Permeability Prediction of Sandstones Based on Mercury Intrusion Method

The use of the mercury intrusion method has been one of the most relevant trends in determining the permeability of porous media in the past decades. In this paper, general knowledge of sandstone reservoir evaluation is delineated including the pore distribution of sandstones and air permeability measurement. Based upon the paradigmatic study conducted by Purcell, a schematic diagram illustrating apparatus used in mercury intrusion is shown and introduced, and the relevant procedure is also outlined. Four significant permeability prediction models are described respectively and compared based on researches focusing on tight rocks. By doing so, this article reveals that the performance of the models is different despite the painstaking analysis and the significance of these studies. The contribution of this present study is providing a general reference of permeability prediction by mercury intrusion method as well as its previous momentous studies, giving a comparison among the given models.

Research on Quantitative Evaluation Methods and Influencing Factors of Natural Gas Reservoir Development

Current methods of evaluating the effects of gas reservoir exploitation primarily focus on evaluating production statistics of a well or field, and they often have a certain subjectivity. In order to further analyze key indexes that affect a gas reservoir during production, this paper considered the characteristic parameters of different types of gas reservoirs and established an index system of evaluating a gas reservoir “exploitation effect” from the three aspects of gas reservoir characteristics, rock characteristics, and economic benefits. There are numerous factors affecting the exploitation effect of a gas reservoir. The relationships between different factors are complicated, and the evaluation result of each factor can also be vague. A fuzzy optimization theoretical model for gas reservoir evaluation and optimization was established on the basis of a quantitative study on the evaluation parameters in fuzzy mathematics. In order to clearly understand the influence of each factor on the gas reservoir exploitation effect, numerical simulation was used to perform a multifactor numerical simulation study of the quantitative sensitivity to determine the sequence of different influencing factors in terms of influencing the gas reservoir exploitation effect. This study provides a quantitative scientific basis for the evaluation of gas reservoir exploitation effect.

Depositional Environments and Reservoir Evaluation of Otuma Oil Field, Niger - Delta basin, Nigeria

This study was carried out by using well logs to evaluate the depositional environments and hydrocarbon reservoirs in the Otuma oil field, Niger Delta basin. The gamma motif/model within- study interval in the drilled well shows blocky, symmetrical, and serrated shapes which suggest a deltaic front with mouth bar to a regressive - transgressive shoreface delta respectively. A correlation was done on the well logs across the wells and the ten well logs were used to evaluate the petrophysical characteristics of the reservoirs. The reservoirs showed highly porous and permeable channels where the wells were used for the characterization. The ten reservoirs were mapped at a depth range of 2395 m to 2919 m with thicknesses varying from 4m to 135m. The petrophysical results of the field showed that the porosity of the reservoirs ranges between 0.10 to 0.30, and permeability from 48 md to 290 md; the water saturation ranges from 0.39 to 0.52, and hydrocarbon saturation from the field 0.48 to 0.61. The By-passed hydrocarbons identified in low resistivity pay sands D4 and D3 at depth 2649 m to 2919 m, respectively were also evaluated and will be put to production in the field.

Design of a New Seismoelectric Logging Instrument

To increase the accuracy of reservoir evaluation, a new type of seismoelectric logging instrument was designed. The designed tool comprises the invented sonde-structured array complex. The tool includes several modules, including a signal excitation module, data acquisition module, phased array transmitting module, impedance matching module and a main system control circuit, which are interconnected through high-speed tool bus to form a distributed architecture. UC/OS-II was used for the real-time system control. After constructing the experimental measurement system prototype of the seismoelectric logging detector, its performance was verified in the laboratory. The obtained results showed that the consistency between the multi-channel received waveform amplitude and benchmark spectrum was more than 97%. The binary phased linear array transmitting module of the instrument can realize 0° to 20° deflection and directional radiation. In the end, a field test was conducted to verify the tool’s performance in downhole conditions. The results of this test proved the effectiveness of the developed seismoelectric logging tool.

A Cognitive Data-Driven Single-Well Modeling Workflow for Reservoir Deliverability Predictions – Expanding the Wireline Formation Tester Application Envelope

In today's dynamically challenging E&P industry, exploration activities demand for out-of-the-box measures to make the most out of the data available at hand. Instead of relying on time consuming and cost-intensive deliverability testing, there is a strong push to extract maximum possible information from time- and cost-efficient wireline formation testers in combination with other openhole logs to get critical reservoir insight. Consequently, driving efficiency in the appraisal process by reducing redundant expenditures linked with reservoir evaluation. Employing a data-driven approach, this paper addresses the need to build single-well analytical models that combines knowledge of core data, petrophysical evaluation and reservoir fluid properties. Resultantly, predictive analysis using cognitive processes to determine multilayer productivity for an exploratory well is achieved. Single Well Predictive Modeling (SWPM) workflow is developed for this case which utilizes plethora of formation evaluation information which traditionally resides across siloed disciplines. A tailor-made workflow has been implemented which goes beyond the conventional formation tester deliverables while incorporating PVT and numerical simulation methodologies. Stage one involved reservoir characterization utilizing Interval Pressure Transient Testing (IPTT) done through the mini-DST operation on wireline formation tester. Stage two concerns the use of analytical modeling to yield exact solution to an approximate problem whose end-product is an estimate of the Absolute Open Flow Potential (AOFP). Stage three involves utilizing fluid properties from downhole fluid samples and integrating with core, OH logs, and IPTT answer products to yield a calibrated SWPM model, which includes development of a 1D petrophysical model. Additionally, this stage produces a 3D simulation model to yield a reservoir production performance deliverable which considers variable rock typing through neural network analysis. Ultimately, stage four combines the preceding analysis to develop a wellbore production model which aids in optimizing completion strategies. The application of this data-driven and cognitive technique has helped the operator in evaluating the potential of the reservoir early-on to aid in the decision-making process for further investments. An exhaustive workflow is in place that can be adopted for informed reservoir deliverability modeling in case of early well-life evaluations.

Fractures and Flow Patterns Detection in Carbonate Reservoirs Using Intelligent Sensor Selection in a Deep Learning and Uncertainty Framework

4th Industrial Revolution (4IR) technologies have assumed critical importance in the oil and gas industry, enabling data analysis and automation at unprecedented levels. Formation evaluation and reservoir monitoring are crucial areas for optimizing reservoir production, maximizing sweep efficiency and characterizing the reservoirs. Automation, robotics and artificial intelligence (AI) have led to tremendous transformations in these areas, in particular in subsurface sensing. We present a novel 4IR inspired framework for the real-time sensor selection for subsurface pressure and temperature monitoring, as well as reservoir evaluation. The framework encompasses a deep learning technique for sensor data uncertainty estimation, which is then integrated into an integer programming framework for the optimal selection of sensors to monitor the reservoir formation. The results are rather promising, showing that a relatively small numbers of sensors can be utilized to properly monitor the fractured reservoir structure.

A Novel and Sustainable Generation of Advanced Mud Gas Logging System for Managed Pressure Drilling Applications: An Explorative Well Deployment from North Germany

Summary In the high risk Managed Pressure Drilling operations, increased certainty given by Mud Logging is a critical deliverable to guarantee a safe drilling environment even under challenging conditions and, to provide the first indications for reservoir evaluation. This paper describes a novel product application that successfully obtains advanced mud gas data from a Managed Pressure Drilling environment, proven in flow-loop and field applications (in Lower Saxony, Germany), by reducing service footprint as well as power consumption.

Saturation and Sigma Measurements in Carbonate Formations with Multiple Pulsed Neutron Technologies: Case Study from Southeast Turkey

This paper describes the petrophysical analysis resulting from operation of two independent pulsed neutron logging tools in the same cased hole well. The well was primarily carbonate and included many different subsurface formations located in the Southeast Anatolia Region of Turkey that included the Derdere, Karababa A, B, and C, Karaboğaz, Bozova, and Germav. Computing the mineralogy and saturation in these environments is challenging due to the complexity and low porosity of the formations that included mixed lithologies and organic shale. One of the objectives of this work was to demonstrate how the spectral data from the two tools was not only consistent, but that they could be combined to create an optimal petrophysical interpretation of the lithology, detailed mineralogy, porosity, and saturation of the formations within the well. Both tools employed a pulsed neutron generator capable of emitting 2 x 108 neutrons/second into the ambient formation. One was a 4-detector, 1-11/16-inch diameter reservoir evaluation tool, and the other was a single detector, 3-1/4-inch geochemical spectroscopy tool. In order to obtain the best possible results, a sound logging program was created that involved running the reservoir evaluation tool in 3 different modes of operation. This included the carbon/oxygen (C/O) mode, the sigma mode, and the gas mode. Stationary measurements were also obtained. The geochemical logging tool has only a single mode of operation. The resulting sigma measurements were in complete agreement. The sigma from the geochemical logging tool was corrected for the effects of diffusion. The advantage of the slim-hole reservoir evaluation tool is that the measurements from the 4th detector are diffusion-free. Data from the 1-11/16-inch reservoir evaluation tool from the gas mode did not reveal any bypassed gas zones in the well. Oil saturation was computed with the reservoir evaluation tool based upon three logging passes in the C/O mode. An important component of the interpretation was that it was supported by MCNP modeling that predicted the tool's response for hydrocarbon saturation. Although data from the geochemical spectroscopy tool was not used to determine saturation in this well, the resulting carbon concentration, that included kerogen as well as hydrocarbons, was completely consistent with the saturation computed from the reservoir evaluation tool.