Pore structure effect on reservoir electrical properties and well logging evaluation

The reservoir pore structure controls the reservoir quality and resistivity response of hydrocarbon-bearing zones and thus, critically affects logging interpretation. We use petrophysical data in three types of reservoir with different pore structure characteristics to show that the complexity of pore structure had a significant effect on the effective porosity and permeability regardless of geological factors responsible for the formation of pore structure. Moreover,, the distribution and content of conductive fluids in the reservoir varies dramatically owing to pore structure differences, which also induces resistivity variations in reservoir rocks. Hence, the origin of low-resistivity hydrocarbon-bearing zones, except for those with conductive matrix and mud filtrate invasion, is attributed to the complexity of the pore structures. Consequently, reservoir-specific evaluation models, parameters, and criteria should be chosen for resistivity log interpretation to make a reliable evaluation of reservoir quality and fluids.

Logging Evaluation of the Ordovician Carbonate Reservoir Beds in the Lungudong Region,Tarim Basin

In recent years, great progress has been made constantly in oil and gas exploration in the Lungudong region of the Tarim Basin. However, progress has been slow in the evaluation of its main oil-producing horizons -- the Ordovician carbonate reservoir beds. Based on previous researches and on the various data such as drilling, geology and oil test, in combination with the interpretation of each single-well imaging and conventional logging data, and through analysis and comparison, the identification methods in imaging and conventional logging for four types of carbonate reservoir beds in this region are summarized in this paper. Calculation formulas for four reservoir bed parameters, i. e. shale content, porosity, permeability and oil saturation in this region are proposed; and reservoir beds in this region are divided into three levels （Ⅰ, Ⅱ and Ⅲ） by combining oil test data and logging data, The lower limits of the effective porosity of reservoir beds and the fracture porosity of effective reservoir beds are determined as 1.8% and 0.04%, respectively. The physical property parameters are calculated by conventional logging curves, and the most advantageous areas for reservoir development are predicted comprehensively. On the plane, the high-value zones of reservoir bed parameters are mainly concentrated in the N-S-trending strike-slip fault, the Sangtamu fault horst zone and near the LG38 well area; vertically, the reservoir bed parameters of the Yijianfang Formation are better than those of the Yingshan and Lianglitage formations.

Logging Evaluation Method of Low Resistivity Reservoir——A Case Study of Well Block DX12 in Junggar Basin

The Hutubi （呼图壁） River reservoir of well block DX12 is a lithologic hydrocarbon reservoir that is under tectonic settings. The main oil-bearing sand body in this area is thin and has a poor transverse connectivity. Because of the complexity of the oil-water relationship, the oil reservoir presents a low resistivity feature, which brings great difficulties to hydrocarbon reservoir identification. This article develops an effective method of well log interpretation that can meet the requirement of low resistivity reservoir well logging evaluation. The authors combine the oil reservoir geology feature, the oil well logging curve characteristics and chemical analytical data to analyze the reasons for low resistivity, then establish the appropriate reservoir parameter explanation model, which uses different saturation computational methods according to different generations. When the clay content is more than 5%, we select W-S dual water model; when the shale content is more than 13%, we use the Schlumberger formula; when the shale content is less then 13%, we use Archie＇s formula. The well logging evaluation method of low resistivity reservoir has been improved by the irreducible water saturation formula which is established by the permeability, the porosity, the coefficient of pore structure and the shale content, hydrocarbon reservoir recognition charts, and the non-resistivity logging methods （repeat formation test （RFT）; modular dynamic test （MDT）, etc.）. The coincidence rate for this arrangement of the well logging integrated interpretation is 82.6% in the well block DX12. It is a powerful direction for low resistivity well log interpretation.

Identification and Evaluation of Low Resistivity Pay Zones by Well Logs and the Petrophysical Research in China

This paper presents an overview of petrophysical research and exploration achievements of low resistivity pay （LRP） zone by well logs in China. It includes geological characteristics and characteristics of well log response of the low resistivity pay zones discovered and evaluated in recent years, as well as the problems in recognizing and evaluating low resistivity pay zones by well logs. The research areas mainly include the Neogene formations in the Bohai Bay Basin, the Triassic formations in the northern Tarim Basin and the Cretaceous formations in the Junggar Basin, The petrophysical research concerning recognition and evaluation of the low resistivity pays, based on their genetic types, is introduced in this paper.

Identification of watered-out zones in carbonate reservoirs using resistivity curve reconstruction based on reservoir classification

The KT-II layer in the Zananor Oilfield,Caspian Basin,Kazakhstan,contains carbonate reservoirs of various types.The complex pore structure of the reservoirs have made it difficult to identify watered-out zones with traditional logging interpretation methods.This study classifies the reservoirs on the basis of core analysis and establishes an identification model for watered-out layers in the field to effectively improve the interpretation accuracy.Thin section analysis shows that there are three types of pores in the reservoirs,i.e.,the matrix pore,fracture and dissolution vug.A triple porosity model is used to calculate the porosities of the reservoirs and the results are combined with core analysis to classify the reservoirs into the fractured,matrix pore,fracture-pore as well as composite types.A classification standard is also proposed.There are differences in resistivity logging responses from the reservoirs of different types before and after watering-out.The preewatering-out resistivities are reconstructed using generalized neural network for different types of reservoirs.The watered-out layers can be effectively identified according to the difference in resistivity curves before and after watering-out.The results show that the watered-out layers identified with the method are consistent with measured data,thus serving as a reference for the evaluation of watered-out layers in the study area.

Complex Exploration Techniques for the Low-permeability Lithologic Gas Pool in the Upper Paleozoic of Ordos Basin

The Ordos basin is a stable craton whose late Paleozoic undergoes two sedimentary stages: from the middle- late Carboniferous offshore plain to the Permian continental river and lake delta. Sandstones in delta plain channels, delta-front river mouth bars and tidal channels are well developed. The sandstones are distributed on or between the genetic source rocks, forming good gas source conditions with widespread subtle lithologic gas pools of low porosity, low permeability, low pressure and low abundance. In recent years, a series of experiments has been done, aimed at overcoming difficulties in the exploration of lithologic gas pools. A set of exploration techniques, focusing on geological appraisal, seismic exploration, accurate logging evaluation and interpretation, well testing fracturing, has been developed to guide the exploration into the upper Paleozoic in the basin, leading to the discoveries of four large gas fields: Sulige, Yulin, Wushenqi and Mizhi.