varies with the rock types. The variable T2 cutoffs can be applied to an offset well containing the same rock types to improve the accuracy of bound fluid volume (BFV) estimation from the T2 distribution.

Proceedings Papers

Paper presented at the SPWLA 58th Annual Logging Symposium, June 17–21, 2017

Paper Number: SPWLA-2017-UU

Abstract

ABSTRACT We present a new method to derive continuous reservoir fluids properties (saturation, salinity, density and hydrogen index) in a complex siliciclastic brownfield. The complexity of our study field lies in the uncertainty of formation salinity, as the water-flooded sands contain an unknown mixture of the connate brine and injected water. In such environments, one cannot simply assume a fixed salinity value when calculating saturation logs with equations that rely on a good knowledge of salinity. Formation evaluation is further complicated by low resistivity contrast between wet and pay sands, where high volume of salty irreducible water lowers resistivity in hydrocarbon-bearing sands. In this field, water production is a big concern for the operator. They would like to gain better understanding of the water flood encroachment to make smarter development plans in the future. To achieve this goal, they acquired advanced LWD logs in a number of development wells to characterize reservoir fluids. The use of LWD logs ensures that invasion of the drilling fluid into the reservoir sands is minimal. Thermal neutron capture cross-section (Sigma) is sensitive to chlorine in the reservoir fluids and rocks and can be used to distinguish between water and hydrocarbon in a salty water environment. Since both Sigma and resistivity are dictated by water saturation (S w ) and salinity together, we can use these two measurements to simultaneously solve for S w and salinity at each depth in a nonlinear least squares inversion routine. The resistivity-sigma workflow assumes total porosity is known but does not require a priori knowledge of salinity and outputs a continuous S w and water salinity log that best honor the input Sigma and resistivity logs.

Proceedings Papers

Paper presented at the SPWLA 57th Annual Logging Symposium, June 25–29, 2016

Paper Number: SPWLA-2016-X

Abstract

Abstract NMR T2 logs respond to both pore size distribution and fluid properties. The presence of more than one fluid can complicate interpretation due to the overprint of the fluids on the pore size information. For many interpretation techniques, including core-based rock typing applications, the response must be transformed to that of a water-filled formation. Further, NMR logs acquired while drilling can look very different to those acquired later, either while wiping with the same logging-while-drilling (LWD) tool used during drilling or on a later wireline-conveyed pass. The difference in the T2 logs is generally due to mud filtrate invasion. Water-based mud (WBM) filtrate invasion into a hydrocarbon zone or oil-based mud (OBM) filtrate invasion into a water zone can both cause additional fluid-related complications. In these circumstances, fluid substitution is performed on the NMR logs in which the hydrocarbon response is replaced by water response. This paper details the workflow first proposed by Shell (Volokitin et al., 1999, 2001), enhanced by NMR factor analysis (Jain et al., 2013) to determine the fluid-related bin porosities and T2 cutoffs. A step-by-step workflow is provided allowing petrophysicists to use this technique in their daily work. The fluid substitution process is illustrated through several examples. In the first example, laboratory T2 measurements were acquired on a core first saturated with water, then with hydrocarbon. The fluid substitution applied to the hydrocarbon-saturated T2 log successfully restores the T2 log as measured on the water-saturated core. The second example is a case of drill & wipe pass LWD NMR logs acquired across an oil-water contact in a formation drilled with OBM. The wipe pass logs look vastly different to the drill pass logs due to invasion. Once the two logs are transformed to water-filled response by substituting the hydrocarbon and OBM filtrate with water, the drill & wipe pass NMR logs look the same and yield the same answers. The third example demonstrates the impact of gas substitution. Before substituting the gas response, it must be corrected for hydrogen index and incomplete polarization effects with the help of other logs. This example shows a formation with both a gas-oil contact and oil-water contact drilled with OBM. The T2 distribution in the water zone serves as a reference to quality control the fluid substitution in the oil and gas zones. The fourth example displays heavy oil substitution. If all the oil components are measurable by NMR, the heavy oil response can be substituted even though its T2 spectrum resides in the bound fluid part of the total spectrum due its fast relaxation time. The permeability and irreducible water saturation must first be estimated using other information before the substitution. These results suggest that fluid substitution is essential to understand and compare NMR logs across the same reservoir at different time in the drilling / fluid invasion process. Fluid substitution to obtain a water-filled response provides corrected pore size distribution and enhanced reservoir rock quality evaluation.

Proceedings Papers

Chanh Cao Minh, Steve Crary, Philip M. Singer, Andrea Valori, Nate Bachman, Gabor Hursan, Shouxiang Ma, Ali Belowi, Ghazi Kraishan

Paper presented at the SPWLA 56th Annual Logging Symposium, July 18–22, 2015

Paper Number: SPWLA-2015-III

Abstract

Abstract Reservoir wettability is a critical parameter affecting hydrocarbon distribution within and recovery from reservoir rocks. The sensitivity of nuclear magnetic resonance (NMR) responses to rock wettability has been demonstrated in a number of publications. These publications suggest that wettability can be determined in the laboratory from NMR T 2 relaxation measurements, obtained in cores after proper cleaning, re-saturation, and aging with reservoir fluids. Wettability changes may be noticed on logging measurements as a downward shift of the oil peak in the T 2 spectrum from the bulk T 2 response of live oils. The main practical obstacle in the T 2 shift-based evaluation of wettability is the poor separation of oil and water peaks in the T 2 spectrum. The bulk T 2 of live oils must be measured and the core sample must be perfectly cleaned to quantify the NMR surface relaxation effect. We demonstrate an improved method based on two-dimensional mapping of NMR diffusion vs. T 2 with two principal advantages. First, the separation between the oil and water signals is greatly improved compared with the T 2 -based approach. Second, key properties such as tortuosity (represented by the Archie cementation exponent m ) and effective surface relaxivity can be inferred from the two-dimensional NMR maps using restricted diffusion models. The wettability index and the rock relaxivity can then be estimated from the effective surface relaxivities. These results are based on a single-step NMR measurement on fresh-state (or "as received") plugs cored with water-base muds containing no surfactants and that should be available days after the cores are recovered. A wettability index using this new NMR method was obtained for carbonate samples from Middle East reservoirs. A strong correlation coefficient of R 2 = 0.7 is observed between this new NMR approach and the standard, more time-consuming methods such as the U.S. Bureau of Mines technique. A sensitivity study of the NMR wettability index versus signal-to-noise ratio is performed on the core data, to assess the feasibility of this new technique down hole. The results suggest that it is possible to obtain reservoir wettability using downhole NMR measurements under appropriate conditions and provided sufficient signal-to-noise is obtained.

Proceedings Papers

Ghazi M. Kraishan, Ali R. Al-Belowi, Zulkifly B. Ab Rahim, Saudi Aramco, Kais Gzara, Chanh Cao Minh, Vikas Jain, Patrick A. Hibler

Paper presented at the SPWLA 55th Annual Logging Symposium, May 18–22, 2014

Paper Number: SPWLA-2014-C

Abstract

Abstract One of the challenges in evaluating mature reservoirs is the uncertainty introduced by pore fluids with unknown or varying petrophysical properties, such as formation water salinity or hydrocarbon gravity. Even though the direct in-situ measurement of these fundamental formation properties using logging devices still eludes the industry, there are a number of recently developed workflows to improve formation evaluation in such reservoirs containing variable or unknown water salinity. One such workflow is based on inversions of formation resistivity and capture cross-section (Sigma) measurements to solve simultaneously for water salinity and saturation. This methodology, however, still requires the knowledge of some petrophysical parameters or properties of the reservoir, such as Archie parameters ( m and n ) and constituent sigma end-points ( Σ mat and Σ hc ), that may not be well known or constant throughout the reservoir. In this paper, a methodology is proposed which uses the geodesic transform of Logging While Drilling (LWD) time-lapse measurements to circumvent the sensitivity of the petrophysical evaluation to various reservoir fluid properties. Intuitively it should be seen that the differential analysis of time-lapsed data will eliminate the static (unchanging) matrix dependency. The non-trivial task is to demonstrate how a fluid property such as variable water salinity can be determined without the resistivity log, thereby eliminating the need to characterize the Archie parameters. Likewise, it will be shown that a generalization of the methodology can allow for the identification of basic hydrocarbon types (gas, light oil, heavy oil and "tar") without the prior knowledge of reservoir hydrocarbon parameters. Application of this technique was tested on data from one well in Saudi Arabia with complex carbonate mineralogy. The field in which the well is located has undergone extensive water-flooding, a process which has precluded the accurate parameterization of reservoir water salinity. The saturation results from this exercise indicate that some of the multiple reservoirs have been depleted to different degrees leading to newly established fluid contacts. The salinity results show that some reservoirs have mixed salinity while others do not, implying preferential flood water advancements. Laboratory analyses of fluid samples taken with a wireline sampling tool have confirmed the results of this evaluation.

Proceedings Papers

Marie-Laure Mauborgne, Franç oise Allioli, Chanh Cao Minh, Roger Griffiths, Carlos Maeso, Nicole Reichel, Christian Stoller, Doug Murray, Hendrayadi Prabawa, Mostafa Haggag, Ahmed AlKhoori

Paper presented at the SPWLA 54th Annual Logging Symposium, June 22–26, 2013

Paper Number: SPWLA-2013-III

Abstract

Abstract Following the implementation of pulsed neutron generator (PNG) technology in logging-while-drilling (LWD) tools, the measurement of formation sigma (Σ, thermal neutron capture cross section) was introduced as a measurement used for water saturation evaluation in saline water environments. Sigma has the advantage of providing saturation independently of resistivity measurements and empirical exponents such as Archie's m and n. This makes saturation evaluation using formation sigma particularly interesting in carbonates and thinly layered formations. The first-generation LWD sigma is a single-depth-of-investigation measurement, which is often sufficient for evaluation of the uninvaded formation properties, as invasion is generally so shallow as to have negligible effect on LWD data acquired while drilling. The latest LWD service combines a suite of gamma ray and neutron detectors associated with the PNG to provide multi-depth-of-investigation (MDOI) formation sigma for shallow invasion identification and measurement quality control. The multi-depth analysis also provides sufficient information to invert for undisturbed formation sigma (Σ t ), invaded formation sigma (Σ xo ), and the invasion radius ( r i ). Comparisons with wireline sigma measurements in both carbonate and clastic reservoirs drilled with water-based mud and oil-based mud show the versatility of the MDOI sigma measurements in identifying permeable zones in difficult environments and addressing the perennial question of whether the conventional single sigma measurement represents the undisturbed formation property. This paper presents MDOI sigma characterization modeling and physical measurements, along with associated environmental corrections and inversion results. Field examples of the application of the measurements and their inversion to extract undisturbed formation properties are shown.

Proceedings Papers

Paper presented at the SPWLA 54th Annual Logging Symposium, June 22–26, 2013

Paper Number: SPWLA-2013-O

Abstract

Abstract In logging, the time dimension often eludes our attention. For instance, it is common to acquire logging-while-drilling (LWD) data in a single pass. The time dimension is frequently ignored, even though it is known that invasion and borehole degradation effects become more pronounced with increasing time after the formation has been drilled. The result of such "static snapshot" thinking is that multiple LWD data acquisition passes are not performed. However, recent advances in the analysis of LWD time-lapse data have revealed a number of important and unique applications. The optimal method to understand reservoir's producibility is to study the nature and movement of the fluids while the fluids are moving. As such, a single snapshot of the formation is insufficient. Since drilling fluid filtrate invasion sets the reservoir fluids in motion, and time-lapse measurements provide a sequence of snapshots of the reservoir at different times during this process, the opportunity arises to use time-lapse data to separate the matrix effect from the true porosity determination (once true porosity is determined, permeability can then be estimated, and hence reservoir producibility). A much more difficult task is to eliminate the fluid effect because 1) the fluid types are unknown, 2) the fluid properties are unknown, and 3) the fluids are mixtures of mud filtrate, formation water and hydrocarbon in unknown proportions. This paper shows how fluids can be identified and their effect eliminated using time-lapse data, and how valuable information can be extracted from LWD time-lapse data which may only show small changes between passes. These small changes, which are often disregarded or overlooked, can make a big difference in understanding complex fluids.

Proceedings Papers

Paper presented at the SPWLA 54th Annual Logging Symposium, June 22–26, 2013

Paper Number: SPWLA-2013-TT

Abstract

Abstract A novel technique, based on "exploratory factor analysis", for NMR logging measurements provides improved accuracy and efficiency in determining poro-fluid distributions and associated porosities in clastic and carbonate reservoirs. The technique addresses questions concerning 1) how many formation components the T 2 distribution truly represents; 2) the T 2 limits of these components; and 3) the underlying pore size distribution and fluid types affecting bound/free fluid T2 cutoff, poro-fluid facies classification, and capillary-height conversion. An automated workflow is followed to identify the dominant modes/peaks ("factors") in a T 2 distribution and repeated patterns/sequences ("fluid facies") using extracted factor volumes in a T 2 depth log. The technique was successfully applied to a siliciclastic reservoir in West Africa and a carbonate reservoir in Brazil.

Proceedings Papers

Chanh Cao Minh, Francois Jaffuel, Yannick Poirier, Shahid Azizul Haq, Mirza Hassan Baig, Claire Jacob

Paper presented at the SPWLA 52nd Annual Logging Symposium, May 14–18, 2011

Paper Number: SPWLA-2011-JJJ

Abstract

ABSTRACT: In West Africa deepwater fields, most reservoirs have very little clay content, with high porosity and permeability as indicated by well logs. Yet in some wells, wireline formation testers (WFT) give dry tests or very low mobility values that are inconsistent with the known reservoir characteristics. Multi-depth of investigation (MDOI) NMR logs show that the culprit is formation damage by mud fines (solid additives) invasion a few inches deep into the formation. In such a case, the alteration is deep enough to impede fluid flow in the vicinity of the probe, but not deep enough to affect conventional density-neutron measurements that read deeper into the formation. To quantify continuously the near-wellbore damage, we use the radial logs of NMR permeability to derive a "skin" log following Hawkins' formulation. The calculation is computed recursively for successive borehole diameters defined by the NMR increasing DOIs. Formation damage evolution with time is also highlighted in a time-lapsed MDOI NMR example. A 2D-NMR example of fines invasion in a gas-bearing formation shows the complexity of the interpretation when multiple fluids exist (fines, OBM filtrate, water and gas). INTRODUCTION Solid fines invasion affecting NMR logs has been reported by Nascimento and Denicol (1999). A typical example is shown in Fig. 1. Whole mud and fines invasion mechanisms are depicted by the cartoon in Fig. 2. Mud solid particles plug the near wellbore formation and might form an internal mud cake. This is referred to as "fines-invaded" and "damaged zone" in this paper, and is different from other definition of the damaged zone as the zone invaded by mud filtrate. Consequently, the radial extent of the damaged zone caused by whole mud/fines invasion is on the order of inches and not several feet as is the case with the radius of invasion.

Proceedings Papers

Keli Sun, Dzevat Omeragic, Chanh Cao Minh, John Rasmus, Jian Yang, Andrei Davydychev, Tarek Habashy, Roger Griffiths, Graham Reaper, Qiming Li

Paper presented at the SPWLA 51st Annual Logging Symposium, June 19–23, 2010

Paper Number: SPWLA-2010-26011

Abstract

ABSTRACT: Although the directional sensitivity and deep investigation depths of directional logging-whiledrilling (LWD) resistivity tools have led to their wide use in detecting bed boundaries for well placement, their multicomponent electromagnetic (EM) measurements also have important applications in formation evaluation. An area of current interest is the evaluation of resistivity anisotropy and formation dip in low-angle wells to better quantify hydrocarbon in place. We present a multistep inversion-based workflow for the interpretation of resistivity anisotropy and formation dip from the directional EM measurements. A 1D parametric inversion is used to construct a layer-cake, transversely isotropic formation model that has outputs of horizontal and vertical resistivities ( Rh and Rv ), formation dip, and layer thicknesses. The procedure takes advantage of predominant sensitivities of different groups of measurements to various formation parameters. After identifying boundary positions, we first invert Rh only from the standard resistivity logs and then add Rv and dip to the inversion model successively, each time incorporating a different group of measurements in the inversion. This significantly improves the robustness of the inversion. We also develop a method of assigning confidence levels to the inversion results for log quality control (LQC), using data misfits and the rate of dip change. The workflow can be used both to process recorded-mode data and to perform real-time interpretation, while drilling, from a subset of input channels. In addition, the algorithm can be applied to conventional LWD resistivity logs to improve their vertical resolution in low-angle wells and to extract Rh and Rv in high-angle wells. The inversion algorithm has been validated, first with synthetic cases constructed from field logs and then with field data in vertical and deviated wells. The examples show that resistivity anisotropy and dip information can be consistently determined from the input logs when the model is appropriate.

Proceedings Papers

Chanh Cao Minh, Jean Baptiste Clavaud, Padmanabhan Sundararaman, Serge Froment, Emmanuel Caroli, Olivier Billon, Graham Davis, Richard Fairbairn

Paper presented at the SPWLA 48th Annual Logging Symposium, June 3–6, 2007

Paper Number: SPWLA-2007-MM

Abstract

Abstract Laminated sand-shale models with anisotropic shales have been discussed extensively. The interpretation methods are written in elaborate mathematical equations. However, there has not been a clear procedure to determine key parameters such as shale anisotropy, to guide the choice of multiple solutions, and more important, to recognize the circumstances in which a solution is robust or sensitive to errors. This paper explains the analytical solutions through interactive crossplots. A graphical crossplot gives better insights into petrophysics than a set of equations, while interactivity allows instant visualization of the solutions, thereby helping the petrophysicist in the most effective way. The objectives of the graphical analysis are 1) to determine the shale anisotropy parameters and whether it is necessary to create multiple zones, 2) to define the region boundaries where each analytical solution is applicable, 3) to illustrate the effect of data outliers on the results, and 4) to quickly perform sensitivity tests. Pay region and non-pay region are subsequently defined, which allows a global assessment of the hydrocarbon potential of the thin-beds sections directly from the chart. Examples are shown in which the shale anisotropy is the same or greater than the thin-bedded sections anisotropy. At first sight, it seems hopeless to analyze such a thin-bedded zone. Another example shows the need to define multiple anisotropic shales. The difficulty is to determine the number of shale points and their respective anisotropy. Another example shows no 100% shale point to pick parameters. The graphical ethod allows successful interpretation of the resistivity anisotropy data in these difficult conditions. The results are corroborated with imaging logs, nuclear magnetic resonance results and core data. It is also found that the graphical analysis is a valuable tool to QC the resistivity anisotropy data. Introduction Klein et al. were first to lay out the interpretation framework of electrically anisotropic reservoirs, i.e. thin sand-shale laminations in 1997. This was adapted by Shray et al. and Fanini et al. in 2001 with the addition of other logs. However, the basic shortcoming of their models was the assumption of isotropic shales that seldom exist in reservoirs under normal compaction. The effect of anisotropic shales was treated in Clavaud et al .'s publication in 2005. Anisotropic shales are described by two independent parameters, R shh and R shv , representing the shale horizontal and vertical resistivity, respectively. However, introducing one more unknown, R shv , to an already under-balanced set of R v , R h equations further complicates the algebraic solutions. Erroneous anisotropic shale parameters can either lead to optimistic or pessimistic results with few means to verify. Here we emphasize the graphical solutions of R v , R h equations adjusted for shale anisotropy. Just as one picks a shale point from a Density-Neutron crossplot and visually has a feel for the shale volume, likewise it can be shown that one can pick an anisotropic shale point and visually have a feel about the shale volume, the sand layer resistivity, and its corresponding water saturation. The graphical method allows the petrophysicist to choose parameters, perform QC and quickly assess the potential of the thin-beds reservoirs with just one look at the crossplot data.

Proceedings Papers

Paper presented at the SPWLA 47th Annual Logging Symposium, June 4–7, 2006

Paper Number: SPWLA-2006-CC

Abstract

The ?Lake? field is located in the Congo basin and holds several oil reservoirs of Albian to Cenomanian age in a mixed lithology of carbonates and sandstones. The R1 reservoir, subject of this presentation, corresponds to a littoral domain varying between

Proceedings Papers

Paper presented at the SPWLA 39th Annual Logging Symposium, May 26–28, 1998

Paper Number: SPWLA-1998-II

Abstract

ABSTRACT A new well logging method for evaluating gas-bearing reservoirs has been developed. The method combines total porosity from the CMR Combinable Magnetic Resonance tool (TCMR) and density log-derived porosity (DPHI). It is based on new gas equations derived recently by Freedman (1997) and will be referred to as the Density-Magnetic Resonance (DMR) method. The equations and the method are also applicable to reservoirs with gas condensate or light oil near the wellbore. The method provides new petrophysical equations for (1) gas-corrected total formation porosity and (2) flushed-zone gas saturation. This paper describes the method in detail and applies it to the evaluation of field data. The DMR gas-corrected total porosity (DMRP) is a new formation evaluation parameter. DMRP from the new method can be used in volumetric calculations to provide more accurate reservoir volume estimates than previously possible. Also, more accurate formation gas saturations can be computed when using gas-corrected total porosity in conjunction with deep-reading resistivity tools. The improved gas saturations and reservoir volumes provide better estimates of gas reserves. Gas-corrected total porosity can also be used in conjunction with the Coates-Timur equation to provide better permeability estimates in gas-bearing zones. Attractive features of the DMR method include (1) faster logging in many environments because the gas polarization can be minimized, (2) robust gas evaluation because the separation in porosity is accentuated by the opposite effect of gas on the DPHI and NMR logs, (3) total porosity corrected for gas effect and (4) simple interpretation analogous to the familiar neutron-density gas detection. The equations for gas-corrected total porosity and flushed-zone gas saturation are derived from the petrophysical response equations for total NMR porosity and formation bulk density. In gas-bearing reservoirs, gas-corrected total porosity is shown to obey a simple approximate equation that can be used to make a semi-quantitative estimate of DMRP by visual inspection of DPHI and TCMR logs. The effects that uncertainties in input parameters have on the outputs of the gas equations are studied using equations derived in Appendix A. Numerical examples using synthetic data and field data are used to demonstrate the relative insensitivity of the gas equation outputs to uncertainties in the inputs. The method is applied to field logs from three commercial gas and oil wells. In the first field example the gas effect on the neutron log is suppressed by thermal neutron absorbers and the neutron-density logs fail to show gas in a gas-bearing zone. The large separation between DPHI and TCMR identifies the zone as gas bearing. In the second field example, gas-corrected total porosity logs are compared to neutron-density logs and to porosity measurements on conventional core. Logs of gas-corrected total porosity including the uncertainties